In this paper, we explore a perspective on well-being in the context of digital nomads, reporting the first findings of an empirical study investigating the extent to which the nomadic lifestyle enables a healthy life and the enjoyment of well-being. Following the Gioia methodology, we collected and analyzed textual data from posts in a specific online Reddit social network discussion community to do this. Preliminary findings indicate that Fear of Missing Out (FOMO) acts as a trigger that stimulates the adoption of digital nomad lifestyles.

Software systems are critical resources for our daily lives. Due to that, computer science students need to learn software engineering knowledge and skills to develop software systems with the expected quality, under budget, and on schedule. The size and complexity of software systems and the short time to market make it necessary to have various software developers working as a team. In this scenario, the success of a project depends on coordination, communication, and collaboration. The evolution of network, communication, and computer technologies made it possible for people from different countries to work on the same project. Therefore, software engineers must collaborate remotely with others in Global Software Engineering (GSE) projects. Hence, students must also learn how to collaborate with people from different countries, with specific expectations, and different cultures and languages. This study lists the main GSE challenges the students must be ready to deal with, how researchers have addressed GSE, and how GSE education has been approached in the last five years. Researchers focused on teaching approaches, what students experienced during GSE courses, and the importance of GSE in industry. Students had the opportunity to face unsolved GSE challenges, and GSE courses still need to be improved.

The learning game “Present of the Future” has shown great potential as an effective tool for promoting futures literacy and speculative design in various educational and professional contexts. Through interactive and collaborative scenarios, participants are encouraged to explore future possibilities and develop creative solutions to contemporary challenges. Despite its promising impact, the game still lacks a structured and systematic process for evaluating the user experience on three levels: the immediate reaction to the game experience, the retention of learning in the short and long term, and collaboration in creating future artifacts. We propose a detailed experiment and an evaluative questionnaire composed of open and closed questions to fill this gap and provide a foundation for critically analyzing these dimensions. Although the experiment has not yet been conducted, the research establishes a robust theoretical and methodological framework that will allow, in future stages, the collection and analysis of quantitative and qualitative data to complement and enrich this study. Thus, we expect that the future application of these practices will contribute to a deeper understanding of the pedagogical and collaborative effects of the game.

With the advancement of Artificial Intelligence (AI) technologies, the world has been increasingly reshaped across multiple domains - healthcare, finance, education, and creative fields. This expansion transforms individual tasks and facilitates complex collaborations where humans and machines work to- gether in unprecedented ways. Through machine learning and, more specifically, large language models (LLMs), AI now plays a crucial role in enhancing productivity. Recent technological advancements have significantly boosted the text generation capabilities of LLMs, enabling them to simulate personas that can represent groups or specific well-known individuals. By simulating expert perspectives, LLMs provide insights to guide human decision-making across various collaborative frameworks in Computer-Supported Cooperative Work (CSCW). Personas, as simulated identities, have proven helpful in group brainstorming sessions, consensus-building exercises, and virtual advisory boards, which help represent diverse viewpoints and facilitate group decisions. Among these CSCW methods, the Delphi method is a well-established approach for reaching consensus among experts through iterative feedback and structured discussions. This work introduces a framework to manage and evaluate LLM-generated personas simulating expert input in Delphi studies. Our contributions include a framework designed for evaluating LLM personas in Delphi studies using a text similarity validation technique comparing real and simulated expert opinions and an evaluation of a Delphi about Brazilian higher education, assessing the LLMs' reliability in real-world scenarios. Findings show LLMs can effectively replicate expert perspectives, enhancing AI integration in specialized decision-making.

The polarization of ideas is a natural phenomenon of human behavior. When productive, it can generate scenarios for reflection on arguments, opinions, and interactions, but when polarization is extreme, it generates social isolation, manipulation, perception of injustice, unproductive debates, certainties of absolute truths, fanaticism, feelings of hatred, and even wars. Deconstructing the ecosystem of extreme polarization directly benefits social stability. Virtual social environments are excellent scenarios for fostering debates, negotiations, and the exposition of ideas. The objective of this study is to use the same virtual social ecosystem with its empowerment mechanisms and influence attributes to support the creation of tools, functionalities, and simulations to develop healthier systems. The knowledge generated supported the development of a design and cognitive ethical affordances practiced in metacognitive design, optimized navigation, and metacognitive simulations. The cognitive, ethical affordances incorporated into the Productive Reinforcement Spiral method model were part of a metacognitive simulation of collaborative negotiation with a productive reinforcement spiral mechanism, whose description and evaluation of the design are the main objectives of this paper.

In light of the increasing recognition of environmental and social challenges, technology-driven corporations often face significant barriers in aligning their innovation-driven goals with sustainable practices. Despite their capacity for rapid technological advancements, these companies struggle to integrate sustainability objectives into their core strategies due to competing priorities and a lack of cohesive frameworks. This study explores Knowledge Management’s (KM) capacity to facilitate and implement sustainable practices. We use the Rapid Review methodology to systematically review the literature and achieve this objective. A total of 35 articles were analyzed, examining factors related to organizational knowledge, the adoption of KM within technology-driven companies, and effective sustainable practices. The results highlight the importance of KM in facilitating and implementing sustainable practices, showing that technology-driven companies that invest in organizing their knowledge can improve their effectiveness in implementing sustainable initiatives, increase their resilience and competitiveness, and strengthen trust with stakeholders.

In recent years, artificial intelligence (AI) has advanced rapidly, transforming various sectors of society and delivering value to governments, businesses, and end users. However, these advances have also increased computational costs and training times, resulting in significant energy consumption by AI systems. This situation highlights the urgent need for regulatory discussions and proposals that guide AI development and innovation toward energy sustainability. This work reviews, organizes, and categorizes recent regulatory policies for AI energy sustainability into four dimensions for trend analysis. The results show that most identified policies concentrate on transparency and energy efficiency, indicating a higher maturity of these measures within regulatory discussions. This work seeks to raise awareness among stakeholders involved with AI and sustainability, encouraging reflections on energy consumption and efficiency to build a more sustainable future.

Traditional methods for Technology Foresight often struggle to keep up with the fast changes in technology. This work looks at how crowdsourcing can improve Technology Foresight by using collective intelligence to spot trends and tackle complex problems. The goal of this research is to overcome the limits of traditional approaches by using online platforms and new technologies like big data and machine learning to make innovation more accessible. We examine how to apply crowdsourcing effectively in Technology Foresight, discussing its benefits, challenges, and real-world uses. We used a Rapid Review (RR) approach, combined with Large Language Models (LLMs), to refine how we select and analyze research. This method helped us find important insights and categorize applications in different areas. The findings show that crowdsourcing can speed up technology forecasting by bringing in diverse viewpoints and encouraging collaboration across fields. Examples include its use in urban planning, disaster management, and open innovation platforms. Furthermore, combining crowdsourcing with advanced technologies enhances its effectiveness in foresight processes. This work offers practical advice for organizations that want to use crowdsourcing in their innovation strategies and suggests future ways to integrate new technologies into Technology Foresight.

Collaborative crowdsourcing has evolved over recent years as a problem-solving model that builds on interactions that take place within crowds or self-organizing teams that form and dissolve in response to an open call. Unlike microtasking, its effectiveness depends primarily on collective actions rather than individual efforts, particularly for non-decomposable tasks that require a certain level of interdependency. Although social news curation has gained attention as a means of empowering both citizens and journalists, there is a need to understand the components and constraints that shape this online crowdsourcing activity when mediated by artificial intelligence (AI). In response to this gap, this paper reimagines the traditional social news curation model through a design fiction prototype consisting of a personalized AI system and user-driven social curation activities. In a highly polarized opinion and political climate where propaganda, misinformation, and extreme polarization take on a dominant framing to generate social chaos, the envisioned solution seeks to model healthy and trustworthy socio-algorithmic interactions towards a more democratic and relevant form of news curation.

The rise of artificial intelligence agents and information technology platforms governed by data-driven algorithms has had profound impacts on the way knowledge work is managed and carried out. Concerning the novel uses of digital work platforms, the arising tensions might suggest that the socio-technical design frameworks adopted by major tech firms are becoming less viable and in some cases ineffective. We propose a conceptual architecture to support a socio-technical framework for exploring Personal Knowledge Ecologies in the context of the digital knowledge economy. This framework aims to increase the degree of individual freedom for the interoperation of these knowledge information infrastructures.

Future-related studies are key in identifying and predicting emerging technologies, fostering innovation, and driving scientific progress. Games have increasingly served as a tool to engage researchers in Technology Forecasting and Foresight activities, presenting a gamified approach to gather, analyze, and synthesize information to allow future foresight. In this work, we use the Rapid Review methodology to analyze the scientific literature and explore the use of games as tools for Technology Forecasting and Foresight. We analyzed and categorized the articles by theme and type of study, identifying the areas where games can be most beneficial to guide professionals performing Technology Forecasting and Foresight, helping companies and governments better understand the future. The empirical evidence found provides a comprehensive understanding of how games can enhance foresight activities and contribute to the success of Technology Forecasting and Foresight initiatives. Our analysis also provides insights for future research about gamified strategies in Foresight.

Since 2016, the demand for remote work has grown by nearly 400%, with 3.5 million remote job vacancies posted, and it is expected to continue to grow in the coming years. Therefore, one of the challenges in advancing remote work is fostering innovation, particularly serendipity, in a remote workforce. This fortunate discovery can pave the way for technological advancements, new business strategies, or even scientific revolutions. However, creating moments of serendipity in a remote work environment is a significant challenge. Thus, finding the right approach to stimulate serendipity in a remote work environment is an ever-evolving challenge. Therefore, this work aims to understand the possibilities of serendipity that collaboration tools used in remote work can support. The methodology used for this work was a Rapid Review. First, we explore the factors related to serendipity in physical offices, for which we identified twenty-three elements. Next, we compiled 38 strategies for remote work that were found to promote serendipity, which we organized in a framework for better observation. Our findings can serve as a starting point for designing new tools and identifying existing software and tools that already play a supportive role.

Recent Artificial Intelligence advancements raise concerns about the future of work, particularly technological unemployment. Studies show automation's impact, but tools like ChatGPT disrupt even traditionally secure professions like programming. In this study, we reevaluate AI's effects using a method to assess the impact of Generative AI technologies on occupations to understand the potential effects of Generative AI systems on software development work. Valuable insights were obtained by gathering the view of a group of workers, primarily composed of developers who are starting their careers, regarding the impact of these technologies on the tasks they perform to provide a comprehensive understanding of the implications of Generative AI for software development. Results show that all programming tasks performed by these workers would experience some impact by Generative AI -65% of the tasks being considerably impacted, 12% moderately impacted, and 18% minimally impacted. This analysis highlights the substantial influence of Generative AI technologies on software development, mainly affecting those in the early stages of their career. The results of this work contribute to the academic community with valuable information. Policymakers can also use this information, as this work provides a comprehensive view of the impacts of Generative AI on software developers, considering their direct impact on job tasks.

