http://precedings.nature.com/tags/Semantic%20Web Recently posted documents tagged with 'Semantic Web' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3775.1 Key assertions are extracted from “conclusions” sections of PubMed abstracts andconverted into Semantic Web / Linked Data format. The results are made accessible viafiles, a SPARQL endpoint, and a faceted search interface. Conclusion sections areidentified as valuable resources for machine-augmented key assertion identification andintegration in the biomedical domain. Results are discussed and opportunities for futurework and cooperation are highlighted. http://dx.doi.org/10.1038/npre.2009.3775.1 Mon, 21 Sep 2009 08:29:29 UTC Extracting conclusion sections from PubMed abstracts for rapid key assertion integration in biomedical research doi:10.1038/npre.2009.3775.1 2009-09-21 Nature Precedings 2009-09-21T08:29:29Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3562/version/1 While OWL, the Web Ontology Language, is often regarded as the preferred language for Knowledge Representation in the world of the Semantic Web, the potential of direct representation in RDF, the Resource Description Framework, is underestimated. Here we show how ontologies adequately represented in RDF could be semantically enriched with SPARUL. To deal with the semantics of relations we created Metarel, a meta-ontology for relations. The utility of the approach is demonstrated by an application on Gene Ontology Annotation (GOA) RDF graphs in the RDF Knowledge Base BioGateway. We show that Metarel can facilitate inferencing in BioGateway, which allows for queries that are otherwise not possible. Metarel is available on http://www.metarel.org. http://precedings.nature.com/documents/3562/version/1 Thu, 06 Aug 2009 19:10:14 UTC Metarel: an Ontology to support the inferencing of Semantic Web relations within Biomedical Ontologies hdl:10101/npre.2009.3562.1 2009-08-06 Ward Blondé Nature Precedings 2009-08-06T19:10:14Z Manuscript Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3225.1 Data curation has been critical in the development of biology from Darwin and Linnaeus to UniProt, the careful collection and organisation of data has been the spring from which new hypotheses and understanding have emerged. In this presentation, I will describe how we have used data curation in my own research group – and also present an overview of curation at the EBI. With new technical developments and the move towards the semantic web, the role of curation in the future needs to develop to take advantage of these new opportunities. This will be discussed. http://dx.doi.org/10.1038/npre.2009.3225.1 Tue, 12 May 2009 13:19:11 UTC Data Curation in Biology – Past, Present and Future doi:10.1038/npre.2009.3225.1 2009-05-12 Nature Precedings 2009-05-12T13:19:11Z Presentation Genetics & Genomics Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3193.1 The UniProt knowledgebase (UniProtKB) is a comprehensive repository of protein sequence and annotation data. We collect information from the scientific literature and other databases and provide links to over one hundred biological resources. Such links between different databases are an important basis for data integration, but the lack of a common standard to represent and link information makes data integration an expensive business. At UniProt we have started to tackle this problem by using the Resource Description Framework (http://www.w3.org/RDF/) to represent our data. RDF is a core technology for the World Wide Web Consortium’s Semantic Web activities (http://www.w3.org/2001/sw/) and is therefore well suited to work in a distributed and decentralized environment. The RDF data model represents arbitrary information as a set of simple statements of the form subject-predicate-object. To enable the linking of data on the Web, RDF requires that each resource must have a (globally) unique identifier. These identifiers allow everybody to make statements about a given resource and, together with the simple structure of the RDF data model, make it easy to combine the statements made by different people (or databases) to allow queries across different datasets. RDF is thus an industry standard that can make a major contribution to solve two important problems of bioinformatics: distributed annotation and data integration. http://dx.doi.org/10.1038/npre.2009.3193.1 Tue, 28 Apr 2009 18:42:07 UTC UniProt in RDF: Tackling Data Integration and Distributed Annotation with the Semantic Web doi:10.1038/npre.2009.3193.1 2009-04-28 Nicole Redaschi Nature Precedings 2009-04-28T18:42:07Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3173/version/1 Although the Web has transformed science publishing, scientific papers themselves are still essentially “black boxes”, with much of their content intended for human readers only. Typically, computer-readable metadata associated with an article is limited to bibliographic details. By expanding article metadata to include taxonomic names, identifiers for cited material (e.g., publications, sequences, specimens, and other data), and geographical coordinates, publishers could greatly increase the scientific value of their digital content. At the same time this will provide novel ways for users to discover and navigate through this content, beyond the relatively limited linkage provided by bibliographic citation.As a proof of concept, my entry in the Elsevier Grand Challenge extracted extended metadata from a set of articles from the journal Molecular Phylogeny and Evolution and used it to populate a entity-attribute-value database. A simple web interface to this database enables an enhanced display of the content of an article, including a map of localities mentioned either explicitly or implicitly (through links to geotagged data), taxonomic coverage, and both data and citation links. Metadata extraction was limited to information listed in tables in the articles (such as GenBank sequences and specimen codes), the body of the article wasn’t used. This restriction was deliberate, in order to demonstrate that making extended metadata available doesn’t require a journal’s publisher to make the full-text freely available (although this is desirable for other