Migrating data-intensive web sites into the Semantic Web
Proceedings of the 2002 ACM symposium on Applied computing
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Generating Relations from XML Documents
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Towards the self-annotating web
Proceedings of the 13th international conference on World Wide Web
Learning domain ontologies for Web service descriptions: an experiment in bioinformatics
WWW '05 Proceedings of the 14th international conference on World Wide Web
XStruct: Efficient Schema Extraction from Multiple and Large XML Documents
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
OntoMiner: Bootstrapping and Populating Ontologies from Domain-Specific Web Sites
IEEE Intelligent Systems
Semantic web infrastructure for fungal enzyme biotechnologists
Web Semantics: Science, Services and Agents on the World Wide Web
Aggregation of bioinformatics data using Semantic Web technology
Web Semantics: Science, Services and Agents on the World Wide Web
Transforming arbitrary tables into logical form with TARTAR
Data & Knowledge Engineering
Automatic Generation of Ontology from the Deep Web
DEXA '07 Proceedings of the 18th International Conference on Database and Expert Systems Applications
Inferring XML schema definitions from XML data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Systems biology metabolic modeling assistant
Bioinformatics
Triplify: light-weight linked data publication from relational databases
Proceedings of the 18th international conference on World wide web
OpenFlyData: The Way to Go for Biological Data Integration
DILS '09 Proceedings of the 6th International Workshop on Data Integration in the Life Sciences
Site-Wide Wrapper Induction for Life Science Deep Web Databases
DILS '09 Proceedings of the 6th International Workshop on Data Integration in the Life Sciences
Learning concept hierarchies from text corpora using formal concept analysis
Journal of Artificial Intelligence Research
On how to perform a gold standard based evaluation of ontology learning
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
Link prediction for annotation graphs using graph summarization
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
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In the Linked Open Data cloud one of the largest data sets, comprising of 2.5 billion triples, is derived from the Life Science domain. Yet this represents a small fraction of the total number of publicly available data sources on the Web. We briefly describe past attempts to transform specific Life Science sources from a plethora of open as well as proprietary formats into RDF data. In particular, we identify and tackle two bottlenecks in current practice: Acquiring ontologies to formally describe these data and creating “RDFizer” programs to convert data from legacy formats into RDF. We propose an unsupervised method, based on transformation rules, for performing these two key tasks, which makes use of our previous work on unsupervised wrapper induction for extracting labelled data from complete Life Science Web sites. We apply our approach to 13 real-world online Life Science databases. The learned ontologies are evaluated by domain experts as well as against gold standard ontologies. Furthermore, we compare the learned ontologies against ontologies that are “lifted” directly from the underlying relational schema using an existing unsupervised approach. Finally, we apply our approach to three online databases to extract RDF data. Our results indicate that this approach can be used to bootstrap and speed up the migration of life science data into the Linked Open Data cloud.