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Project: SysMO DB5

Abstract (Expand)

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/)

Authors: , , Matthew Horridge, Simon Jupp, , , , , Robert Stevens,

Date Published: 1st Feb 2013

Publication Type: Journal

Abstract (Expand)

Research in Systems Biology involves integrating data and knowledge about the dynamic processes in biological systems in order to understand and model them. Semantic web technologies should be ideal for exploring the complex networks of genes, proteins and metabolites that interact, but much of this data is not natively available to the semantic web. Data is typically collected and stored with free-text annotations in spreadsheets, many of which do not conform to existing metadata standards and are often not publically released. Along with initiatives to promote more data sharing, one of the main challenges is therefore to semantically annotate and extract this data so that it is available to the research community. Data annotation and curation are expensive and undervalued tasks that have enormous benefits to the discipline as a whole, but fewer benefits to the individual data producers. By embedding semantic annotation into spreadsheets, however, and automatically extracting this data into RDF at the time of repository submission, the process of producing standards-compliant data, that is available for semantic web querying, can be achieved without adding additional overheads to laboratory data management. This paper describes these strategies in the context of semantic data management in the SEEK. The SEEK is a web-based resource for sharing and exchanging Systems Biology data and models that is underpinned by the JERM ontology (Just Enough Results Model), which describes the relationships between data, models, protocols and experiments. The SEEK was originally developed for SysMO, a large European Systems Biology consortium studying micro-organisms, but it has since had widespread adoption across European Systems Biology.

Editor: David Hutchison and Takeo Kanade and Josef Kittler and Jon M. Kleinberg and Friedemann Mattern and John C. Mitchell and Moni Naor and Oscar Nierstrasz and C. Pandu Rangan and Bernhard Steffen and Madhu Sudan and Demetri Terzopoulos and Doug Tygar and Moshe Y. Vardi and Gerhard Weikum and Camille Salinesi and Moira C. Norrie and Óscar Pastor

Date Published: 2013

Publication Type: Journal

Abstract (Expand)

Encouraging more broad and inclusive data sharing in today's world will involve concerted community efforts to overcome technical barriers and human foibles. Vivien Marx investigates. (includess comments from Carole Goble, and mentions SysMO, SEEK and RightField).

Author: Vivien Marx

Date Published: 7th Jun 2012

Publication Type: Not specified

Abstract (Expand)

BACKGROUND: Ontologies are being developed for the life sciences to standardise the way we describe and interpret the wealth of data currently being generated. As more ontology based applications begin to emerge, tools are required that enable domain experts to contribute their knowledge to the growing pool of ontologies. There are many barriers that prevent domain experts engaging in the ontology development process and novel tools are needed to break down these barriers to engage a wider community of scientists. RESULTS: We present Populous, a tool for gathering content with which to construct an ontology. Domain experts need to add content, that is often repetitive in its form, but without having to tackle the underlying ontological representation. Populous presents users with a table based form in which columns are constrained to take values from particular ontologies. Populated tables are mapped to patterns that can then be used to automatically generate the ontology's content. These forms can be exported as spreadsheets, providing an interface that is much more familiar to many biologists. CONCLUSIONS: Populous's contribution is in the knowledge gathering stage of ontology development; it separates knowledge gathering from the conceptualisation and axiomatisation, as well as separating the user from the standard ontology authoring environments. Populous is by no means a replacement for standard ontology editing tools, but instead provides a useful platform for engaging a wider community of scientists in the mass production of ontology content.

Authors: Simon Jupp, Matthew Horridge, Luigi Iannone, Julie Klein, , Joost Schanstra, , Robert Stevens

Date Published: 25th Jan 2012

Publication Type: Not specified

Abstract (Expand)

MOTIVATION: In the Life Sciences, guidelines, checklists and ontologies describing what metadata is required for the interpretation and reuse of experimental data are emerging. Data producers, however, may have little experience in the use of such standards and require tools to support this form of data annotation. RESULTS: RightField is an open source application that provides a mechanism for embedding ontology annotation support for Life Science data in Excel spreadsheets. Individual cells, columns or rows can be restricted to particular ranges of allowed classes or instances from chosen ontologies. The RightField-enabled spreadsheet presents selected ontology terms to the users as a simple drop-down list, enabling scientists to consistently annotate their data. The result is 'semantic annotation by stealth', with an annotation process that is less error-prone, more efficient, and more consistent with community standards. AVAILABILITY AND IMPLEMENTATION: RightField is open source under a BSD license and freely available from http://www.rightfield.org.uk

Authors: , , Matthew Horridge, , , , ,

Date Published: 15th Jul 2011

Publication Type: Journal

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