Enhancing reuse of data and biological material in medical research : from FAIR to FAIR-Health

The known challenge of underutilization of data and biological material from biorepositories as potential resources formedical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability—entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)—are likely to address only parts of the problem. In this article,we argue that biologicalmaterial and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks.Wepropose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.peer-reviewe

Recommending Items in Social Tagging Systems Using Tag and Time Information

In this work we present a novel item recommendation approach that aims at improving Collaborative Filtering (CF) in social tagging systems using the information about tags and time. Our algorithm follows a two-step approach, where in the first step a potentially interesting candidate item-set is found using user-based CF and in the second step this candidate item-set is ranked using item-based CF. Within this ranking step we integrate the information of tag usage and time using the Base-Level Learning (BLL) equation coming from human memory theory that is used to determine the reuse-probability of words and tags using a power-law forgetting function. As the results of our extensive evaluation conducted on data-sets gathered from three social tagging systems (BibSonomy, CiteULike and MovieLens) show, the usage of tag-based and time information via the BLL equation also helps to improve the ranking and recommendation process of items and thus, can be used to realize an effective item recommender that outperforms two alternative algorithms which also exploit time and tag-based information.Comment: 6 pages, 2 tables, 9 figure

App creation in schools for different curricula subjects - lesson learned

The next generation of jobs will be characterized by an increased demand for people with computational and problem solving skills. In Austria, computer science topics are underrepresented in school curricula hence teaching time for these topics is limited. From primary through secondary school, only a few opportunities exist for young students to explore programming. Furthermore, today's teachers are rarely trained in computer science, which impairs their potential to motivate students in these courses. Within the "No One Left Behind" (NOLB) project, teachers were supported to guide and assist their students in their learning processes by constructing ideas through game making. Thus, students created games that referred to different subject areas by using the programming tool Pocket Code, an app developed at Graz University of Technology (TU-Graz). This tool helps students to take control of their own education, becoming more engaged, interested, and empowered as a result. To ensure an optimal integration of the app in diverse subjects the different backgrounds (technical and non-technical) of teachers must be considered as well. First, teachers were supported to use Pocket Code in the different subjects in school within the feasibility study of the project. Observed challenges and difficulties using the app have been gathered. Second, we conducted interviews with teachers and students to underpin our onsite observations. As a result, it was possible to validate Pocket Codes' potential to be used in a diverse range of subjects. Third, we focused especially on those teachers who were not technically trained to provide them with a framework for Pocket Code units, e.g., with the help of structured lesson plans and predefined templates.Comment: 10 pages, 5 tables EduLearn 201

UT Linked Data Informal Learning Discussion Series Bibliography

The following bibliographies were created as part of the UT Linked Data Informal Learning Discussion Series hosted at UT LibrariesThe following bibliographies were created as part of the UT Linked Data Informal Learning Discussion Series hosted at UT LibrariesUT Librarie

Barry Smith an sich

Festschrift in Honor of Barry Smith on the occasion of his 65th Birthday. Published as issue 4:4 of the journal Cosmos + Taxis: Studies in Emergent Order and Organization. Includes contributions by Wolfgang Grassl, Nicola Guarino, John T. Kearns, Rudolf Lüthe, Luc Schneider, Peter Simons, Wojciech Żełaniec, and Jan Woleński

Singing voice separation based on non-vocal independent component subtraction and amplitude discrimination

Copyright Institute of Electronic Music and AcousticsMany applications of Music Information Retrieval can benefit from effective isolation of the music sources. Earlier work by the authors led to the development of a system that is based on Azimuth Discrimination and Resynthesis (ADRess) and can extract the singing voice from reverberant stereophonic mixtures. We propose an extension to our previous method that is not based on ADRess and exploits both channels of the stereo mix more effectively. For the evaluation of the system we use a dataset that contains songs convolved during mastering as well as the mixing process (i.e. “real-world” conditions). The metrics for objective evaluation are based on bss_eval

OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories

In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and adapts its concepts to knowledge engineering for Maven-based ontology development and management of ontology artifacts in distributed ontology repositories.Comment: Pre-print submission to 9th International Workshop on Semantic Web Enabled Software Engineering (SWESE2013). Berlin, Germany, December 2-5, 201