Stealthy annotation of experimental biology by spreadsheets. (10th October 2012)

• Record Type: Journal Article
• Authors: Wolstencroft, Katherine; Owen, Stuart; Horridge, Matthew; Jupp, Simon; Krebs, Olga; Snoep, Jacky; du, Franco; Mueller, Wolfgang; Stevens, Robert; Goble, Carole; Remick, Carolyn; Hunt, James; Javid, Harold; Bougé, Luc; Lengauer, Christian
• Is Part Of: Concurrency and computation. Volume 25:Number 4(2013:Mar.)
• Page Start: 467
• Page End: 480
• Publication Date: 2012-10-10
• Subjects: Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.2941
• Languages: English
• ISSNs: 1532-0626

Abstract

<abstract abstract-type="main"> <title>SUMMARY</title> <p>The increase in volume and complexity of biological data has led to increased requirements to reuse that data. Consistent and accurate metadata is essential for this task, creating new challenges in semantic data annotation and in the constriction of terminologies and ontologies used for annotation. The BioSharing community are developing standards and terminologies for annotation, which have been adopted across bioinformatics, but the real challenge is to make these standards accessible to laboratory scientists. Widespread adoption requires the provision of tools to assist scientists whilst reducing the complexities of working with semantics. This paper describes unobtrusive 'stealthy' methods for collecting standards compliant, semantically annotated data and for contributing to ontologies used for those annotations. Spreadsheets are ubiquitous in laboratory data management. Our spreadsheet‐based RightField tool enables scientists to structure information and select ontology terms for annotation within spreadsheets, producing high quality, consistent data without changing common working practices. Furthermore, our Populous spreadsheet tool proves effective for gathering domain knowledge in the form of Web Ontology Language (OWL) ontologies. Such a corpus of structured and semantically enriched knowledge can be extracted in Resource Description Framework (RDF), providing further means for searching across the content and contributing to Open Linked Data (http://linkeddata.org/). Copyright © 2012 John Wiley & Sons, Ltd.</p> </abstract>