We analyze datasets collected by the Center for Applied Internet Data Analysis (CAIDA) and the Réseaux IP Europeéns (RIPE) sites to demonstrate the efficacy of machine learning models in predicting Internet outages and disruptions that affect and hinder network access to essential services and humanitarian aid in times of conflict. Custom datasets for specific geographic areas are created using data filtering. A sliding time window transformation was applied to design models that accurately predict disruptions. Model performance is evaluated based on the prediction accuracy using Internet Outage Detection and Analysis (IODA) and RIPE datasets.

The growth and diversification of public debate made it possible for civil society to become more participatory in decision-making processes. In other words, it enabled citizen participation, which is the interaction between civil society and public authorities to solve problems. Furthermore, with the development of information and computer technologies, citizen participation has expanded into the digital realm, giving way to electronic participation or e-participation. However, in this context, citizen engagement still is a challenge. As a result, different researches have been carried out to identify strategies that can increase engagement so that electronic participation is effective. One of these fields aims to improve users' experience and the usability of electronic participation tools by using gamification to enliven participatory activities. The purpose of this article is to carry out a systematic mapping study of the literature as a way of better understanding the impact caused by gamification on citizen participation. Thus, 75 papers were selected and classified, allowing the identification of research methods, application contexts, forms of participation, and game elements used. This mapping enabled the following discoveries: design and prototyping is the most carried out research method for studying gamification in citizen participation, and civic engagement was the most analyzed context. Furthermore, the development of tools mainly focused on asking the population their opinions on policy issues to create a partnership between government and civil society.

The Massification of remote work, in response to the COVID-19 pandemic, has been causing significant changes in productive and working arrangements, both for individuals, organizations, and society. At the level of personal life philosophy, for example, this transformation can be evidenced in the dissemination of digital nomadism values such as work/leisure balance among corporate workers. On the other hand, at the level of gig/crowd work platforms, the emergence of tensions may indicate the exhaustion of sociotechnical design models adopted by big techs. We show how evidence collected from digital nomads in empirical ethnography studies can inform HCI/CSCWD researchers of design-oriented strands to explore emerging opportunities in new creative digital crypto-economic ecosystems. Finally, we present a proposed research agenda to explore DNs’ activities in the crypto-economic ecosystem.

This paper explores the challenges and strategies used to design, build and evaluate a collective intelligence (CI) model to support discussions about cities. Through an autoethnography of ideas and discussion practices in both online and offline contexts, this work explores the tensions between the chosen methodological approaches, including design science research (DSR) and participatory action research (PAR). Moreover, we also examine the challenges and pitfalls observed during the practical conduction of this research when involving participants in the process of empirically evaluating the proposed model. Finally, aspects related to the autoethnographic process itself as a reflective method are discussed alongside the consequences of desiring and seeking participation in the research process.

Healthcare practitioners are professionals with highly specialized knowledge leaving a vast gap between them and their patients. Mobile Health applications may provide a fast and precise diagnosis to patients through expert systems and chatbots. We surveyed and classified Mobile Health apps, discussing their advantages, such as lower costs and replicability. However, most technologies lack the common sense and creativity to solve individual cases, and their precision is far from that of humans. Mobile Health is a relatively new field, and new technologies will be developed in the future, changing the current balance in favor of machines but not replacing healthcare professionals completely. This trend should be watched closely by those interested in healthcare, given its potential for the improvement of patient treatment and also their capacity to disrupt healthcare professionals’ formation and work. Therefore, this work contributes to understanding the capabilities and limitations of mHealth apps in providing medical diagnosis and treatment.

Shopping tools are widely used by millions of users to find the best deals in different marketplaces worldwide. In this work, we introduce the concept of crowdsourced deals, which refers to deals found and shared by a crowd of potential consumers. We analyze various crowdsourced deal tools and highlight their features. By formalizing collaboration in certain types of bargain-hunting tools, we can develop new techniques to improve the user experience and attract more contributors to maintain an active and stable community. Understanding the concept of crowdsourced deals can also benefit organizations looking to increase their sales and analyze their online reputation. Bargain-hunting tools provide a form of marketing that we can refer to as online word-of-mouth advertising, which is crucial in today’s consumer society, similar to well-known word-of-mouth advertising.

In this paper, we continue our investigations on digital nomadism and the impact of COVID-19 pandemic on the work-related aspects and lifestyle of digital nomads (DN). The findings presented in this empirical study reflect the analysis of the impact of COVID-19 outbreak (and its waves) on the market economy and work-life boundaries of DNs as perceived from posts and comments gathered from a Reddit community during the period of early March 2020 until the end of 2022. From this point, our results indicate that the massification of remote work among formal workers in response to COVID-19 pandemic has impacted both the formal labor market and the DN ecosystem. As a consequence, we argue that digital nomadism tends to play a critical role beyond work from (almost) anywhere (WFA) in a post-COVID-19 era taking into account the novel facets of nomadic work-lifestyle.

In this paper, we report on new findings about the results of an empirical study which aims to investigate how the COVID-19 pandemic has been shaping nomadic work practices and also challenging the lifestyles of digital nomads (DN). To do this, we collected textual data from posts in a Reddit community. We argue that, in order to understand how to design technical solutions for the so-called ‘new normal’ working conditions, one way to approach this is to understand how digital nomads are being impacted in their work practices and routines, and also how they are seeing the future of their technology-mediated work-life space. Finally, we show how evidence collected from DNs about their experiences and difficulties perceived during the pandemic period can inform CSCW researchers worldwide about future design-oriented strands.

In recent years, digital technologies have been used to support discussions about the city and also to involve citizens in participatory public processes. However, despite the widespread use of social media platforms, old issues related to engagement and participation still persist in digital initiatives. The main goal of this study is to carry out an empirical evaluation of a collective intelligence model that combines crowdsourcing and social storytelling to support discussions about the city from a bottom-up perspective. Within a design science research approach we designed a participatory action study that was carried out through a workshop with students and professionals from different areas, such as architecture, urban design and information technology. As a result, we were able to assess whether the collective intelligence model was acceptable to the participants by investigating whether the behavioral assumptions were valid and thus outlining some contributions to the field of urban informatics.

In the process of creating a Technological Roadmap, a large amount of data must be analyzed, and future events may be spread across several document databases, making it harder to researchers retrieve all future events described in these publications in a timely fashion. Technology Roadmapping is a time-consuming and error-prone method that usually requires a group of experts to be properly executed. This work presents NERMAP, a collaborative system capable of semiautomating the Technology Roadmapping process, through the Named Entity Recognition method. The evaluation showed that NERMAP is capable of retrieving up to 83% of future events in documents. Furthermore, the system was also able to identify some future events that our validation team missed. By using the system, researchers can perform the analysis in considerably less time, thus reducing costs. Therefore, the proposed system enables a small group of researchers to analyze a large number of documents in a short time, streamlining their ability to identify, process, and analyze information in the form of roadmaps.

The Internet of Everything (IoE) is the paradigm of intelligent services that supports a ubiquitous and always-connected world of smart sensors and actuators, human and non-human in a cyber-physical lifestyle. Recent years have witnessed the fast proliferation of smart devices. In addition, these functional smart sensors possess powerful computation and communication capabilities and contribute to intelligent services outcomes of IoE-based applications. Then by adopting a knowledge-based approach on sensors smartness, we make a comparative assessment and classify smart sensors (image sensors, temperature sensors, proximity sensors, speed sensors, and sound sensors) regarding intelligence levels. We extracted valuable conclusions and inferences from this classification, providing insights and future directions towards promised benefits offered by distilled intelligence in smart sensors applications. (Abstract)

The purpose of this paper is to reveal a set of new results obtained from an ongoing investigation focused on the way that the particular characteristics which are inherent to “wannabe” digital nomads’ activities contribute to the sustainability of the whole digital nomad ecosystem. In line with the premise of this research, we assume the importance of understanding the impacts that are being felt in the personal knowledge management ecology practices and routines of digital nomads as experienced by a specific online population (i.e., Reddit user base), together with a deep and wide examination of their preferences and expectations regarding the technology-mediated work-life issues that exert a direct influence on the digital nomad community. To this end, we gathered and further processed text posts and comments from users in the ‘/r/digitalnomad’ subreddit. From a sociotechnical standpoint, the empirical data extracted from this sample population about the wannabe/how to be digital nomad symbiotic ecosystem can provide insightful information for researchers worldwide about future design-level interventions.

With a growing demand for new technologies, concepts such as the Internet of Everything (IoE) – in which smart sensors (humans and machines) connect, communicate, and share information from the surrounding environment – are gaining notoriety. Thus, this study focuses on developing a knowledge flow model in the IoE scenario for Smart Cities, including how knowledge is disseminated in these intelligent environments in human-to-machine interactions. The study considers a knowledge-based taxonomy defined for IoE environments and supports the full realization of IoE applications through a knowledge management strategy. The proposed IoE Knowledge Flow Model contributes to identification of knowledge flows related to IoE architecture layers in smart city applications.

In recent decades, technological advances have exponentially accelerated the search for digital transformation. The use of technologies based on Artificial Intelligence (AI) is essential to achieve these goals. In this work, we investigate the future trends in the field. We conducted a systematic review and analyzed their content with a methodology based on Future-Oriented Technology Analysis (FTA) techniques. We have identified 30 future events related to digital transformation and AI and their respective feasible years. Our findings are categorized into industry fields: business process management, construction industry, digital economy, human resources, healthcare, industry, social innovation, tourism, and education. Our work allows decision-makers to draw up strategies, map the paths to be taken, and better prepare for their future needs, using AI as a tool for value aggregation.

We report the first findings of an empirical study aimed at investigating how COVID-19 pandemic has impacted the work practices and lifestyles of digital nomads (DN). To do this, we analyzed messages, questions and comments posted by digital nomads in a specific online discussion community of the Reddit social network. Preliminary findings indicate COVID-19 as an opportunity to test DN lifestyle by aspiring digital nomads who want to plan their careers and also present evidence of an overload of online channels for actual DNs. On the other hand, we found that much of the literature on digital nomadism is fragmented and scattered through different disciplines and perspectives, with a strong focus on digital nomads' lifestyles. In order to obtain a holistic and unified understanding of digital nomads, we conducted a comprehensive literature review to further conceptualize the phenomenon under study.

Over the past decades, the use of digital technologies to support participatory urban planning and design has been repeatedly described as a crucial instrument and critical building block for tackling historical problems of participation in such processes. Social media, e-participation platforms, and crowdsourcing applications are examples of technologies that can involve citizens in decision-making processes and thus leverage the benefits of collective intelligence. However, despite the extensive use of social media platforms, old problems related to engagement and participation still occur in digital initiatives. Successful collaboration examples between citizens, policymakers, and strategic stakeholders are still scarce based on online social practices. This study aims to introduce a collective intelligence model, which combines crowdsourcing and social storytelling to support participatory urban planning and design from a bottom-up perspective. The paper concludes by discussing a scenario where citizens can engage in mapping, taking photos, sending ideas, or even creating collective stories about their university issues in a post-pandemic future.

