@book{
 title = {Automatic annotation of bioinformatics workflows with biomedical ontologies},
 type = {book},
 year = {2014},
 source = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 keywords = {Bioinformatics,Ontologies,Scientific workflows,Semantic annotation,Tags,Term extraction,Text mining,Web services},
 volume = {8803},
 id = {6fcf84a2-c4b9-3eb0-8476-a57a62dc7cb6},
 created = {2017-12-03T10:44:25.364Z},
 file_attached = {false},
 profile_id = {17c87d5d-2470-32d7-b273-0734a1d9195f},
 last_modified = {2017-12-12T09:00:54.060Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {© Springer-Verlag Berlin Heidelberg 2014. Legacy scientific workflows, and the services within them, often present scarce and unstructured (i.e. textual) descriptions. This makes it difficult to find, share and reuse them, thus dramatically reducing their value to the community. This paper presents an approach to annotating workflows and their subcomponents with ontology terms, in an attempt to describe these artifacts in a structured way. Despite a dearth of even textual descriptions, we automatically annotated 530 my- Experiment bioinformatics-related workflows, including more than 2600 workflow-associated services, with relevant ontological terms. Quantitative evaluation of the Information Content of these terms suggests that, in cases where annotation was possible at all, the annotation quality was comparable to manually curated bioinformatics resources.},
 bibtype = {book},
 author = {García-Jiménez, B. and Wilkinson, M.D.}
}

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