reasons). http://precedings.nature.com/documents/3173/version/1 Fri, 24 Apr 2009 17:31:02 UTC Enhanced display of scientific articles using extended metadata hdl:10101/npre.2009.3173.1 2009-04-24 Roderic D. M. Page Nature Precedings 2009-04-24T17:31:02Z Manuscript Ecology Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3079/version/1 Linking together the data of interest to biodiversity researchers (including specimen records, images, taxonomic names, and DNA sequences) requires services that can mint, resolve, and discover globally unique identifiers (including, but not limited to, DOIs, HTTP URIs, and LSIDs). bioGUID implements a range of services, the core ones being an OpenURL resolver for bibliographic resources, and a LSID resolver. The LSID resolver supports Linked Data-friendly resolution using HTTP 303 redirects and content negotiation. Additional services include journal ISSN look-up, author name matching, and a tool to monitor the status of biodiversity data providers. bioGUID is available at http://bioguid.info/. Source code is available from Google Code. http://precedings.nature.com/documents/3079/version/1 Fri, 17 Apr 2009 21:01:04 UTC bioGUID: resolving, discovering, and minting identifiers for biodiversity informatics hdl:10101/npre.2009.3079.1 2009-04-17 Roderic Page Nature Precedings 2009-04-17T21:01:04Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2579.1 This paper describes my entry in the Elsevier Grand Challenge “Knowledge Enhancement in the Life Sciences” contest. The entry takes a collection of fulltext issues of Molecular Phylogenetics and Evolution as the starting point, then extracts citation links to both papers and data, such as Genbank sequences and specimens, together with geotagged localities, and builds a “web” of objects linked by typed relationships. Each object (such as a publication, a sequence, a specimen, a taxon name, etc.) is treated equally, so that you can take a publication and see what taxa it refers to, or take the taxon and find all the publications that refer to the taxon. Although the database has been seeded with some articles from Molecular Phylogenetics and Evolution, much of the data comes from GenBank, PubMed, and specimen databases. These are accessed through bioGUID, a tool I constructed to resolve globally unique identifiers and return associated metadata. http://dx.doi.org/10.1038/npre.2008.2579.1 Fri, 28 Nov 2008 16:52:15 UTC Visualising a scientific article doi:10.1038/npre.2008.2579.1 2008-11-28 Roderic Page Nature Precedings 2008-11-28T16:52:15Z Manuscript Ecology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2337/version/1 Extraction of protein-protein interactions data from scientific literature remains a hard, time- and resource-consuming task. This task would be greatly simplified by embedding in the source, i.e. research articles, a standardized, synthetic, machine-readable codification for protein-protein interactions data description, to make the identification and the retrieval of such very valuable information easier, faster, and more reliable than now.We shortly discuss how this information can be easily encoded and embedded in research papers with the collaboration of authors and scientific publishers, and propose an online demonstrative tool that shows how to help and allow authors for the easy and fast conversion of such valuable biological data into an embeddable, accessible, computer-readable codification. http://precedings.nature.com/documents/2337/version/1 Wed, 01 Oct 2008 10:19:29 UTC Embedding machine-readable proteins interactions data in scientific articles for easy access and retrieval hdl:10101/npre.2008.2337.1 2008-10-01 Paolo Tieri Nature Precedings 2008-10-01T10:19:29Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2176.1 Presented as part of the session titled “Sharing scientific data: who benefits?” at ESOF (The Euroscience Open Forum) 2008.Session abstract: Digital datasets—text-based, numeric, audio, video or image-based—form the output of all scientific disciplines. How are these data being made available for sharing? What quality control mechanisms are in place? What kinds of naming conventions, tags, and metadata are in use and how effective are they at helping to manage open data? Who is storing, archiving and curating open data and at which levels? And how is the production and sharing of open data assessed: what processes are in place for crediting scientists for making their raw data openly accessible for sharing and use? How much can and should data publication replace traditional forms of publication of research findings? http://dx.doi.org/10.1038/npre.2008.2176.1 Tue, 19 Aug 2008 19:56:47 UTC What are the ethical and social responsibilities of scientists? doi:10.1038/npre.2008.2176.1 2008-08-19 Philip Campbell Nature Precedings 2008-08-19T19:56:47Z Presentation Genetics & Genomics Molecular Cell Biology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1760/version/1 A major challenge facing biodiversity informatics is integrating data stored in widely distributed databases. Initial efforts have relied on taxonomic names as the shared identifier linking records in different databases. However, taxonomic names have limitations as identifiers, being neither stable nor globally unique, and the pace of molecular taxonomic and phylogenetic research means that a lot of information in public sequence databases is not linked to formal taxonomic names. This review explores the use of other identifiers, such as specimen codes and GenBank accession numbers, to link otherwise disconnected facts in different databases. The structure of these links can also be exploited using the PageRank algorithm to rank the results of searches on biodiversity databases. The key to rich integration is a commitment to deploy and reuse globally unique, shared identifiers (such as DOIs and LSIDs), and the implementation of services that link those identifiers. http://precedings.nature.com/documents/1760/version/1 Thu, 03 Apr 2008 20:10:36 UTC Biodiversity informatics: the challenge of linking data and the role of shared identifiers hdl:10101/npre.2008.1760.1 2008-04-03 Roderic Page Nature Precedings 2008-04-03T20:10:36Z Manuscript Ecology Bioinformatics http://creativecommons.org/licenses/by/3.0/