It has been a quarter of a century since the publication of the first edition of the IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD) held in 1996 in Beijing, China. Despite some attempts to empirically examine the evolution and identity of the field of CSCW and its related communities and disciplines, the scarcity of scientometric studies on the IEEE CSCWD research productivity is noteworthy. To fill this gap, this study reports on an exploratory quantitative analysis of the literature published in the IEEE CSCWD conference proceedings with the purpose of visualizing and understanding its structure and evolution for the 2001-2019 period. The findings offer valuable insights into the paper and author distribution, country and citation-level productivity indicators, degree of collaboration, and collaboration index. Through this analysis we also expect to get an initial overview of the IEEE CSCWD conference concerning the main topics being presented, most cited papers, and variances in the number of keywords, full-text views, and references.

The paradigm of the Internet of Everything (IoE) adds value to Internet of Things (IoT) in connections among people, processes, data, and things. However, knowledge creation process in IoE context still requires concerns to what extent connected sensors and actuators collaborates in value created and outcomes of IoE applications. This study focuses on the requirement and design approach for identification of critical knowledge within IoE domain though a knowledge ranking approach. Existing solutions for semantic definitions and taxonomies in IoE are reviewed for this purpose. In addition, this work proposes the use of a knowledge-based taxonomy as the main driver for ranking knowledge in smart sensors as IoE enablers with a qualitative approach of its dimensions. To the best of our knowledge, this is the first work that comprehensively integrate a taxonomy concerning ranking knowledge in IoE applications.

Citizen engagement in building user-curated narratives of complex or long-lasting news stories has been the key foundation of the design and implementation of the Acropolis virtual environment. Previous user studies have shown, by positive evidence, that this goal can be pragmatically achieved, but the challenge now lies in assessing: a) the extent to which an environment like Acropolis can be used to empower citizens; and b) whether and how the tool could be used to support the work of professional curators. Findings from a focus group study highlighted the tool's potential to engage citizens with news, the usefulness of the environment to build virtual memories, and the convenience of using Acropolis to support professional journalistic work.

Over the past decade, online crowdsourcing has established itself as an emerging paradigm that industry and government have been using to harness the cognitive abilities of a multitude of users distributed around the world. In this context, microtask crowdsourcing has become the method of choice for addressing a wide range of diverse problems. Microtasks typically require a minimum of time and cognitive effort, but combined individual efforts have made it possible to accomplish great achievements. The goal of this paper is to contribute to the ongoing effort of understanding whether the same success that microtask crowdsourcing has achieved in other domains can be obtained in the field of social news curation. In particular, we ask whether it is possible to turn online news curation, typically a social and collaborative activity on the Web, into a model in which curatorial activities are mapped into microtasks to be performed by a crowd of online users.

In the last decade, games with a purpose (GWAP) have emerged as an effective way to recruit and organize a large number of volunteers to help address difficult challenges. In previous work, a framework for crowdsourced collection, cleaning, and measurement of digital content was presented and used in the design of Cassino Musical, a game for procuring and measuring the musical talent of unknown artists. Preliminary results from an online experiment with the game provide basic proof that GWAP can be successfully applied to the task of measuring musical talent, and are described in this paper.

Worldwide, the electricity sector has undergone radical changes with the emergence of new technologies that expand possibilities. In such a dynamic environment, the sector's regulatory and supervisory activities became major challenges. In this article, we present a case study on the collaborative design of a digital platform for learning, accessing information and fostering the collaboration between distributors, the regulatory agency and electricity consumer councils in Brazil. A series of national surveys were conducted with industry authorities, experts, representatives of electricity distributors and representatives of final consumers. Finally, we present the results of these surveys, which allowed the derivation of primary requirements for the design of the collaboration platform that is under development.

Organizations often use one or more knowledge-based approaches in order to structure and promote their Intellectual Capital (IC), ensuring flexibility and resilience in an environment of constant change, competitiveness and innovation capabilities. In this context, Knowledge Management (KM) and Future-oriented Technology Analysis (FTA) are two research topics that have been used by organizations. However, organizations usually do not use both KM and FTA. Moreover, when they use both, they apply them as separate initiatives. Therefore, applying KM and FTA together produce many challenges. In this direction, this work presents a framework that uses FTA to improve KM processes through the use of the IC, as well the use of KM processes to improve FTA Strategies. Moreover, the proposed framework forms a virtuous circle, in which KM processes, Intellectual Capital and FTA strategies interact producing a mutual benefit.

In recent years, social curation technology has been successfully promoted as a means of addressing the problem of involving citizens with news content. Sites like Facebook., Reddit and Storify., just to name a few, allow their users to discuss, comment., share, identify and review news content from various sources. A key goal of this paper is to analyze the process of social validation in the context of Acropolis, a social computing platform that allows citizens to build and share their own narratives about complex or long-term news stories. The sense of social validation determines an increase in self-esteem, self-confidence, and instant happiness, when conveniently engendered in virtual environments.

The practice of Knowledge Management within the scope of the Brazilian Federal Government advocates achieving the strategic objectives of organizations, aiming the provision of better services to society. Such improvements can be achieved by acquiring new knowledge or transforming existing knowledge, that although belong to the organization could be equally useful to other organizations. However, internal rules of organizational confidentiality, the lack of motivating and integrative policies make these organizations closed in the aspect of the transfer of acquired knowledge to other organizations, leading to efforts and redundant spending to acquire new knowledge. In this paper, we propose the creation of a Knowledge Management service bus for Federal Government organizations, aiming the transfer of knowledge among their organizations thought software interoperability. Therefore, our proposal enables, beyond the software interoperability among the participating organizations, the creation of Knowledge Management Systems' standards.

The content creation process on the Internet changed with the emergence of Social Networks, with the volume of information overgrowing. Unfortunately, social networks have shown a high potential for disseminating hoaxes and, more recently, fake news. This fact encouraged the emergence of fact-checking organizations, usually carried out by journalism organizations. However, they have limitations to meet the enormous demand arising from the immense volume of fake news currently on the Internet. Thus, this study proposes a crowd-based solution as a way to meet this high demand for fact-checking. The proposed fact-checking process uses crowdsourcing to performing the filtering, analysis and classification of news. In this way, we can use a checking mechanism that may scale proportionally to the creation of fake news.

The construction of a Gold Standard Corpus for Plagiarism Detection (GSCPD) is a challenging task for reproducible research in computer science, given that there is a trade off between the time expended by the experts and the size, quality, and reliability of a GSCPD. In such a challenging scenario, this paper describes a framework to support the construction of a GSCPD in any language. Aiming for reproducibility and scalability, the framework involves a data acquisition process and a Crowd Science project that employs human processing power to identify plagiarism in pairs of textual data extracted via the data acquisition process. This papers also presents the application of this framework in Portuguese language and the preliminary results of a feasibility study about the use of a tool that composes the framework.

The labor market is becoming increasingly competitive, with new technologies and products being launched at all times.Companies that have the privilege of creating the products at the beginning of innovation can serve more customers and thus generate more profits.In this search for the market, companies are increasingly willing to please their customers, trying to understand what they seek.There are several concepts, ways, strategies, and technologies that help companies better understand what people are searching for, interfering with this market.These strategies include Futureoriented Technology Analysis (FTA) and others, such as Knowledge Management (KM), from which we focus on Technological and Participatory practices.These strategies are directly related bringing a fundamental advantage to the company that knows how to use these concepts effectively.

In the long run, technologies positively impacted work and, in general, brought benefits to society as a whole. However, history also shows that the first generations coexisting with new technologies had their jobs profoundly impacted both in terms of quantity and quality. As we enter the 4thIndustrial Revolution, computing has been one of the key technologies that impact work and its advancements must be accompanied with special care. Computation not only impacts work but is also a powerful tool to support the construction of knowledge and proposition of actions on the technologies that disrupt work. This paper proposes the development of a computer system that allows workers themselves to evaluate the technologies that will impact work in the future. We present each stage of the application of the Design Science Research methodology for developing the system. The artificial evaluation of the resulting prototype shows its utility and opportunities for improvement.

The Joint Planning Process of the Brazilian Ministry of Defense comprises the elaboration of possible courses of action (COA) to be adopted in a joint operation. The Commander, advised by his General Staff, assesses each COA and selects subjectively the one that best meets the mission statement. Such decision-making process has no simulation tool to assist the Commander and his General Staff in confronting their own COA with possible enemy COAs. We analyzed how the Brazilian Ministry of Defense (MD) codifies knowledge in such simulated confrontation, their structures and the knowledge flow. Starting with the information from MD doctrines, we structured the explicit knowledge in models and diagrams, which describe business processes, taxonomies, conceptual maps, and mental maps. Understanding the knowledge creation process increases the efficiency of an operation, while reduces confrontation errors, minimizing revision efforts and optimizing the use of the operational capabilities of the Armed Forces.

The ubiquity of smartphones creates great opportunities for participatory sensing, where people can implicitly contribute observations about their local environments through sensors such as cameras and accelerometers. The collected data can then be aggregated and used to benefit the crowd in some way. In this paper, we report on the current development of Sherlock, a device capable of automatically detecting the presence of people in localities through evidences left by smartphones called probe requests, without any user intervention. To validate the proposed mechanism implemented in the device, we performed an experiment with ten participants in six rounds where it was possible to automatically detect 41 presence events, of which 66% could be detected within less than 30s. The implicit crowdsourcing mechanism behind this approach may allow real-time monitoring of people flows in public environments, which can enable, among other things, energy systems to be automatically orchestrated according to demand, reducing associated costs.

Acropolis is a social computing platform especially designed to engage citizens in building and sharing their own narratives about complex or long-term news stories. The first two design cycles of the platform have shown, by positive evidence, that this goal has been achieved, but in the previous papers no analysis was conducted regarding the social behavior of the participants in relation to consuming or being exposed to different viewpoints of their own. Several studies suggest that people crave more for reinforcement of opinion than they reject exposure from different points of view, and that from the standpoint of strengthening democratic discourse, hearing the other side is crucial. A key goal of this paper is to evaluate the extent to which the participants of the latest experiment in the aforementioned platform followed this behavior. Besides that, we aim to investigate whether the design of the platform favored the goal of encouraging the consumption of diverse sources and opinions, with an eye towards the next design cycles.

The advance of technology has influenced the relationship between government and citizen. In this scenario, the convergence between digital democracy, crowd computing, information visualization, mining of social media and collaborative information systems can increase citizen participation in solution for social problems. The aim of this paper is to propose an application that provides a collaborative environment and allows citizens to help with the solutions of social problems. Expect that the application encourage the participation increase of citizens in decision-making of public sector. In proposal is described some features and the basic application architecture. Furthermore, in order to facilitate understanding was generated a prototype and a conceptual model of the application.

