Representing and coding the knowledge embedded in texts of Health Science Web published articles

Despite the fact that electronic publishing is a common activity to scholars electronic journals are still based in the print model and do not take full advantage of the facilities offered by the Semantic Web environment. This is a report of the results of a research project with the aim of investigating the possibilities of electronic publishing journal articles both as text for human reading and in machine readable format recording the new knowledge contained in the article. This knowledge is identified with the scientific methodology elements such as problem, methodology, hypothesis, results, and conclusions. A model integrating all those elements is proposed which makes explicit and records the knowledge embedded in the text of scientific articles as an ontology. Knowledge thus represented enables its processing by intelligent software agents The proposed model aims to take advantage of these facilities enabling semantic retrieval and validation of the knowledge contained in articles. To validate and enhance the model a set of electronic journal articles were analyzed

Discovery Tools and Local Metadata Requirements in Academic Libraries

As the second decade of the twenty-first century commences, academic librarians who work to promote collection access must not only contend with a vast array of content available in a wide range of formats, but they must also ensure that new technologies developed to accommodate user search behaviors yield satisfactory outcomes. Next generation discovery tools are designed to streamline the search process and facilitate better search results by incorporating metadata from proprietary and local collections, then by providing relevancy-ranked results. This paper investigates the implications of discovery tool use for accessing materials housed in institutional repositories and special collections, in particular, how the discovery of these materials depends on local metadata creation practices. This paper surveys current research pertaining to metadata quality issues that may put unique local collections at risk for being overlooked in meta-search relevancy rankings, and considers ways in which academic libraries can address this issue as well as areas for future research

General cost analysis for scholarly communication in Germany : results of the "Houghton Report" for Germany

Management Summary: Conducted within the project “Economic Implications of New Models for Information Supply for Science and Research in Germany”, the Houghton Report for Germany provides a general cost and benefit analysis for scientific communication in Germany comparing different scenarios according to their specific costs and explicitly including the German National License Program (NLP). Basing on the scholarly lifecycle process model outlined by Björk (2007), the study compared the following scenarios according to their accounted costs: - Traditional subscription publishing, - Open access publishing (Gold Open Access; refers primarily to journal publishing where access is free of charge to readers, while the authors or funding organisations pay for publication) - Open Access self-archiving (authors deposit their work in online open access institutional or subject-based repositories, making it freely available to anyone with Internet access; further divided into (i) CGreen Open Access’ self-archiving operating in parallel with subscription publishing; and (ii) the ‘overlay services’ model in which self-archiving provides the foundation for overlay services (e.g. peer review, branding and quality control services)) - the NLP. Within all scenarios, five core activity elements (Fund research and research communication; perform research and communicate the results; publish scientific and scholarly works; facilitate dissemination, retrieval and preservation; study publications and apply the knowledge) were modeled and priced with all their including activities. Modelling the impacts of an increase in accessibility and efficiency resulting from more open access on returns to R&D over a 20 year period and then comparing costs and benefits, we find that the benefits of open access publishing models are likely to substantially outweigh the costs and, while smaller, the benefits of the German NLP also exceed the costs. This analysis of the potential benefits of more open access to research findings suggests that different publishing models can make a material difference to the benefits realised, as well as the costs faced. It seems likely that more Open Access would have substantial net benefits in the longer term and, while net benefits may be lower during a transitional period, they are likely to be positive for both ‘author-pays’ Open Access publishing and the ‘over-lay journals’ alternatives (‘Gold Open Access’), and for parallel subscription publishing and self-archiving (‘Green Open Access’). The NLP returns substantial benefits and savings at a modest cost, returning one of the highest benefit/cost ratios available from unilateral national policies during a transitional period (second to that of ‘Green Open Access’ self-archiving). Whether ‘Green Open Access’ self-archiving in parallel with subscriptions is a sustainable model over the longer term is debateable, and what impact the NLP may have on the take up of Open Access alternatives is also an important consideration. So too is the potential for developments in Open Access or other scholarly publishing business models to significantly change the relative cost-benefit of the NLP over time. The results are comparable to those of previous studies from the UK and Netherlands. Green Open Access in parallel with the traditional model yields the best benefits/cost ratio. Beside its benefits/cost ratio, the meaningfulness of the NLP is given by its enforceability. The true costs of toll access publishing (beside the buyback” of information) is the prohibition of access to research and knowledge for society

Web Service Discovery in a Semantically Extended UDDI Registry: the Case of FUSION

Service-oriented computing is being adopted at an unprecedented rate, making the effectiveness of automated service discovery an increasingly important challenge. UDDI has emerged as a de facto industry standard and fundamental building block within SOA infrastructures. Nevertheless, conventional UDDI registries lack means to provide unambiguous, semantically rich representations of Web service capabilities, and the logic inference power required for facilitating automated service discovery. To overcome this important limitation, a number of approaches have been proposed towards augmenting Web service discovery with semantics. This paper discusses the benefits of semantically extending Web service descriptions and UDDI registries, and presents an overview of the approach put forward in project FUSION, towards semantically-enhanced publication and discovery of services based on SAWSDL

Improving average ranking precision in user searches for biomedical research datasets

Availability of research datasets is keystone for health and life science study reproducibility and scientific progress. Due to the heterogeneity and complexity of these data, a main challenge to be overcome by research data management systems is to provide users with the best answers for their search queries. In the context of the 2016 bioCADDIE Dataset Retrieval Challenge, we investigate a novel ranking pipeline to improve the search of datasets used in biomedical experiments. Our system comprises a query expansion model based on word embeddings, a similarity measure algorithm that takes into consideration the relevance of the query terms, and a dataset categorisation method that boosts the rank of datasets matching query constraints. The system was evaluated using a corpus with 800k datasets and 21 annotated user queries. Our system provides competitive results when compared to the other challenge participants. In the official run, it achieved the highest infAP among the participants, being +22.3% higher than the median infAP of the participant's best submissions. Overall, it is ranked at top 2 if an aggregated metric using the best official measures per participant is considered. The query expansion method showed positive impact on the system's performance increasing our baseline up to +5.0% and +3.4% for the infAP and infNDCG metrics, respectively. Our similarity measure algorithm seems to be robust, in particular compared to Divergence From Randomness framework, having smaller performance variations under different training conditions. Finally, the result categorization did not have significant impact on the system's performance. We believe that our solution could be used to enhance biomedical dataset management systems. In particular, the use of data driven query expansion methods could be an alternative to the complexity of biomedical terminologies

Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines

A cross-disciplinary examination of the user behaviours involved in seeking and evaluating data is surprisingly absent from the research data discussion. This review explores the data retrieval literature to identify commonalities in how users search for and evaluate observational research data. Two analytical frameworks rooted in information retrieval and science technology studies are used to identify key similarities in practices as a first step toward developing a model describing data retrieval

SAGA: Stellar Abundances for Galactic Archaeology

A tutorial for the Stellar Abundances for Galactic Archaeology (SAGA) database is presented. This paper describes the outline of the database, reports the current status of the data compilation and known problems, and presents plans for future updates and extensions.Comment: Proceedings of the conference, "Nuclei in the Cosmos XII", invited talk at Online Support sessio