The presence of accounts managed by cybersecurity experts, professionals, and organizations makes social media a valuable source for computer security awareness. By regularly capturing and analyzing the posts on emerging cyber threats, individuals and organizations can understand potential dangers in a timely manner and effectively implement mitigation strategies. However, retrieving relevant and informative posts from a social network is challenging due to the high percentage of posts containing uninformative content. This paper proposes a novel approach based on supervised classifiers for selecting relevant social media posts and categorizing them according to different types of vulnerabilities. To accomplish this task, we designed a pipeline combining text classifiers in cascade, training them on manually labelled data. We analyzed various neural network techniques, leveraging language-agnostic sentence-level embeddings and past user activity, validating these techniques in a cross-validation setup. With an achieved accuracy of 87%, our approach offers effective filtering and classification of social media posts, empowering cybersecurity professionals to stay informed and take appropriate measures.

Data Ecosystems (DE) are used across various fields and applications. They facilitate collaboration between organizations, such as companies or research institutions, enabling them to share data and services. A DE can boost research outcomes by managing and extracting value from the increasing volume of generated and shared data in the last decades. However, the adoption of DE solutions for scientific data by R&D departments and scientific communities is still difficult. Scientific data are challenging to manage, and, as a result, a considerable part of this information still needs to be annotated and organized in order to be shared. This work discusses the challenges of employing DE in scientific domains and the corresponding potential mitigations. First, scientific data and their typologies are contextualized, then their unique characteristics are discussed. Typical properties regarding their high heterogeneity and uncertainty make assessing their consistency and accuracy problematic. In addition, this work discusses the specific requirements expressed by the scientific communities when it comes to integrating a DE solution into their workflow. The unique properties of scientific data and domain-specific requirements create a challenging setting for adopting DEs. The challenges are expressed as general research questions, and this work explores the corresponding solutions in terms of data management aspects. Ultimately, the paper presents a real-world scenario with more technical details.

Abstract Information extracted from social media has proven to be very useful in the domain of emergency management. An important task in emergency management is rapid crisis mapping, which aims to produce timely and reliable maps of affected areas. During an emergency, the volume of emergency-related posts is typically large, but only a small fraction is relevant and help rapid mapping effectively. Furthermore, posts are not useful for mapping purposes unless they are correctly geolocated and, on average, less than 2% of posts are natively georeferenced. This paper presents an algorithm, called CIME, that aims to identify and geolocate emergency-related posts that are relevant for mapping purposes. While native geocoordinates are most often missing, many posts contain geographical references in their metadata, such as texts or links that can be used by CIME to filter and geolocate information. In addition, social media creates a social network and each post can be enhanced with indirect information from the post’s network of relationships with other posts (for example, a retweet can be associated with other geographical references which are useful to geolocate the original tweet). To exploit all this information, CIME uses the concept of context, defined as the information characterizing a post both directly (the post’s metadata) and indirectly (the post’s network of relationships). The algorithm was evaluated on a recent major emergency event demonstrating better performance with respect to the state of the art in terms of total number of geolocated posts, geolocation accuracy and relevance for rapid mapping.

Concerns about energy and sustainability are growing everyday involving a wide range of fields. Even Information Systems (ISs) are being influenced by the issue of reducing pollution and energy consumption and new fields are rising dealing with this topic. One of these fields is Green Information Technology (IT), which deals with energy efficiency with a focus on IT. Researchers have faced this problem according to several points of view. The purpose of this paper is to understand the trends and the future development of Green IT by analyzing the state-of-the-art and classifying existing approaches to understand which are the components that have an impact on energy efficiency in ISs and how this impact can be reduced. At first, we explore some guidelines that can help to understand the efficiency level of an organization and of an IS. Then, we discuss measurement and estimation of energy efficiency and identify which are the components that mainly contribute to energy waste and how it is possible to improve energy efficiency, both at the hardware and at the software level.