Knowing the future of work is something that we all wish to do in order to be prepared for it. Unfortunately, humans cannot predict precisely the future of anything yet. Nevertheless, in this paper we try to get as close as we can to it by looking at some trends of the future of work. This challenge is undertaken by reviewing the scientific literature on the subject. We elaborate on some insights for CSCW based on the trends of the future of work and society.

This paper presents an observatory for registering applications that use participatory sensing to collect data. Cataloging these applications will aid the scientific community to exchange more information, facilitating the comparison between different initiatives. Through an initial research, the applications are categorized in areas usually considered in the literature. We propose a survey to validate the platform and also discuss the taxonomies created as a result of this survey. The main contributions of this paper include the classification of crowdsensing applications in different ontological categories, as well as the proposal of a technology platform that enables the distributed and collaborative cataloging of crowdsensing initiatives.

It is understood that large quantities and diversity among users of a crowdsourcing system is something to be explored. So that the characterization of these users can aid in the decision-making on aspects related to crowdsourcing systems design, such as user interface design, recruitment strategies, motivating participants, among other specific challenges of crowdsourcing systems. Considering the characterization of the users' communities within the context of crowdsourcing systems, it was noted the need for a framework that helps in the identification of user-model classes more adherent to certain types of crowdsourcing systems. Thus, in this paper we present the proposal of a high-level framework that associates a set of relevant user models classes in relation to types of crowdsourcing systems. This paper also discusses the results of a preliminary study, presenting the analysis of the framework, which was capable of helping a crowdsourcing researchers' group choosing the user-model class that best fits to their business models.

Analyzing social iterations in a scientific environment will assist researchers in expanding their collaborative networks. Scientific social networks represent the researchers' social iterations in an academic environment. The analysis of these networks requires a detailed study of their structure and it is important the use of visual resources in order to a better understanding of how the social iterations occur. In this paper we will use centrality metrics and a clustering algorithm to analyze the structure of a Brazilian scientific social network. A scientific social network visualization tool will be used to allow a visual analysis of the collaboration between researchers from different educational institutions.

Emergency situations are unpredictable and happen in many ways around the world. Natural disasters or similar events of major proportions require governmental intervention. In order to do so, the public administration must keep resources ready to attend these events. In this work, we propose a framework to analyze economic factor that may influence the government supply chain. We evaluate the proposed framework, analyzing medical supplies in the Brazilian Navy, focusing in the surgical gloves — a representative supply. In our analysis we found out that Price Registration bids tend to be the most effective policy in economic crisis scenarios.

Waiting for service is a problem faced by people from different countries and cultures. The problem of waiting in a queue can bring losses of quality of life and even economic problems. In this paper, we propose a mechanism for automatic detection of wait events via smartphones. This detection is done cooperatively by observing data collected from the user's smartphone's wifi and accelerometer sensors, and such information is compared to contributions made by other users. Experiments have proven the efficacy of this mechanism to be about 99% accurate.

The Future-oriented Technology Analysis (FTA) literature recommends to use diversified FTA methods to improve the quality of the results. As the FTA methods are performed, the output of one method is used as an input of the next one. We propose that FTA methods rely on collaboration in order to produce the final result of the FTA. In this work, we analyze the collaboration applied to the FTA, from the collaboration among the researches when performing a method to the collaboration between the FTA methods. Finally, we also discuss the awareness of the collaborative work and how the FTA methods may support them.

The waiting time for customer services is a problem that affects most cultures and has been studied by the academic community for several decades from the standpoint of psychology, sociology, marketing and computer science. In this paper we present a review of the literature on the subject, and also propose a classification of approaches that deal with this problem. We also report our participatory effort in articulating requirements and functionalities of a design solution to address this problem. A series of interviews were conducted with stakeholders and other people involved in the problem of waiting time delays in customer services, allowing requirements to be posed and validated through a survey. Finally, we present the latest details of an application being developed to address this problem and the final conclusions.

Link Prediction is a classic social networks analysis problem. Knowing in advance future actions in social network can help, for example, agents decision. Link Prediction techniques are based on metrics that have different approaches. In this paper, we model a multi-relational scientific social network to assess the impact of content extraction on topological metrics. Thus, a metric composed of topological and semantic approach is proposed to solve link prediction problem. The results were compared with those presented by Katz metric.

Information Systems Development faces many recurrent issues that must be addressed in every project. A lot of common requirements and features repeatedly appear on different projects challenging the development team. Exchanging solutions and the expertise gained over the evaluation of such solutions among projects can prevent the development teams from reinventing the wheel. The MDArte framework has been used to develop information systems through the Model Driven Architecture approach, automating the generation from models reaching around 80% of the application code. Most important is that the MDArte framework turned out to be a common platform between the adherent projects used to share new solutions and features. This paper focus on recurrent issues present at the modeling phase. We applied the concept of Model Patterns in order to provide diagram templates. A set of diagram templates were designed, implemented and evaluated by a volunteer project. The feedback was extremely positive and the proposed approach proves to be very promising. This level of collaboration between different projects on one hand accelerates the development and on the other hand prevents from neglecting important issues on information systems development.

We report on the second design cycle of Acropolis, a social computing platform that allows citizens to build and share their own narratives about long-running news stories. A key goal of this research project is to explore the following design opportunity: how can we re-design news stories in order to engage citizens in their reading and curation? In this paper, we describe an asymmetric collaboration approach to engage the crowd of citizens in social news curation. We conclude with the description of a quantitative evaluation conducted during the second design cycle that yielded very encouraging results.

A Species List of Flora is a working list of scientific descriptions of all known plants occurring within a given region. It represents an inventory in process, i.e., updates and new plant species are added every working day. The Flora checklist has an important value for the scientific community, government, industry and society, since it gathers accurate data on flora diversity. Knowing the Brazilian flora has been a commitment assumed by Brazil towards the international community. In 2009, the Rio de Janeiro Botanical Garden, in a joint action with several research institutions, started the development of a Virtual Research Environment based on crowdsourcing. The aim of the project was to support the collaborative and distributed work of an undefined number of pre-qualified trained taxonomists, grouped in their specialties. This article describes the technological aspects related to the ongoing work on the List of Species of the Brazilian Flora, which is a recent example of success in building a knowledge database collaboratively. It describes the mechanisms used for determining individual characteristics of potential participants (target audience), the means of collaboration and communication, as well as the technological platform developed to support a web-based crowdsourcing design for Virtual Research Environment. Some information on both the performance of the team of about 600 researchers and the quality of information produced are presented, also including some of the lessons learned and recommendations for future action.

Sharing knowledge across projects is a necessary challenge to ensure the competitive advantage of organizations. With temporary structures, multiple roles, multiple activities, and limited time, the project-based organization needs to retain the knowledge gained in a project and share it with others. “Lessons learned” processes are implemented in order to systematize the transfer of this knowledge, with the main challenge being the mobilization of people to record their experiences in a database. The stored knowledge, however, needs to be validated before being shared and appropriately classified in one of the three main categories: Best Practices, Lessons Learned, and Points for Attention. This study shows the benefits of a checklist / action plan for ensuring the effectiveness of the validation stage, since failures during this stage may jeopardize the initial effort to mobilize project teams to record their experiences and learning.

This work in progress proposes the use of vivid impressions of users to monitor the waiting and service time in the provision of public and private services. The solution consists of an environment in which users can report the time spent waiting for the provision of a particular service. For the strategy to be successful, this account should be done through a simplified interface, preferably mobile, that takes advantage of the user's location knowledge. This approach uses the crowd collaboration to achieve some goal, and has been used in applications such as Waze.

This paper analyzes five social curation tools, chosen for having a relevant number of users and for being subject of other academic studies. Based on existing literature, the concepts of curation, digital curation, and social curation are discussed. Three main research questions are the objective of the research: how ‘social’ are the studied tools, if they are adequate to crowd work, and how good they are as search engines. It is concluded that in the current state of affairs, these tools are quite social as social media sites, but little social as social curation sites; that they are not adequate to crowd work. It is observed, however, that these tools use the wisdom of the crowds to filter the vast web content, and that they may be seen as crowd computing tools.

Collaborative visualization is a study field that emerged by combining computer-supported cooperative work (CSCW) and information visualization. The main goal is to analyze how visualization techniques can be used to support collaboration. One of the key aspects for the effective use of visual representations as a facilitator for collaboration is the analysis of how this feature influences collaborative work The aim of this paper is to present a study which considered the use of visualization techniques for supporting the collaboration process from a 3C collaboration model perspective. More specifically, we analyzed the influence of techniques from the user's perspective. A case study was conducted to investigate the relationship of visualization techniques with activities performed by users in a software development scenario. The results of the case study show that visualization techniques influence collaborative tasks.

People make decisions every day. If the wrong decisions are made in governments and companies, this may cause huge financial losses or other negative consequences. There are several methods to help decision-makers with these hard decisions. Delphi is one of those methodologies. It relies on the wisdom of crowds to extract the best solution from a multidisciplinary group of experts. Long-term decisions may take more than a decade to be proven right or wrong, and as the time passes, the reasons for the decision may be forgotten. There is a lack of methods which enable storage of the reasons for a decision made using the Delphi methodology. We propose an ontology which stores the whole process, thereby allowing the decision-maker to validate the reasons for the decision. If the experts' opinions are still valid, it is likely that the decision is still valid. We also prove that our ontology is minimal and sufficient to satisfy our objective.

Software development projects with geographically disperse teams, especially when use UML models for code generation, may gain performance by using tools with collaborative capabilities. This study reviews the distributed collaborative UML editors available in the literature. The UML Editors were compared using a Workstyle Model. Then, we discuss the fundamental challenges which these kind of UML Editors face to assist distributed developers and stakeholders across disperse locations.

Software systems are developed by people working collaboratively and software reuse allows us to reuse the knowledge and assets of previous software projects. In this paper we briefly present CollabRDL, a collaborative language that extends RDL (Reuse Description Language). It is textual and executable and allows us to describe activities of the reuse process explicitly following an order. We also explore the literature on the 3C Model and on Role Analysis to investigate whether CollabRDL conforms to the 3C model, in order to have an indication of where we need to improve CollabRDL to achieve our goals.

Information Systems Development faces a lot of recurrent issues that must be addressed in every project. A lot of common requirements and features repeatedly appear on different projects challenging the development team. Exchanging solutions and the expertise gained over the evaluation of such solutions among projects can prevent the development teams from reinventing the wheel. The MDArte framework has been used to develop information systems through the Model Driven Architecture approach, automating the generation from models reaching around 80% of the application code. Most important in the present context is that the MDArte framework turned out to be a common platform between the adherent projects used to share new solutions and features. This paper presents how the MDArte framework evolves through the collaboration of the adherent projects. It also provides examples of features developed and evaluated by one project, shared and applied in other projects. This level of collaboration between different projects on one hand accelerates the development and on the other hand prevents from neglecting important issues on information systems development.

