Demo Data from EDBT 2026 / reviewers in the wild / expert
Chris F. Taylor
dblp:07/414
· DBLP profile ↗
5ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 5
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Bioinformatics and computational biology · 78% Computational science and engineering · 22% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational science and engineering › scientific data management
data standards |
0.1 | 1 | 2006 | The MGED Ontology: a resource for semantics-based description of microarray experiments · Bioinform. 2006 |
Bioinformatics and computational biology › ontology
ontology development |
0.1 | 1 | 2006 | The MGED Ontology: a resource for semantics-based description of microarray experiments · Bioinform. 2006 |
Methods — techniques the papers use, named apart from their topics
ontology-based annotation · 0.1checklist management · 0.1ontology engineering · 0.1controlled vocabulary · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community levelabstractUNLABELLED: The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies; (ii) empowers users to uptake community-defined checklists and ontologies; and (iii) facilitates submission to international public repositories. AVAILABILITY AND IMPLEMENTATION: Software, documentation, case studies and implementations at http://www.isa-tools.org. Philippe Rocca-Serra, Marco Brandizi, Eamonn Maguire, Nataliya Sklyar, Chris F. Taylor, Kimberly Begley, Dawn Field, Stephen C. Harris, Winston Hide, Oliver Hofmann 0001, Steffen Neumann, Peter Sterk, Weida Tong, Susanna-Assunta Sansone |
Bioinform. | 5 |
| 2009 | Survey-based naming conventions for use in OBO Foundry ontology developmentabstractBACKGROUND: A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. RESULTS: We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. CONCLUSION: Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data. Daniel Schober, Barry Smith 0001, Suzanna Lewis, Waclaw Kusnierczyk, Jane Lomax, Chris Mungall, Chris F. Taylor, Philippe Rocca-Serra, Susanna-Assunta Sansone |
BMC Bioinform. | 7 |
| 2006 | The MGED Ontology: a resource for semantics-based description of microarray experimentsabstractMOTIVATION: The generation of large amounts of microarray data and the need to share these data bring challenges for both data management and annotation and highlights the need for standards. MIAME specifies the minimum information needed to describe a microarray experiment and the Microarray Gene Expression Object Model (MAGE-OM) and resulting MAGE-ML provide a mechanism to standardize data representation for data exchange, however a common terminology for data annotation is needed to support these standards. RESULTS: Here we describe the MGED Ontology (MO) developed by the Ontology Working Group of the Microarray Gene Expression Data (MGED) Society. The MO provides terms for annotating all aspects of a microarray experiment from the design of the experiment and array layout, through to the preparation of the biological sample and the protocols used to hybridize the RNA and analyze the data. The MO was developed to provide terms for annotating experiments in line with the MIAME guidelines, i.e. to provide the semantics to describe a microarray experiment according to the concepts specified in MIAME. The MO does not attempt to incorporate terms from existing ontologies, e.g. those that deal with anatomical parts or developmental stages terms, but provides a framework to reference terms in other ontologies and therefore facilitates the use of ontologies in microarray data annotation. AVAILABILITY: The MGED Ontology version.1.2.0 is available as a file in both DAML and OWL formats at http://mged.sourceforge.net/ontologies/index.php. Release notes and annotation examples are provided. The MO is also provided via the NCICB's Enterprise Vocabulary System (http://nciterms.nci.nih.gov/NCIBrowser/Dictionary.do). CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Patricia L. Whetzel, Helen E. Parkinson, Helen C. Causton, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Laurence Game, Mervi Heiskanen, Norman Morrison, Philippe Rocca-Serra, Susanna-Assunta Sansone, Chris F. Taylor, Joseph White, Christian J. Stoeckert Jr. |
Bioinform. | 12 |
| 2006 | The use of concept maps during knowledge elicitation in ontology development processes - the nutrigenomics use caseabstractBACKGROUND: Incorporation of ontologies into annotations has enabled 'semantic integration' of complex data, making explicit the knowledge within a certain field. One of the major bottlenecks in developing bio-ontologies is the lack of a unified methodology. Different methodologies have been proposed for different scenarios, but there is no agreed-upon standard methodology for building ontologies. The involvement of geographically distributed domain experts, the need for domain experts to lead the design process, the application of the ontologies and the life cycles of bio-ontologies are amongst the features not considered by previously proposed methodologies. RESULTS: Here, we present a methodology for developing ontologies within the biological domain. We describe our scenario, competency questions, results and milestones for each methodological stage. We introduce the use of concept maps during knowledge acquisition phases as a feasible transition between domain expert and knowledge engineer. CONCLUSION: The contributions of this paper are the thorough description of the steps we suggest when building an ontology, example use of concept maps, consideration of applicability to the development of lower-level ontologies and application to decentralised environments. We have found that within our scenario conceptual maps played an important role in the development process. Alexander García Castro, Philippe Rocca-Serra, Robert Stevens 0001, Chris F. Taylor, Karim Nashar, Mark A. Ragan, Susanna-Assunta Sansone |
BMC Bioinform. | 4 |
| 2004 | Pedro: a configurable data entry tool for XMLabstractUNLABELLED: Pedro is a Java application that dynamically generates data entry forms for data models expressed in XML Schema, producing XML data files that validate against this schema. The software uses an intuitive tree-based navigation system, can supply context-sensitive help to users and features a sophisticated interface for populating data fields with terms from controlled vocabularies. The software also has the ability to import records from tab delimited text files and features various validation routines. AVAILABILITY: The application, source code, example models from several domains and tutorials can be downloaded from http://pedro.man.ac.uk/. Kevin L. Garwood, Chris F. Taylor, Kai J. Runte, Andy Brass, Stephen G. Oliver, Norman W. Paton |
Bioinform. | 2 |