In this work, we present UDDI registry by example (Urbe), a novel approach for Web service retrieval based on the evaluation of similarity between Web service interfaces. Our approach assumes that the Web service interfaces are defined with Web service description language (WSDL) and the algorithm combines the analysis of their structures and the analysis of the terms used inside them. The higher the similarity, the less are the differences among their interfaces. As a consequence, Urbe is useful when we need to find a Web service suitable to replace an existing one that fails. Especially in autonomic systems, this situation is very common since we need to ensure the self-management, the self-configuration, the self-optimization, the self-healing, and the self-protection of the application that is based on the failed Web service. A semantic-oriented variant of the approach is also proposed, where we take advantage of annotations semantically enriching WSDL specifications. Semantic Annotation for WSDL (SAWSDL) is adopted as a language to annotate a WSDL description. The Urbe approach has been implemented in a prototype that extends a universal description, discovery and integration (UDDI) compliant Web service registry.

The extensive adoption of Web service-based applications in dynamic business scenarios, such as on-demand computing or highly reconfigurable virtual enterprises, advocates for methods and tools for the management of Web service nonfunctional aspects, such as Quality of Service (QoS). Concerning contracts on Web service QoS, the literature has mostly focused on the contract definition and on mechanisms for contract enactment, such as the monitoring of the satisfaction of negotiated QoS guarantees. In this context, this article proposes a framework for the automation of the Web service contract specification and establishment. An extensible model for defining both domain-dependent and domain-independent Web service QoS dimensions and a method for the automation of the contract establishment phase are proposed. We describe a matchmaking algorithm for the ranking of functionally equivalent services, which orders services on the basis of their ability to fulfill the service requestor requirements, while maintaining the price below a specified budget. We also provide an algorithm for the configuration of the negotiable part of the QoS Service-Level Agreement (SLA), which is used to configure the agreement with the top-ranked service identified in the matchmaking phase. Experimental results show that, in a utility theory perspective, the contract establishment phase leads to efficient outcomes. We envision two advanced application scenarios for the Web service contracting framework proposed in this article. First, it can be used to enhance Web services self-healing properties in reaction to QoS-related service failures; second, it can be exploited in process optimization for the online reconfiguration of candidate Web services QoS SLAs.

E-services can be used to wrap an organization's information system and to provide a standard interface that enables cooperation with other information systems. As a consequence, e-services should not only support operating activities, but also embed mechanisms for inter-organizational coordination and control over operating activities. Inter-organizational coordination and control are based on contractual agreements that coordinate processes across cooperating companies and establish mechanisms to control the fulfillment of production goals. The objective of this paper is to describe a methodological approach for the design of e-services that supports the specification of inter-organizational coordination and control requirements. The paper explains how the methodology is structured in three phases, from requirements specification to conceptual design and implementation. The first phase of the methodology supports the specification of cooperation requirements, which constitute the static description of coordination and control requirements. In the second methodological phase, this static description is completed with a dynamic description of the actions to be taken upon exceptions, which occur when cooperating partners do not comply with cooperation goals. The static and dynamic description of coordination and control represent a conceptual specification of a business transaction. In the final methodological phase, this conceptual specification is implemented based on the WSDL and BPEL4WS languages for e-service design. The methodology is tested on the case study of the Italian production district of Matera.

Many different applications in different areas need to deal with both: databases, in order to take into account large amounts of structured data; and quantitative and qualitative temporal constraints about such data. We propose an approach that extends: temporal databases and artificial intelligence temporal reasoning techniques and integrate them in order to face such a need. Regarding temporal reasoning, we consider some results that we proved recently about efficient query answering in the Simple Temporal Problem framework and we extend them in order to deal with partitioned sets of constraints and to support relational database operations. Regarding databases, we extend the relational model in order to consider also qualitative and quantitative temporal constraints both in the data (data expressiveness) and in the queries (query expressiveness). We then propose a modular architecture integrating a relational database with a temporal reasoner. We also consider classes of applications that fit into our approach and consider patient management in a hospital as an example.