Crowdsourcing is both a new paradigm of collaboration and a new frontier for CSCWD. Since its introduction in 2006, the notion of Crowdsourcing has been the object of a number of studies. Crowdsourcing has a multidisciplinary nature with a huge diversity of applications that encompasses many practices. The concepts that shape crowdsourcing are still under construction and it is difficult to reach a consensus. Based on this scenario, this paper proposes a meta-model which aims to fit generic solutions related to a specific subset of crowdsourcing designed to accomplish a specific task: Data Collection and Participatory Sensing to leverage the engagement of volunteers with Science and Environmental issues.

Smartphones are increasingly present in our daily lives. Since the launch of the Apple store, more than 500,000 applications were built and some 25 billion downloads were made. We are facing an era where the traditional medical paradigm is leaving the traditional physician-centred model and evolving towards a new de-centralized model where patients are given more responsibility for their health. In this new health care context, the premise whereby many people are eager to contribute by sharing health information, anytime and anywhere, should be included in the design of new technologies to support collaborative work in healthcare. This article presents We4Fit, a mobile phone app intended to change the behavior of the users through participation in a collaborative game. The game was developed to show how gamification can be used as a motivational trigger and the value of persuasive technology in changing the eating habits of the users and in promoting a healthy life.

Developing and evolving critical information systems in order to cope with changes in regulations and laws is a constant worry for governments in the e-Government era. Due to the frequent challenges and some previous frustrating experiences, the Brazilian Government has searched for an alternative development method that could better fit its needs. At the same time, Brazilian Academia, represented in this case by the Computer Science Department of COPPE/UFRJ, has been researching how to bridge the gaps in order to harness the promise of Model-Driven Architecture in real life projects. A successful partnership between both started in 2005, which gave birth to a complete MDA development environment that would later be known as MDArte. The MDArte framework has been freely available since 2009 through the SPB portal (Brazilian Public Software Portal � www.softwarepublico.gov.br) and throughout its construction and evolution more than a dozen real projects have been built and maintained. During the development of such real life projects a lot of critical organizational aspects raised. The main contribution of this paper is to reveal and motivate the discussion on such organizational aspects that must be faced when deciding to adopt an MDA approach. In order to contextualize our perceptions, we present the MDArte experience, including its origin, evolution and current state. The major challenging and complex systems that have been developed with MDArte are presented as success cases along with an analysis of the benefits of using a Model Driven Development (MDD) approach.

Crowdsourcing tools have improved e-learning over the last few years. However, these tools vary in many aspects. This work discusses and analyzes the basic e-learning processes based on these tools, defining ways to classify them through these processes. Finally, we define conceptual models tailored to each type of process, using a standard notation for software development. These conceptual models may be used to build new e-learning crowdsourcing tools.

Delphi is a traditional method for supporting the decision-making process. It relies on a panel of experts who collaboratively reach a consensus about a given topic. This method may be empowered with new communication technologies which can gather a larger and more geographically distant expert group. In this work, we discuss in depth the gathering of a panel of experts for Delphi, which may be constrained by geographic location and competence levels, using methods to find experts in social networks. The Delphi process was also adapted to use social network analysis methods to find experts, thus allowing faster expert selection from small local groups to huge worldwide groups.

The Web is now both an information repository and a cyberspace supported by a participatory culture. In the domain of news and journalism, the Social Web has witnessed the emergence of Social News Websites (SNW), where users contribute for various reasons. Sites like Digg, Reddit and Storify, just to name a few, allow their users to discuss, comment, share, recirculate, tag and rate news from various sources. However, the social computing literature has described these sites so far through narrow definitions, e.g., as a synonym for social news aggregators, as specializations of social media or even as specialized forms of online social networks. In this research, we identify a broader landscape of social applications exploring citizen participation in the news value chain, and propose a broader definition and a typology for social news applications from the perspective of Crowd Computing.

Identifying and measuring a musical talent is not a simple task that could be performed by computers. In addition to the technical challenges, it also involves social, emotional and cultural issues. This problem is aggravated when the task needs to be performed taking as input the huge amount of music content available on the Internet today. In this paper we report work in progress on a social interactive Game with a Purpose using fun as a key motivational factor to assist in recruitment and measurement of musical talent.

Software applications are developed by people who work together and software reuse is an area that aims to improve the software development processes. In this paper we investigate design languages available in the related literature that provide explicit support to collaboration mechanisms. Our main research goal is to provide RDL (Reuse Description Language) with mechanisms to support working in Collaborative Software Engineering under the umbrella of CSCW. By looking for languages that support collaboration features, we aim to understand how to design and add CSCW facilities to RDL.

This work presents and discusses an approach in the MUTIRÕ project, showing the possibilities created in an experiment using fuzzy scenarios instead of traditional crispy ones. The Olympic and Paralympics Games that will be hosted in Rio de Janeiro in mid-2016 served as a confirmation of these concepts. A strategic planning process in Semantic Crowdware Large Group Decision demands several premises that should be taken into account and is discussed in this work. The preparation plans for the Rio 2016 event should be carefully prepared and depend mostly on the ideas generated by specialists. However, this is not feasible, as most of the problems addressed in this kind of event are unique and should be a mix of old experiences and new ideas. The premise that many people are eager to contribute by sending new ideas and collaborating is not true and new approaches should be tried. Although many of the steps in the process will be discussed, this paper will concentrate on the definition of the Prospective Scenarios considered as the most appropriate for the use of the Large Group concepts. To assist in this task, our paper intends to show a strategic planning method adapted to use a large number of collaborators interested in the success of Rio 2016, taking into account their socioeconomic and geographical aspects.

The medical paradigm is leaving the traditional doctor-patient relationship, i.e., the physician-centred model and evolving towards a new de-centralized model where patients are given more responsibility for their health. This article seeks to understand what is changing in this relationship and what role the Web and the interconnected crowds of people play in this state of affairs. Our work discusses the evolution of the Web, how it is changing Medicine and the way patients are reaching to health information, and presents a new approach for Medicine 3.0 and its prospective scenarios. This transition has been changing the interaction between doctors and patients. Patients have become more social and responsible for their own health, adopting new communication channels and interacting with other patients and stakeholders distributed all over the world. In this new health care context, the premise whereby many people are eager to contribute by sharing health information, anytime and anywhere, should be included in the design of new technologies to support collaborative work in healthcare. To assist in this, our paper discusses how the new crowdware systems is supporting a multitude of Web-based collaborators interested in Medical Care, showing some examples of its application, taking into account all the stakeholders: doctors, patients, laboratories, hospitals, and apomediators.

In this paper we report work in progress on the design of a task scheduler that aims to assist people in choosing, scheduling and performing their everyday tasks. The main idea behind the proposed application is a role-playing-game in which the player must strive to evolve features he most desires for his character - to obtain the desired result. A key goal of our approach is guiding users to perform activities that provide more benefits to their health. One way to accomplish this goal is through collaboration - by stimulating people to share their practices, difficulties and action plans.

Citizen Science projects are characterized by mass collaboration of ordinary citizens with scientific research. The advent of new crowdware technologies and the ease of access made possible by the Internet are reshaping the way people and scientific organizations work together. However, the particular nature of this form of collaboration requires a tailored approach that increases the chances of all involved parties meet their expectations and achieve their goals. We propose a conceptual framework to help Citizen Science enterprises in conceiving their crowdsourcing strategy and designing their collaboration systems. It departs from basic principles of traditional marketing models and incorporates the specific requirements of this increasingly popular but also complex form of web-based collaborative work.

Recent crowd sourcing tools are changing the Education. However, each tool has a specific approach, business model and e-Learning goals. Due the increasing contribution of crowd sourcing in the e-Learning process, it has become important to study it and map the challenges intrinsic to this activity. This work discusses and classifies several crowd sourcing e-Learning tools that can be found in the Internet. We defined and used eleven dimensions to classify the 22 tools found, ranging from online Universities to marketplaces for online courses. The work contributions are: provide the first map the crowd sourcing tools and a framework for classify the future tools.

The aim of this paper is to present a framework for crowd sourced collection, cleaning and measurement of digital content that follows the dynamics of a game with a purpose (GWAP) for capturing the collective knowledge and also for computing tasks through players' interactions. Using this framework we developed a game called Cassino Musical as a solution to the recruitment and measurement of musical talent from unknown artists who post videos of their musical performances on the Internet.

Game theory has been largely criticized for not being practical enough. Although game theory is compulsory in any economics, business and management course it is not widely accepted as a theory that has a practical application. Although the answer to this problem does not lie on the surface, a connection between game theory and negotiation support systems has revealed the use of the principles of game theory in simulating business negotiations for IT and non-IT people. The behavioural aspects of people's actions during negotiations characterise their different strategies in various situations.

This work presents a Strategic Planning approach in the MUTIRÕ project, showing the new concepts of Crowdware in a Large Scale decision support system. The Olympic and Paralympics Games that will be hosted in the city of Rio de Janeiro in the middle of 2016 will serve as a confirmation of these concepts. The preparation plans for Rio 2016 event will demand several artifacts to allow its correct effectiveness. This series of developments will be decided by the Event Commission and many people are eager to contribute by sending novice ideas and collaborating. To aid this task, our paper intends to show a crowd-based decision support systems methods through different solutions in order to help large groups in their discussions, their alternatives generation and all group choosing process. The continental characteristic of our country creates several opportunities for these techniques establishing additional difficulties for CSCWD. While groupware focus on the technologies related to work group, crowdware synthesizes the search for artifacts that implements the principles of James Surowiecki Wisdom of the Crowds in a very large number of collaborators. The main task of this project is to help groups interested in the Rio 2016 success taking into account their socioeconomic and geographical aspect.

Despite advances in the requirements elicitation techniques, researchers show that even today software engineers cannot understand exactly what a product should offer to meet user needs and expectations. This paper aims to propose a new strategy to assist the process of requirements categorization, so that it becomes possible to extract from the user what he really expects of a product. The proposed framework is based on the concepts of requirements categorization established by Noriaki Kano, and on previous studies focused on collective intelligence, to propose different approaches to extract from the crowd the necessary knowledge to classify requirements and decide what should be prioritized and what should not, according to user expectations.

There is no discussion on how collaborative tools can enhance the way we perform our everyday tasks. By interacting with each other we can find out the answers to our questions and improve the quality of our decisions. Moreover, the tools available make it very easy to spread our issues and gather results and feedback online within a very short response time. When it comes to traditional information systems the wisdom of the crowds' principle is neglected. The vast majority of information systems deployed provides no collaborative tool aimed at supporting users to perform their tasks. The community of users of any information system is a powerful resource of tacit knowledge that must be exploited. The MDArte framework has been used to develop information systems through the Model Driven Architecture approach, automating the generation from models reaching around 80% of the application code. This paper presents the Collaborative MDArte initiative which goes further in the automatic generation embedding collaborative tools into generated information systems with no additional efforts.

