This paper1 first argues that ontology design may benefit from treating ontologies as theories and from the definition of a set of operations that map ontologies into ontologies, especially their constraints. The paper then defines the class of ontologies used and proposes four operations to manipulate them. It proceeds to discuss how the operations may help design new ontologies. The core of the paper describes an implementation of the operations as a Protégé plug-in, called OntologyManagerTab, and includes use case examples to validate the discussion.

ISCOOL is an interactive educational game for text analysis and interpretation. It draws from several reference datasets, providing users with information about people, organisations and locations, as well as word definitions and historical facts that serve as the basis for reading comprehension and provide a wider context for information to be accessed, interpreted and understood. In game-play, users choose images to best illustrate a read text. The interactivity of the game encourages users to test their knowledge, and critically analyse what was read. ISCOOL was assessed by students with low literacy levels in English. The results show high levels of acceptance and applicability to genuine learning activities.

Understanding students' strengths and weaknesses can help in the design of teaching materials to successfully bridge identified gaps. Formal exams are useful to gauge the extent of learners' memorised information, but have been critiqued for not reflecting the true extent of learners knowledge. Diagnostic assessment assists teachers in setting task-specific plans and goals, for both individual students, and the learner-group as a whole. In this paper, we describe Treasure Explorers, a Game With a Purpose (GWAP) with a multilayered structure that facilitates the learning process, promotes user retention, and is designed to reward contributing players. A comprehensive evaluation based on game log and TAM model was conducted. The log of over 5,500 records reveals that aspects of engagement and learning had occurred, and qualitative evaluations show the applicability and usability of games as diagnostic assessment tools. Treasure Explorers assists teachers in identifying student difficulties, and has significant potential to help educators plan for lesson content.

Abstract: Over the last ten years, members of the WEBIST community have dedicated their time and efforts to face a number of research challenges, making significant advances in Information Systems and pointing to new directions for innovation and learning. After ten successful WEBIST conferences and several scientific pub-lications, an extensive analysis of the WEBIST conferences has been carried out (involving authors, publi-cations, conference impact, topics coverage, community analysis and other aspects) to possibly assist us to further advance Information Systems. Thus, in this paper, we present an in-depth analysis of the last ten WEBIST conferences based on social network analysis, bibliometrics and statistical measures and describe a Web-based application built on top of triplified datasets to interactively explore the findings and possibly assist the Information Systems community to reveal new directions. 1

Scientific studies are usually developed by contributions from different researchers. Analyzing such collaborations is often necessary, for example, when evaluating the quality of a research group. Also, identifying new partnership possibilities within a set of researchers is frequently desired, for example, when looking for partners in foreign countries. Both analysis and identification are not easy tasks, and are usually done manually. This work presents VRRC, a new approach for visualizing recommendations of people within a co-authorship network (i.e., a graph in which nodes represent researchers and edges represent their co-authorships). VRRC input is a publication list from which it extracts the co-authorships. VRRC then recommends which relations could be created or intensified based on metrics designed for evaluating co-authorship networks. Finally, VRRC provides brand new ways to visualize not only the final recommendations but also the intermediate interactions within the network, including: a complete representation of the co-authorship network; an overview of the collaborations evolution over time; and the recommendations for each researcher to initiate or intensify cooperation. Some visualizations are interactive, allowing to filter data by time frame and highlighting specific collaborations. The contributions of our work, compared to the state-of-art, can be summarized as follows: (i) VRRC can be applied to any co-authorship network, it provides both net and recommendation visualizations, it is a Web-based tool and it allows easy sharing of the created visualizations (existing tools do not offer all these features together); (ii) VRRC establishes graphical representations to ease the visualization of its results (traditional approaches present the recommendation results through simple lists or charts); and (iii) with VRRC, the user can identify not only new possible collaborations but also existing cooperation that can be intensified (current recommendation approaches only indicate new collaborations). This work was partially supported by CNPq, Brazil.