Biotea: RDFizing PubMed Central in support for the paper as an interface to the Web of Data

Castro, Leyla Jael; McLaughlin, Casey; García, Alexander

doi:10.1186/2041-1480-4-s1-s5

Cited by 20 publications

(15 citation statements)

References 22 publications

(32 reference statements)

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“…For a reliable linkage to data sets a permanent unique identifier from initiatives such as DataCite [3] is needed. Some prototype systems use this approach to show the connections between publications and research data to the end user, e.g., in the context of the OpenAire infrastructure [14] or of Pubmed Central [9]. A more specialized approach is the Data Documentation Initiative (DDI) [20].…”

Section: Linking and Retrieving Of Social Science Informationmentioning

confidence: 99%

A Digital Library for Research Data and Related Information in the Social Sciences

Hienert

Kern

Boland

et al. 2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search system for social science information that allows finding information around research data in a single digital library. Users can search for research data sets, publications, survey variables, questions from questionnaires, survey instruments, and tools. Information items are linked to each other so that users can see, for example, which publications contain data citations to research data. The integration and linking of different kinds of information increase their visibility so that it is easier for researchers to find information for re-use. In a log-based usage study, we found that users search across different information types, that search sessions contain a high rate of positive signals and that link information is often explored. CCS CONCEPTS• Information systems~Digital libraries and archives

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Section: Linking and Retrieving Of Social Science Informationmentioning

confidence: 99%

A Digital Library for Research Data and Related Information in the Social Sciences

Hienert

Kern

Boland

et al. 2019

2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)

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“…The BioTea project [4] deserves a special mention. Its goal is to make the biomedical literature available as RDF, taking papers again from PubMed Central.…”

Section: Related Workmentioning

confidence: 99%

Exploring Bibliographies for Research-related Tasks

Iorio

Giannella

Poggi

et al. 2015

Proceedings of the 24th International Conference on World Wide Web

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Bibliographies are fundamental tools for research communities. Besides the obvious uses as connection to previous research, citations are also widely used for evaluation purposes: the productivity of researchers, departments and universities is increasingly measured by counting their citations. Unfortunately, citations counters are just rough indicators: a deeper knowledge of individual citations -where, when, by whom and why -improves research evaluation tasks and supports researchers in their daily activity. Yet, such information is mostly hidden within repositories of scholarly papers and is still difficult to find, navigate and make use of.In this paper, we present a novel tool for exploring scientific articles through their citations. The environment is built on top of a rich citation network, encoded as a LOD, and includes a user-friendly interface to access, filter and highlight information about bibliographic data.

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“…Many biomedical platforms provide SPARQL endpoints to search over the data, such as EBI [15], Uniprot [16], Medical Subject Headings (Mesh) (https://id.nlm.nih.gov/mesh/query), NCBI2RDF [17], Big Linked Cancer Data [18], Biotea [19]. However, the limitation of triple store and SPARQL query in indexing scalability and the query formalization has driven Information Retrieval approaches to deal with entity search over the past few years [2].…”

Section: Related Workmentioning

confidence: 99%

Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships

Zong

Lee

Ahn

et al. 2017

Computers in Biology and Medicine

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Objective The keyword-based entity search restricts search space based on the preference of search. When given keywords and preferences are not related to the same biomedical topic, existing biomedical Linked Data search engines fail to deliver satisfactory results. This research aims to tackle this issue by supporting an inter-topic search—improving search with inputs, keywords and preferences, under different topics. Methods This study developed an effective algorithm in which the relations between biomedical entities were used in tandem with a keyword-based entity search, Siren. The algorithm, PERank, which is an adaptation of Personalized PageRank (PPR), uses a pair of input: (1) search preferences, and (2) entities from a keyword-based entity search with a keyword query, to formalize the search results on-the-fly based on the index of the precomputed Individual Personalized PageRank Vectors (IPPVs). Results Our experiments were performed over ten linked life datasets for two query sets, one with keyword-preference topic correspondence (intra-topic search), and the other without (inter-topic search). The experiments showed that the proposed method achieved better search results, for example a 14% increase in precision for the inter-topic search than the baseline keyword-based search engine. Conclusion The proposed method improved the keyword-based biomedical entity search by supporting the inter-topic search without affecting the intra-topic search based on the relations between different entities.

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Biotea: RDFizing PubMed Central in support for the paper as an interface to the Web of Data

Cited by 20 publications

References 22 publications

A Digital Library for Research Data and Related Information in the Social Sciences

A Digital Library for Research Data and Related Information in the Social Sciences

Exploring Bibliographies for Research-related Tasks

Supporting inter-topic entity search for biomedical Linked Data based on heterogeneous relationships

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