According to some researchers, the wave of crowds we are witnessing in recent years is another example of the challenges for the CSCW community, a line of research that fights against the dilemma of fragmentation. The reflexes of this phenomena in projects of different branches have caused a change of paradigm in how products and services are idealized and how the projects are conducted in a collaborative way. Successful examples have attracted the attention of entrepreneurs in various areas and increased the business vocabulary with terms like crowd wisdom, crowdsourcing, crowdfunding and open innovation. It is a different reality from the one we are used to in the context of groupware systems, and it brings new challenges that leave some relevant open research questions. This paper proposes a characterization of crowd computing systems, contextualizing the design activity within this domain, presents a research agenda in the context of CSCW and discusses possible implications of the mass phenomena on the line of action of the community of Computer Supported Cooperative Work in Design.

Over the past 5 decades society has been increasingly requiring immediate results, and this is reflected in business. Due to this, the attention given to strategy, strategy management and strategy planning has increased. The use of the Balanced Scorecard (BSC) is a way of achieving this strategic capability. Moreover, a proper BSC has effective metrics to track its goals. This work proposes a system that recommends metrics in accordance with the goals of a BSC. The recommendation is made using data mining techniques, in particular association rules.

Citizen science projects generally use the Web platform to promote scientific research and recruit volunteers to assist them. Through a crowdsourcing platform, a large amount of data is submitted and some factors may lead the scientific community to doubt the seriousness of some projects. This may be due to the unreliability of data collected on a voluntary basis and the absence of criteria for quality control of the submitted data. Our main research goal is to propose a collaborative framework for improving data quality. By associating data quality dimensions to scientists through a voting network, we aim to create a continuous process for data quality validation.

Recent behavioral and cultural changes driven by the paradigm of mass collaboration highlighted the phenomenon of crowdsourcing as an innovative and promising production model, with positive effects in several business areas. In the field of music, the so called wave of crowds has fostered creative processes where people from anywhere in the world with Internet access can collaborate in different ways in musical productions, even not being practitioners. The present work is a study of crowd computing applications in the context of music, with an eye towards the crowdsourcing phenomena. We investigate forms of collaboration involving crowds and the available platforms. We also discuss the challenges coupled to this domain and propose a research agenda.

The city of Rio de Janeiro will host the 2016 Olympic and Paralympics Games. Several improvements are being planned for the city in order to prepare it for the so called Rio 2016 event. This sequence of developments will be decided by a Local Committee and many people enthusiastic to participate should contribute by sending ideas and actually collaborate in the planning process. To assist this huge task force, our paper intends to use decision support systems techniques and cognitive means through different approaches in order to aid large groups in their discussions, their alternatives generation and all group choosing process. This work presents a semantic search method in the LaSca system for the MUTIRÕ project, which explores the coordination in a Large Scale decision support system. The importance of a locale semantic search comparing to a classical search method is that most contributors are not formal and well behaved in language structure, using lots of slang and alternative means of communication. As Brazil is a continental country it created several local ways of communications that vary from place to place creating additional difficulties for a search tool. A smart thesaurus must be constructed through semi-automatic means and a search engine should be crated to allow feasible searches by the users. The main task of this project is to help groups interested in the Rio 2016 success taking into account socioeconomic and geographical aspects.

Social networks are dynamic social structures consisting of individuals or organizations, usually represented by nodes tied by one or more types of relationships. Analyzing these structures allows us to detect several inter and intra connections between people, inside and outside their organizations. In this context, we construct a multi-relational scientific social network where researchers may have four different types of relationships with each other. Using clustering techniques with max flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific scenario of the Computing Sciences.

Social networks are sets of links that organize people, groups, and institutions in an equal and democratic way, and around a common purpose [4]. During the formation of such networks, problems can arise, such as elements that concentrate many relationships, very isolated individuals or peripheral members of a network, people who are the only link between two distinct groups, agglomerations of people in isolated points. This can cause a series of communications problems, which ultimately will cause losses to the most important element that flows through social networks: knowledge. Thus it is necessary a series of analysis on social networks so we can monitor possible collaborations and assist in the formation of work teams, this can be done through the concept of balancing social networks developed by us [20], whose main focus is to maintain the social network as cohesive as possible in order to maximize the flow of knowledge. A practical application of these analysis occurred in the project BRINCA (Analysis and Balancing of Scientific Social Networks in Cancer Control). BRINCA's goals are to analyze how members of the Cancer INCT (National Institute of Science and Technology) collaborate and how the scientific knowledge flows amongst the different researchers and institutions. With this project we could perform contextualized analysis (i.e. by relationship type, subject, institution, geographic location, time) and use the metrics of social network analysis to understand and verify how collaboration occurs in a multi-disciplinary, multi-team project. Moreover, we used the criteria of social network analysis to perform the balancing. In addition, some of the analysis made on the scenery of cancer are shown.

Modern society offers us many ways to socially interact with friends, colleagues, co-workers, etc. In this scenario, our social networks are in constantly changing and interests, objectives, and other things involved in each social interaction can be affected or even remain out of reach. For each change, the social network has to be re-analyzed to show us if the interests and objectives can still be attained. Each analysis carries its own variables, relevant information, contexts and difficulties, and this new analysis can be expensive for a Human entity. We argue that autonomic computing could help with the analysis and in decision-making, transforming the network into an autonomic social network: intelligent networks capable of analyzing themselves and suggesting actions to individuals or computational systems towards attaining one or more set goals.

Recommendation systems are largely used nowadays to support collaborative tasks. However it is important to consider the knowledge about each user of the system. In this paper we describe the use of knowledge to improve the recommendation system of the Business Process Cooperative Editor (BPCE), a collaborative business process modeling tool. We introduce the concept of Knowledge Vectors, and how they are applied to BPCE, balancing recommendations with the knowledge the recommender has on the subject of the evaluated model.

It has been known that Information Technology (IT) area has increasingly demanded more professionals over the years. In Brazil this reality is even more evident - this emerging and large country, the expanded search for IT professionals still faces difficulty in finding skilled labor. Moreover, this difficulty is accentuated during the definition of teams, due to the diversity of expertise of each professional. In this direction, this article focuses on how to discover and manage cognitive and behavioral aspects of IT professionals. Based on psychological questionnaires and negotiation games, this work aims at analyzing types of behavior (logically reasoning people, creative people, communicative people and organized people), aspects of collaborative and competitive issues elucidates how the predominance of a specific stereotype can influence negotiations among IT people. The results were obtained in a Brazilian context, involving technical and management staff, with IT people and non-IT people.

One of the most essential problems during negotiations is to know what people aim to claim. Although it sounds strange, most professionals go into the negotiation table without enough preparation. Regarding preparation it is important to understand that this is the stage when professionals have to anticipate the counterpart's interests, alternatives, concessions and possible changes in strategy. Experienced negotiators usually keep in their mind the whole negotiation and, most of the time, they still have personal notes about the deal. Indeed, people have memory limits and this may disrupt even the cleverest ones. Therefore, Negotiation Support Systems can help to store this information and also manipulate it in the future. In this direction, this work presents an environment focused on a negotiation preparation step, mainly considering knowledge management and mobile technologies. The article shows how these concepts may carry out the preparation stage, advantages to use it and available reports. Besides, some experiments and results will be also addressed in this work.

Decision-making involves choosing between one or more alternatives, to achieve one or more goals. To support this process, there are decision support systems that employ different approaches, supporting groups or not. Generally, however, these systems do not have great flexibility; their users have to follow preestablished decision methods. This paper, then, briefly addresses LaSca, a decision support system that employs different approaches in supporting large groups, for the benefits its use presents in decision-making processes, in their problem and solution discussing, alternatives generation and group choosing process, this way letting its users to also decide how to decide. Then, it presents the system's last improvements. Finally, this work discusses how the LaSca system could help design a great sports event such as the upcoming 2016 Olympic games at Rio de Janeiro with the aid of large groups, using the organization of the Public Security schema of the Panamerican Championship of Artistic Gymnastics, that happened in November 2009, in Aracaju, Brazil, as an example.

This paper describes a collaborative tool, ARARA (Artifacts and Requirements Awareness Reinforcement Agents), that provides awareness in Software Development Process (SDP). Ontologies support this application for they are used by project team members when preparing the artifacts, propagating the concepts through them, and used by agents as knowledge base to retrieve information, tag the artifacts, detect changes, and search for linked artifacts that may be affected by a change on a previous artifact. This collaborative tool can improve team members awareness automatically no matter where they are geographically working, once agents are responsible for tracking and notifying requirements, or any other changes, to team members, including consequent candidates for modifications.

The historic decision to take the biggest sporting competition in the world to South America was announced by the International Olympic Committee in Copenhagen, Denmark and started several projects in the city of Rio de Janeiro, Brazil. The redevelopment of Praça Mauá Pier, one of a number of improvements planned for the city's port is the first of a series of enhancements planned for the city in order to prepare it for the so called Rio 2016 event. This sequence of developments will be decided by a Local Committee and should be aided by many people eager to participate and actually collaborate in construction process. To support this process, this paper intends to use decision support systems that employ different approaches in supporting large groups in their problem and solution discussing, alternatives generation and group choosing process. This work presents the use of the LaSca system in the MUTIRÕ project, which explores the coordination in a Large Scale decision support system that sustains the argumentations which were produced by the discussion involving the members of the design team and aids them to achieve a final conclusion. The main task of this project is to help groups interested in the Rio 2016 success taking into account socioeconomics aspects.

Meetings take a large amount of time, and frequently, meeting facilitators are called in to help steer the meeting in the right direction. Unfortunately, facilitation is still something of an art. To assist facilitators, the thinkLet technique has been proposed. Through the use of thinkLets, facilitators may plan the meeting beforehand, deciding which activities to perform at each point. However, designing a meeting is not an easy task, especially for novice facilitators. In this paper we present AgendBuilder, a system to assist the design of meetings, electronic or otherwise, using thinkLets and compatibility rules. The system helps facilitators select and link thinkLets together in and orderly fashion, designing the meeting in the process.

Autonomic automation is viewed as a new approach to business process automation. In this work, we propose a method to identify the best-suited business processes as candidates for an autonomic automation. Generally, this decision is made by process automation experts or inspired by management preferences. Moreover, the best candidate to an autonomic automation is possibly different from a candidate to a traditional automation. To support our method we developed a tool with ability to inspect the process model and obtain specific metrics. Finally, we present the results of the proposed selection method, compared with expert choices and to existent methods for traditional automation selection.

This work presents an implemented framework called Real Time Multi Logic Reasoner (RT-MLR) that aims to help a development of context-aware systems. RT-MLR has been designed combining the rule based method with the regular object-oriented architecture. RT-MLR has an inference engine that allows to express and merge knowledge through rules in three logic types: First-Order Logic, Fuzzy Logic and Temporal Logic. This engine works based on an event based approach, which supports a continuous monitoring of system domain. RTMLR has been exemplified base on its capability to perform context reasoning in a military application according to data fusion approach.

This work presents a spatial distribution analysis of Brazilian Atlantic Forest Bromeliad species catalogued by the Rio de Janeiro Botanical Gardens Research Institute. Our analysis aims at identifying probable endangered species and conservation areas (environmental reservations) for specific Bromeliad species. For that, we propose a solution using Data Mining techniques and the data visualization through the TerraView tool. Thus, it was possible to define where are typical species, allowing more effective field tours.