The problem of analyzing and classifying conceptual schemas is becomig increasingly important due to the availability of a large number of schemas related to existing applications. The purposes of schema analysis and classification activities can be different: to extract information on intensional properties of legacy systems in order to restructure or migrate to new architectures; to build libraries of reference conceptual components to be used in building new applications in a given domain; and to identify information flows and possible replication of data in an organization. This article proposes a set of techniques for schema analysis and classification to be used separately or in combination. The techniques allow the analyst to derive significant properties from schemas, with human intervention limited as far as possible. In particular, techniques for associating descriptors with schemas, for abstracting reference conceptual schemas based on schema clustering, and for determining schema similarity are presented. A methodology for systematic schema analysis is illustrated, with the purpose of identifying and abstracting into reference components the similar and potentially reusable parts of a set of schemas. Experiences deriving from the application of the proposed techniques and methodology on a large set of Entity-Relationship conceptual schemas of information systems in the Italian Public Administration domain are described

In many computer-based applications, temporal information has to be stored, retrieved, and related to other temporal information. Several time models have been proposed to manage temporal knowledge in the fields of conceptual modeling, database systems, and artificial intelligence. In this paper we present TSOS, a system for reasoning about time that can be integrated as a time expert in environments designed for broader problem-solving domains. The main intended goal of TSOS is to allow a user to infer further information on the temporal data stored in the database through a set of deduction rules handling various aspects of time. For this purpose, TSOS provides the capability of answering queries about the temporal specifications it has in its temporal database. Distinctive time-modeling features of TSOS are the introduction of temporal modalitites , i.e., the possibility of specifying if a piece of information is always true within a time interval, or if it is only sometimes true, and the capability of answering about the possibility and the necessity of the validity of some information at a given time, the association of temporal knowledge both to instances of data and to types of data , and the development of a time calculus for reasoning on temporal data. Another relevant feature of TSOS is the capability to reason about temporal data specified at different time granularities.

Characteristics and requirements of systems for temporal data management in the areas of data and knowledge bases, artificial intelligence, and software engineering are investigated and discussed on the basis of a case study. Six representative approaches were selected for this analysis, with the goal of identifying particular features of systems proposed in different areas. The six approaches are: Allen's interval-based logic, Dean and McDermott's time map management, Kowalski and Sergot's event calculus, Maiocchi and Pernici's TSOS. Snodgrass' TQuel, and Hagelstein's ERAE. The characteristics of each system are classified and compared. On the basis of this analysis, a framework for the evaluation of temporal systems and for the specification of temporal data management systems is proposed.>

Designers of office information systems, which share various features with information systems and software development, need to carefully consider special issues such as document and communication flows, user roles, user interfaces, and available technology. The ESPRIT Project, Automatic TOols for Designing Office Information Systems (TODOS), proposes an integrated environment for office design with tools for requirements collection and analysis, conceptual design, rapid prototyping, and architecture selection. Conceptual design is a central phase of office system design: It provides correct and complete functional requirements from which the office prototype will be developed and the final architecture chosen. C-TODOS, the conceptual design support tool developed within TODOS, is presented in this paper. The purpose of C-TODOS is to give the designer tools for supporting conceptual modeling activities with the goal of obtaining correct, consistent, and good quality office-functional specifications. This paper presents C-TODOS within the TODOS development environment and describes the basic features of the tool: the TODOS Conceptual Model, the Specification Database, and the Modeling, Query and Consistency Checking Modules. The use of C-TODOS, through illustration of the development of a test case, and possible future research are discussed.

article Time modeling in office information systems Share on Authors: F. Barbic Dipartimento di Elettronica, Politecnico di Milano Dipartimento di Elettronica, Politecnico di MilanoView Profile , B. Pernici CSISEI - CNR, Politecnico di Milano CSISEI - CNR, Politecnico di MilanoView Profile Authors Info & Claims ACM SIGMOD RecordVolume 14Issue 4May 1985 pp 51–62https://doi.org/10.1145/971699.318902Online:01 May 1985Publication History 17citation295DownloadsMetricsTotal Citations17Total Downloads295Last 12 Months5Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

The original characteristics of an office information system, when compared to a conventional information system, imply the need for developing new design methodologies and models, or for substantially changing existing design approaches.In this paper the relevant features of office information systems are outlined and some existing office methodologies and models are classified and evaluated.Particular emphasis is given to the early phases of the design process, commonly called "conceptual" or "logical" design phases.The basic requirements for conceptual design methodologies in the office environment are derived from the analysis and evaluation of existing design approaches.