A sea of standards for -omics (‘genomics,’ ‘proteomics’ or ‘metabolomics’) data: sink or swim?

http://jamia.bmj.com/content/early/2013/10/03/amiajnl-2013-002066.long / http://jamia.bmj.com/content/21/2/193.full.pdf+html

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Abstract

In the era of big data, omic-scale technologies, and increasing calls for data sharing, it is generally agreed that the use of community-developed, open data standards is critical. Far less agreed upon is exactly which data standards should be used, the criteria by which one should choose a standard, or even what constitutes a data standard. It is impossible simply to choose a domain and have it naturally follow which data standards should be used in all cases. The ‘right’ standards to use is often dependent on the use case scenarios for a given project. Potential downstream applications for the data, however, may not always be apparent at the time the data are generated. Similarly, technology evolves, adding further complexity. Would-be standards adopters must strike a balance between planning for the future and minimizing the burden of compliance. Better tools and resources are required to help guide this balancing act.

… the Pistoia Alliance (http://www.pistoiaalliance.org) and DRYAD,15 among others.16–18 At the national level in the USA, the data sharing trend is reflected in programs such as the National Institutes of Health’s (NIH) recently announced ‘big data to knowledge’ (BD2K) initiative,19 and the White House office of science and technology policy’s recent directive that the results of government-funded research be made publicly available.20 The Innovative Medicines Initiative (http://www.imi.europa.eu/) is Europe’s largest public–private initiative that supports collaborative research projects and builds networks of industrial and academic experts in order to boost pharmaceutical innovation in Europe. Internationally, the Research Data Alliance (https://rd-alliance.org/) has been established by an international steering group from funding agencies in the USA, EU and Australia; and recently the global alliance for genomic and clinical data sharing has brought together over 70 leading healthcare, research, and disease advocacy organizations, involving researchers from more than 40 countries, to enable secure sharing of genomic and clinical data.21 …

What is a data standard?

The International Organization for Standardization defines a standard as ‘…a document that provides requirements, specifications, guidelines or characteristics that can be used consistently to ensure that materials, products, processes and services are fit for their purpose’.27 Standards range from de jure, that is, ordained by some official organization such as the International Organization for Standardization or the American National Standards Institute, to de facto, that is, developed by grass-root initiatives and commonly adopted, but not prescribed by an official or specific authority. The BioSharing registry (http://biosharing.org/) houses a fairly comprehensive, curated list of data standards (primarily de facto) in the life science, environmental, and biomedical space. These standards are divided into three categories.

First, content standards take the form of reporting guidelines, for example, minimum information checklists. These vary from general guidance to itemized prescriptions of the information that should be provided (ie, curation guidelines), including both data and metadata.

The second category consists of syntax standards in the form of representations and formats that facilitate the exchange of information. These fall broadly into two types: delimited text, or a ‘markup language’ such as XML.

Third are the semantic standards in the form of terminology artifacts, such as controlled vocabularies or ontologies. These add an interpretive layer to the data by defining the concepts or terms in a domain, and in some cases the relationships between them. …

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