Peer-to-peer (P2P) offers good solutions for many applications such as large data sharing and collaboration. Thus, it appears as a powerful paradigm to develop scalable distributed applications, as reflected by the increasing number of emerging projects based on this technology. However, building tr

Business process management systems are largely used nowadays. Process Modeling, whether for depicting new processes or for optimizing existing ones, requires knowledge and proper tools. However, most process models are created from scratch, not having reuse promoted, i.e., not considering existing

In order to evaluate information retrieval algorithms it is imperative to use a dataset as a test database. However, access to such datasets is often difficult and expensive, since building them is a time-consuming and costly task. This paper presents a collaborative approach to dataset creation that uses a data quality evaluation technique based on fuzzy theory, to assist users in selecting suitable Web documents for their datasets. These documents are automatically captured by a crawler and assessed on information derived from their metadata.

Now-a-days, with the wide availability of Internet access, a great diffusion of the decision-making in large groups concepts and practices is happening, with many softwares to support it and many people eager to participate and actually collaborating arising. However, these ideas are not exactly new. In the middle of the 5th-4th century BC, some Greek city-states, like Athens, already had a political system in which the citizens of these states made the governmental decisions. And, besides being the birthplace of Democracy, Greece, with its high-developed philosophy ideas, also laid the foundations to Argumentation Theory, which will help in analyzing and validating the today's concepts of decision-making in large groups used in the LaSca (from Large Scale) Decision Support System. This paper, after presenting this discussion, and also illustrating some concepts of Collaboration Engineering with the developed system, will give an example of how LaSca could be extremely useful in an actual electoral system.

Knowledge has always been an advantage in any social activity that involves dispute. To possess knowledge on the domain of a negotiation can give one the edge to attain one's desired goals. In order to obtain such knowledge, an alternative can be the collaboration between allied negotiators where past experiences, acquired in negotiation, can be important and a powerful tool to future efforts. To facilitate this collaboration, this work presents an application of the 3C model for negotiation, the NK-Sys, a tool whose goal is to support the negotiator in decision-making; this tool takes Knowledge Management into account to allow cooperation between negotiators.

Man as a social being, as a being in social relations, is in constant motion. Such mobility affects the social networks that Man builds throughout one's existence. Networks that can consist of dozens, hundreds or even thousands of other people, with various degrees of mobility. During the formation of such networks, problems can arise, such as elements that concentrate many relationships, very isolated individuals or peripheral members of a network, people who are the only link between two distinct groups, agglomerations of people in isolated points. This can cause a series of losses to the most important element that flows through social networks: knowledge. In scientific social networks, this assertion takes even more importance, mainly on account of the mobility of researchers and the excess of knowledge circulating in it, making it more vulnerable to the movements of Man. It is with the intent of solving this problem that our work seeks to achieve success, as it analyzes the scientific social networks based on the GCC tool detects the problems related to them, and suggests recommendations of relationships to users considered harmful to the flow of knowledge in the network. We call this process of social network balancing. For the evaluation of this work we conducted a comparison with several similar proposals, and developed a working prototype, which in turn was used to make our case studies.

Sources of alternative, clean and smart energies are a demand on our modern world. And as a design project, collaboration and knowledge management are elements that improve the work on multidisciplinary teams. This work describes a collaborative project to construct a Brazilian solid oxide fuel cell, its problems and the solution created to enable a collaborative work on a national context.

Conferences are an important environment for academic knowledge exchange, and are valued by researchers as a good way to increase ones social network and meet potential collaborators. The question we investigate in this work is whether conferences actually influence collaboration between researchers, providing a starting point for joint work. To conduct this investigation, we used the DBLP database containing 640.977 distinct authors, 1.057.207 papers published in 21.354 journals and conferences spanning over more than 70 years. Using the concept of coauthorship as evidence of collaboration, we found that at best only 123.886 collaborations (from a total of 2.685.224, or 4,61%) could have emerged from the authors having met at a conference. This leads us to the conclusion that conference environments do not significantly promote collaboration among participants.

Corporate and personal computers are flooded by a huge amount of data. Among them, there are irrelevant, similar, false, wrong and obsolete data. Besides, the treatment of this data is relatively complex. Systems need to check, transform, adapt, and summarize data in order to use it. These activities spend time and money of many companies that should be concerned for business rules. In RSS feeds, we have these problems: the users receive a big number of news, sometimes irrelevant or duplicated. The tools to cope with these data do not provide efficient mechanisms to manager information overload. To reach this goal, it is necessary to introduce a new complexity to feed readers, what is sometimes undesirable. Therefore, we propose the autonomic collaborative RSS that transfers the system complexity to data, facilitating the system development. At the same time, it allows to incorporate data treatment rules, as well, data filtering through data killing patterns.

A social network is a social structure consisting of individuals or organizations usually represented by nodes tied by one or more types of relationships. The resulting structures are complex and analyzing them enables us to detect several inter and intra connection problems. This work focuses on using data mining techniques to identify intra and inter organization groups of people with similar profiles that could have relationships among them. The clusters identified allow us to identify the collaboration in the Brazilian scientific scenario of Computing Science, assessing how researchers in the best universities and research centres collaborate and relate to each other. This kind of approach can help in the identification and improvement of collaboration on innovative and multidisciplinary teams, especially on manufacturing and design scenarios.

Ontology alignment has impact in how ontologies will be treated by actors in semantic web and stills an unsolved issue. To contribute in this issue, we present an algorithm developed in the GNoSIS system. This solution uses both syntactic and semantic techniques in a structural approach. The algorithm uses distinct resemblance functions and calculates the degree of similarity between the concepts in a recursive manner, calculating the resemblance function result between concepts based on the total similarity degree between concepts with a close kinship. A validation of this approach is presented in this article.

Scientific environments are known for being highly dynamic, subject to rapid evolution and demanding constant renewal and update. Additionally, science is a highly social arena. However, interpersonal collaboration and knowledge flow in scientific environments are usually more restricted. Collaboration is intense among small groups of people working on specific problems within a domain, but low between groups. As user profiling has been extensively used as a basis for recommendation, personalization and matchmaking systems, a better profile identification can improve interaction levels among researchers belonging to the same domain but working in different laboratories. Profiles may be constructed in two ways: either through explicit declaration by the user or through the observation of users’ actions. Many systems employ one approach to the exclusion of the other. We contend that a combined approach will yield better results, especially on scientific scenario, providing a mix of declared and inferred information. In this article, we present inference-based profiles in scientific environments (i-ProSE), an integrated system that dynamically creates and maintains scientific user profiles based both on declared information and on observed behaviour. The i-ProSE can be used to locate experts, deliver content, build communities, find collaborators for long-term projects or detect instantaneous opportunities for informal collaboration, which is presented with a short study case.

Decision-making involves choosing between one ore more alternatives, to achieve one or more goals. To support this process, there are decision support systems that employ different approaches, supporting groups or not. Generally, however, these systems do not have great flexibility; their users have to follow pre- established decision methods. This paper, after exposing some decision-making processes, describes a system, LaSca (from Large Scale), to support decisions in large-scale groups. This system, besides allowing effective achievement of the benefits of deciding in large groups through the proper structuring of the group, also allows its users to define themselves how this structuring will happen, based or not in the existing theories on the subject. So, in addition to facilitate the decision-making process, LaSca also allows its users to decide how to decide.

This article focuses on the generation of knowledge chains as a way of retaining the knowledge generated during the execution of a water resources project. To create new chains we are making use of the knowledge stored in project tasks, and the ontology technology. The ontology concepts associated with a task are converted into knowledge units, which are filled with all the information related to it. The ontology structure will be used to create the sequence of the knowledge chain that includes the units created. The new chain will be presented and must be validated by the author to be added to the environment knowledge chains base.

In many group work situations, meetings take up a reasonable amount of time. Several techniques have been introduced to streamline meetings and reach conclusions faster, many of which place an individual in the role of meeting facilitator. Facilitation involves intervening to produce desired results. Thus, a facilitator should be able to identify certain group dynamics and act accordingly. In this paper, we present and electronic idea generation system based on thinkLets dynamics and designed to measure group dynamics. This information is provided to the facilitator so he or she can decide whether or not to intervene.

Currently, Fourier and cosine discrete transformations are used to classify documents. This article proposes a new strategy that uses wavelets in the representation and reduction of data text. Wavelets have been extensively used for dimensionality reduction in the field of signal processing. In this work, we show that a text document, after being subjected to a simple process of reorganization of its terms, can be treated like a signal and analyzed by signal processing tools. We demonstrate that this new representation is able to describe the most relevant features of documents in a synthetic representation and this new perspective improves the performance of the classification algorithm.

In scientific and engineering scenarios we can notice the predominance of explicit knowledge being manipulated and distributed, which makes recommender systems very useful in this environment. But along with a knowledge management approach this kind of system can support the organization in better identifying competences, help engage users in a continuous and dynamic knowledge exchange, and customize knowledge dissemination as much as possible. In this work we detail a collaborative recommender system which is used in a Knowledge Management Environment for Scientific and Engineering contexts; we show how this approach can be aimed at a KM process and how this approach can deal with other kinds of knowledge used in research centers and universities.

Decision-making involves choosing between one ore more alternatives, to achieve one ore more goals. This process is composed of a series of steps, ranging from the identification of the problem itself, going trough the definition of criteria that characterize possible solutions to the problem, to the decision-making itself, in which a possible solution to the exposed problem is finally adopted. These steps can be performed by a single person or by a group of people. In group decisions, the solution choice at the end of the process must be effectively made by the group. To support this process, there are decision support systems that employ different approaches, supporting groups or not. This paper defines the decision-making process, presenting benefits of group decision and describes a system to support decisions in large scale groups. Participatory design in the BamPetro environment preservation project seeks to bring a large number of end users into the design process to take into account different perspectives, and help the group cope with multi-objective decisions. These decisions demand synergy among users of the environment preservation project, even though they represent different areas, competencies, political agendas and social interests.

Customer relationship management -CRM -is a broad term that can cover every mode of customer interaction. This concept has been widely used in business language, enabling companies to gain more knowledge about their customers which, in its turn, can be used to improve marketing and sales targeting, improving their results. University and research institutions (URIs), as any other organizations, also need to cater to the needs of their clients, which may be: society in general, their students, researchers and collaborators; other institutions -of a research or commercial nature with which they interact (supplying data, results from research work, consultancy work, and the execution of partnerships) -or governments that make use of their teaching practices and results from their research work. So, this work is a CRM proposal for URIs, studying the differences between the academic/scientific and business world and proposing an environment to manage all kinds of relationships in the academic and scientific scenario.

It may be very difficult to design in advance a global system model which accomplishes all organizational unit idiosyncrasies in complex organizations dispersed across large geographical regions. In this work, we propose the use of our Coppeer framework for agent based peer-to-peer application development to implement an environment in which distributed systems can be collaboratively and incrementally built. The key points of the approach are the use of semi-structured documents as data model, the partitioning of system code in several loosely coupled agents and the use of ontologies to conciliate differences in organizational unit vocabularies.

