Abstract
BackgroundInformation technology has the potential to increase the pace of scientific progress by helping researchers in formulating, publishing and finding information. There are numerous projects that employ ontologies and Semantic Web technologies towards this goal. However, the number of applications that have found widespread use among biomedical researchers is still surprisingly small. In this paper we present the aTag (‘associative tags’) convention, which aims to drastically lower the entry barriers to the biomedical Semantic Web. aTags are short snippets of HTML+RDFa with embedded RDF/OWL based on the Semantically Interlinked Online Communities (SIOC) vocabulary and domain ontologies and taxonomies, such as the Open Biomedical Ontologies and DBpedia. The structure of aTags is very simple: a short piece of human-readable text that is ‘tagged’ with relevant ontological entities. This paper describes our efforts for seeding the creation of a viable ecosystem of datasets, tools and services around aTags.ResultsNumerous biomedical datasets in aTag format and systems for the creation of aTags have been set-up and are described in this paper. Prototypes of some of these systems are accessible at http://hcls.deri.org/atagConclusionsThe aTags convention enables the rapid development of diverse, integrated datasets and semantically interoperable applications. More work needs to be done to study the practicability of this approach in different use-case scenarios, and to encourage uptake of the convention by other groups.
Highlights
Seasonal affective disorder (SAD) is common in ...“ while the conclusion sections contain lots of these abbreviated forms that tend to be unintelligible when only the conclusion sections are viewed in isolation, e.g.: „ CONCLUSIONS: This study shows that SAD is effectively treated with ...“ The script recognizes local abbreviations and expands them, making the conclusion sections better intelligible
The aTags convention enables the rapid development of diverse, integrated datasets and semantically interoperable applications
ATags do not depend on any new vocabularies but are based on reusing the popular Semantically Interlinked Online Communities (SIOC) vocabulary [13] combined with entities from established ontologies and taxonomies, such as Open Biomedical Ontologies (OBO) ontologies or DBpedia [14,15]
Summary
Seasonal affective disorder (SAD) is common in ...“ while the conclusion sections contain lots of these abbreviated forms that tend to be unintelligible when only the conclusion sections are viewed in isolation, e.g.: „ CONCLUSIONS: This study shows that SAD is effectively treated with ...“ The script recognizes local abbreviations and expands them, making the conclusion sections better intelligible. E.g., after processing the conclusion reads “CONCLUSIONS: This study shows that Seasonal affective disorder is effectively treated with ...“ 3) The conclusion sections are extracted and turned into aTags serialized in Turtle format For this trial, each aTag was annotated with the MeSH terms associated with the article. Semantic Web technologies and ontologies hold the promise to enable the creation of smarter software systems that facilitate key assertion integration through better structuring of information, shared standards, clear semantics and global interlinking of data. These technologies have undergone remarkable progress in recent years. The Linked Data community [7] created a global network of RDF/OWL resources that consists of billions of statements, with each resource being available for fine-grained access based on established web standards
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