Composite interests' exploration thanks to on-the-fly linked data spreading activation

International audienceExploratory search systems are built specifically to help the user in his cognitive consuming search tasks like learning or topic investigation. Some of these systems are built on the top of linked data and use semantics to provide cognitively-optimized search experiences. Thanks to their richness and to their connected nature linked data datasets can serve as a ground for advanced exploratory search. We propose to address the case of mixed interests' exploration in the form of composite queries (several unitary interests combined) e.g. exploring results and make discoveries related to both The Beatles and Ken Loach. The main contribution of this paper is the proposition of a novel method that processes linked-data for exploratory search purpose. It makes use of a semantic spreading activation algorithm coupled with a sampling technique. Its particularity is to not require any results preprocessing. Consequently this method offers a high level of flexibility for querying and allows, among others, the expression of composite interests' queries on remote linked data sources. This paper also details the analysis of the algorithm behavior over DBpedia and describes an implementation: the Discovery Hub application. It is an exploratory search engine that notably supports composite queries. Finally the results of a user evaluation are presented

Knowledge graphs for covid-19: An exploratory review of the current landscape

Background: Searching through the COVID-19 research literature to gain actionable clinical insight is a formidable task, even for experts. The usefulness of this corpus in terms of improving patient care is tied to the ability to see the big picture that emerges when the studies are seen in conjunction rather than in isolation. When the answer to a search query requires linking together multiple pieces of information across documents, simple keyword searches are insufficient. To answer such complex information needs, an innovative artificial intelligence (AI) technology named a knowledge graph (KG) could prove to be effective. Methods: We conducted an exploratory literature review of KG applications in the context of COVID-19. The search term used was "covid-19 knowledge graph". In addition to PubMed, the first five pages of search results for Google Scholar and Google were considered for inclusion. Google Scholar was used to include non-peer-reviewed or non-indexed articles such as pre-prints and conference proceedings. Google was used to identify companies or consortiums active in this domain that have not published any literature, peer-reviewed or otherwise. Results: Our search yielded 34 results on PubMed and 50 results each on Google and Google Scholar. We found KGs being used for facilitating literature search, drug repurposing, clinical trial mapping, and risk factor analysis. Conclusions: Our synopses of these works make a compelling case for the utility of this nascent field of research

Active Collaboration Learning Environments: The Class of Web 2.0

The maturity and increased integration of online collaboration, networking, and research tools offer Information Systems faculty opportunities to provide unique learning environments at multiple levels. A growing ensemble of Web 2.0 technologies provide the background to introduce and explore fundamental aspects of information system development, design, application, and use, while simultaneously providing a functional suite of tools which will aid students in other aspects of their university learning. A selection of these technologies and case studies of their classroom usage is discussed. In addition, an agenda for research in both pedagogy and in information systems phenomena is outlined

Engage D2.2 Final Communication and Dissemination Report

This deliverable reports on the communication and dissemination activities carried out by the Engage consortium over the duration of the network. Planned activities have been adapted due to the Covid-19 pandemic, however a full programme of workshops and summer schools has been organised. Support has been given to the annual SESAR Innovation Days conference and there has been an Engage presence at many other events. The Engage website launched in the first month of the network. This was later joined by the Engage ‘knowledge hub’, known as the EngageWiki, which hosts ATM research and knowledge. The wiki provides a platform and consolidated repository with novel user functionality, as well as an additional channel for the dissemination of SESAR results. Engage has also supported and publicised numerous research outputs produced by PhD candidates and catalyst fund projects

VAS (Visual Analysis System): An information visualization engine to interpret World Wide Web structure

People increasingly encounter problems of interpreting and filtering mass quantities of information. The enormous growth of information systems on the World Wide Web has demonstrated that we need systems to filter, interpret, organize and present information in ways that allow users to use these large quantities of information. People need to be able to extract knowledge from this sometimes meaningful but sometimes useless mass of data in order to make informed decisions. Web users need to have some kind of information about the sort of page they might visit, such as, is it a rarely referenced or often-referenced page? This master\u27s thesis presents a method to address these problems using data mining and information visualization techniques

Recommendations for collaborative paediatric research including biobanking in Europe: a Single Hub and Access point for paediatric Rheumatology in Europe (SHARE) initiative

Innovative research in childhood rheumatic diseases mandates international collaborations. However, researchers struggle with significant regulatory heterogeneity; an enabling European Union (EU)-wide framework is missing. The aims of the study were to systematically review the evidence for best practice and to establish recommendations for collaborative research. The Paediatric Rheumatology European Single Hub and Access point for paediatric Rheumatology in Europe (SHARE) project enabled a scoping review and expert discussion, which then informed the systematic literature review. Published evidence was synthesised; recommendations were drafted. An iterative review process and consultations with Ethics Committees and European experts for ethical and legal aspects of paediatric research refined the recommendations. SHARE experts and patient representatives vetted the proposed recommendations at a consensus meeting using Nominal Group Technique. Agreement of 80% was mandatory for inclusion. The systematic literature review returned 1319 records. A total of 223 full-text publications plus 22 international normative documents were reviewed; 85 publications and 16 normative documents were included. A total of 21 recommendations were established including general principles (1-3), ethics (4-7), paediatric principles (8 and 9), consent to paediatric research (10-14), paediatric databank and biobank (15 and 16), sharing of data and samples (17-19), and commercialisation and third parties (20 and 21). The refined recommendations resulted in an agreement of >80% for all recommendations. The SHARE initiative established the first recommendations for Paediatric Rheumatology collaborative research across borders in Europe. These provide strong support for an urgently needed European framework and evidence-based guidance for its implementation. Such changes will promote research in children with rheumatic diseases