Knowledge is something that we're always seeking, but it is unthinkable that a person, with one's common tasks of the day, could take the time to follow people around and ask them about a certain type of knowledge one is interested in. However, imagine if we could share it with many people, even those unknown? Imagine if we didn't have to go one by one, asking them about common interests? Our gain would be huge. Not only in terms of time, but also in terms of gathered information. It is to fill this gap that the Mobile Exchange of Knowledge (MEK) concept came to life, so like its implications, which involve, in a mobile way, the interchange of knowledge between people who possess the same interests. Some issues like ad-hoc networks, social networks, location prediction and distributed knowledge management are also related with the MEK concept. However, to verify how effective our idea is, we conducted an experiment in the geographical space of an university in Brazil, where we analyzed the movements of students and also their interest and willingness to share them.

To complement the learning process and promote continuous learning, this paper proposes an environment that uses knowledge management techniques to improve the learning process for building personal knowledge through the exchange of knowledge chains in learning communities. Here we are using the generic model for the knowledge management cycle proposed by Stollenwerk The processes that are part of this model are: 1) knowledge identification; 2) knowledge capture; 3) knowledge selection and validation; 4) knowledge organization and storage; 5) knowledge sharing; 6) knowledge application and 7) creation of knowledge. The use of knowledge management became important in this work because it gave a theoretical foundation to the knowledge chains learning process specification.

In large communities, finding experts or partners can sometimes be hard. Normally, to find new partners one asks for recommendations from known acquaintances. This is a form of social navigation, whereby one searches for others in the network, who might fit required profiles. Time is an important factor in this type of situation, as needs, interests and expertise levels change rapidly. This paper presents a peer-to-peer system to assist social network navigation and search. It builds user profiles through an analysis of ongoing activities that takes time into account, and matches these to find opportunities for collaboration.

In this work, we first present a model of emergent design which allows a community of designers to collectively translate a set of requirement specifications into a completed design. Then, we describe the COPPEER framework, an environment for developing and running collaborative peer-to-peer applications which directly supports the main requirements elicited in our proposal

In project teams, having an unique vocabulary and a common understanding about terms is essential to the success of the project. This issue especially disturbs a design project, which has a multidisciplinary team and must consist of people with specific and different knowledge, from diverse domains, to execute special activities. Negotiation arises from this context as a process for the construction of consensus. The goal of this work is to present a model of negotiation to obtain the consensus of meanings, based on models of business negotiation, and consequently, deal with conflicts and the multiplicity of understandings of a concept, making this negotiation a way for creating value for all agents involved.

The SYMBAD (Similarity Based Agents for Design) system is a project developed to aid architectural design team members to share knowledge used in stand design. Stands play important role in promoting a company image, projects its presence and emphasizes the corporate identity in events and fairs. The processes and problems in stand projects are quite common and can be easily found in other design situations. From conceptual design to the construction of a final product, a stand project passes through many hands, each one adding bits and pieces until it is completed. The physical distance, difficulties in communication and cultural aspects make designers interact less than necessary, generating problems in all phases of the design activities. The SYMBAD project uses an ontology based framework to improve process awareness in a design activity. Based on the knowledge kept from previous projects and similarity aspects, agents can identify possibilities for reuse and provide information to help the design team to built new stands using past materials and ideas. Through a constructed ontology and collaborative features agents can produce global awareness, to facilitate later steps and optimize the process as a whole. In this paper we present some of the junctions and architecture aspects, as well as some of the implementations choices made for this project

In this paper we consider a process which complements the learning process for building personal knowledge through the exchange of knowledge chains. This approach consists in the partial automatization of the process of creating knowledge chains, through the use of the technology from agents, ontologies and data mining. The agents will monitor all media used by the learner, and will classify its content using an ontology. From there, we want to create and recommend a chain to the learner. This point became important when we observed that the learners weren't motivated to create their chains, which, normally, takes a lot of effort

This paper presents SRST, a tool designed to support knowledge management and collaboration activities of the student-supervisor relationship that arise during the development of a graduate thesis. In universities, graduate students account for the greatest part of the research work force, and are usually in close collaboration with their supervisors. Most student-supervisor interaction can be characterized as a form of knowledge management. SRST unites these concepts in a single and original tool and deals with four of the elements related to a thesis: "ideas", "tasks", "discussions", and "documents"

Decentralized projects, where several organizations come together to work on a joint project, are quickly becoming the norm, due to increased networking and distribution. Subcontracting and consulting lead to the creation of more flexible, less hierarchical structures. In these networked structures, partners are often considered as peers and the group has the flexibility to restructure itself according to its needs. In this paper, we present a study of a decentralized software research, design and development group, and discuss its needs. A large amount of time is spent with articulation and maintaining partners up-to-date, which suggests that appropriate awareness support might facilitate the group's activities

Efficient evaluation of spatial queries is an important issue in spatial database. Among spatial operations, spatial join is very useful, intersection being the most common predicate. However, the exact intersection test of two spatial objects is the most time-consuming and I/O-consuming step in processing spatial joins. On the other hand, the use of approximations can reduce the need for examining the exact geometry of spatial objects in order to find the intersecting ones. This work proposes a new raster approximation (Three-Color Raster Signature - 3CRS) for representing different data types (polygons, polylines and points), and to be used as filter in the second step of the Multi-Step Query Processor. We have also executed experimental tests over real datasets, the results having demonstrated the effectiveness of our approach.

The activities executed in the scientific environment are extremely dependent on knowledge from their performers. Thus, knowledge management initiatives are very important in this environment. One of the possibilities for improving the knowledge flow is to explore past experiences, resulting from the modeling and execution of previous scientific activities and handled by a workflow management system. This work presents Thoth, a system which aims at knowledge reuse in the scientific environment, during the planning, design and execution of scientific activities. This approach is integrated with a CBR approach, also described in this paper, with workflow systems and the use of ontologies.

With the increase in adoption of remote work groups and teams working in non-collocated environments, several opportunities for interaction have been lost. Contact with colleagues and discovery of opportunities, previously easy due to physical proximity, is made harder with distance. In this paper, we describe an agent-based framework to assist users in finding opportunities for interaction that may have been overlooked.

Stands have an important role in an event. They present the image of a company, project its presence and emphasize the corporate identity to all guests. Architecture companies, which design stands, involve several individuals. From conceptual design to the construction of a final product, a stand project passes through many hands, each one adding bits and pieces until it is completed. The physical distance, difficulties in communication and cultural aspects make workers interact less than necessary, generating problems in all phases of the design activities. Reuse of materials and ideas is less feasible as design complexity increases. The processes and problems in stand projects are quite common and can be easily found in other design situations. We present an agent framework to improve process awareness in an architecture company. Based on users activities and previous designs, agents identify possibilities for reuse and provide information to the conceptual designer so that their designs take construction difficulties and possibilities for reuse into account. The agents instrument the process to produce global awareness, to facilitate later steps and optimize the process as a whole. In this paper we present the agent architecture, as well as each agent's general functioning and reasoning rules.

With the grown availability of large and specialized online ontologies, the questions about the integration of independently developed ontologies have become even more important. To facilitate the ontology integration process, this paper presents an ontology integration support module, that promotes the creation of new ontologies by reusing others. The hypothesis is that the ontology designer achieves a reduction in the time dedicated to create a new ontology, as well as obtain ontologies with better quality. The experimental use of the prototype developed showed evidence that the hypothesis can be confirmed.

Currently, one problem faced by the organizations is the inability of the institution to know what it actually knows, in other words, the competences that the organization masters. This problem especially disturbs team formation for a design project, which must be composed of people with specific knowledge to execute different activities. Simple classification or a keyword approach is not sufficient for competence identification. The expertise of an employee or researcher often differs in small but significant details, and an approach is required to allow the accurate description of people's competences and to implement a retrieval strategy that finds a person with a specific competence. We propose a technique to identify competences by mining employee documents, especially publications. We have chose a number of criteria, which is described in this paper, to find people with specific expertise and propose than to projects. Finally, a possible indication for a person's participation in a community is her/his published knowledge and expertise degree.

This article presents the Bill of Experiments tool (BOE), a collaborative environment for the reuse of scientific experiments. The tool is a Web-based system aimed at scientists and suppliers of scientific artifacts. It is capable of pointing out the best alternatives for the accomplishment of scientific experiments based on cost criteria, deadline attainment and quality, in an analogy with the bill of materials process. With the aid of a scientific database on experiments we can describe a collaborative environment for the explicit description, combination, generation (design) and reuse of scientific knowledge. For this work we used concepts from various research areas, like knowledge management, databases, artificial intelligence workflow and CSCW. We present a study case applied to the biological area. We obtained the best alternatives for the experiment's detailed accomplishment and an explanation of why the inference module was chosen, and the advantage of using CLP techniques over conventional optimization techniques. BOE acts as an Internet portal that unites researchers, institutions and companies in a paradigm similar to B2B.

Researchers create and change information faster than in the past. Although a large part of this exchange is in document form, there is also much informal or tacit knowledge exchange in peoples' interactions. The Epistheme environment was designed for scientific knowledge management. This environment is an instance of the SpeCS collaborative framework and aims at knowledge creation, according to Nonaka and Takeuchi's (1995) theory. Researchers can be provided with all necessary knowledge to execute their tasks, to make decisions, collaborate with one another and disseminate an individual's knowledge to transform it into organizational knowledge. This article shows the Epistheme framework with the modules of identification, creation, validation, integration, acquisition and knowledge distribution.

This work presents the development of the AGROMET environment: a platform that supports scientific work in a cooperative way providing the reutilization of data, metadata, models, programs and workflow definitions. To reach this goal this environment is composed of five modules that are responsible for: i) data integration; ii) support to the scientific workflows; iii) support to the collaborative decision making; iv) scientific knowledge management, and v) document and content management. To understand the questions involved in the scientific work a study case is accomplished in the agro-meteorology area in the Brazilian Agricultural Research Enterprise (Embrapa Solos). With this collaborative platform the access, sharing and consequent innovation of the scientific knowledge will be better disseminated in the environment work.

X-Arc is a Web-based architecture for the integration and sharing of spatial data sources in an XML (Extensible Markup Language) format that applies meta data and mediation concepts. It is an important component of SPeCS (Spatial Decision Collaborative Support System), an architecture which intends to support the aspects of multi-criteria spatial analysis within a distributed GIS with tools that can help a group cope with all activities in this kind of project. In the X-Arc framework, the availability and computing capabilities of data sources, as well as the heterogeneity of its data (structure, format, type and meta data) are explored by the data mediation and publishing services. Through SPeCS users can cooperate, collaborate and coordinate their integration activities during their spatial analysis. The work presents a framework that supports the georeferencing of argumentations and allows transparent access to heterogeneous data sources involving the members of the design team in a spatial collaborative context.