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The Minimum Information for Biological and Biomedical Investigations (MIBBI) project provides a resource for those exploring the range of extant minimum information checklists and fosters coordinated development of such checklists.

The Genomic Contextual Data Markup Language (GCDML) is a core project of the Genomic Standards Consortium (GSC) that implements the "Minimum Information about a Genome Sequence" (MIGS) specification and its extension, the "Minimum Information about a Metagenome Sequence" (MIMS). GCDML is an XML Schema for generating MIGS/MIMS compliant reports for data entry, exchange, and storage. When mature, this sample-centric, strongly-typed schema will provide a diverse set of descriptors for describing the exact origin and processing of a biological sample, from sampling to sequencing, and subsequent analysis. Here we describe the need for such a project, outline design principles required to support the project, and make an open call for participation in defining the future content of GCDML. GCDML is freely available, and can be downloaded, along with documentation, from the GSC Web site (http://gensc.org).

Purpose – Citation data needs to be recognised as a part of the Commons – those works that are freely and legally available for sharing – and placed in an open repository. The paper aims to discuss this issue. Design/methodology/approach – The Open Citation Corpus is a new open repository of scholarly citation data, made available under a Creative Commons CC0 1.0 public domain dedication and encoded as Open Linked Data using the SPAR Ontologies. Findings – The Open Citation Corpus presently provides open access (OA) to reference lists from 204,637 articles from the OA Subset of PubMed Central, containing 6,325,178 individual references to 3,373,961 unique papers. Originality/value – Scholars, publishers and institutions may freely build upon, enhance and reuse the open citation data for any purpose, without restriction under copyright or database law.

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the "semantic glue" to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans.

A database has been created, http://www.FishPathogens.eu, with the aim of providing a single repository for collating important information on significant pathogens of aquaculture, relevant to their control and management. This database will be developed, maintained and managed as part of the European Community Reference Laboratory for Fish Diseases function. This concept has been initially developed for viral haemorrhagic septicaemia virus and will be extended in future to include information on other significant aquaculture pathogens. Information included for each isolate comprises sequence, geographical origin, host origin and useful key literature. Various search mechanisms make it easy to find specific groups of isolates. Search results can be presented in several different ways including table‐based, map‐based and graph‐based outputs. When retrieving sequences, the user is given freedom to obtain data from any selected part of the genome of interest. The output of the sequence search can be readily retrieved as a FASTA file ready to be imported into a sequence alignment tool of choice, facilitating further molecular epidemiological study.

This meeting report summarizes the proceedings of the fifth Genomic Standards Consortium (GSC) workshop held December 12-14, 2007, at the European Bioinformatics Institute (EBI), Cambridge, UK. This fifth workshop served as a milestone event in the evolution of the GSC (launched in September 2005); the key outcome of the workshop was the finalization of a stable version of the MIGS specification (v2.0) for publication. This accomplishment enables, and also in some cases necessitates, downstream activities, which are described in the multiauthor, consensus-driven articles in this special issue of OMICS produced as a direct result of the workshop. This report briefly summarizes the workshop and overviews the special issue. In particular, it aims to explain how the various GSC-led projects are working together to help this community achieve its stated mission of further standardizing the descriptions of genomes and metagenomes and implementing improved mechanisms of data exchange and integration to enable more accurate comparative analyses. Further information about the GSC and its range of activities can be found at http://gensc.org.

Researchers working on environmentally relevant organisms, populations, and communities are increasingly turning to the application of OMICS technologies to answer fundamental questions about the natural world, how it changes over time, and how it is influenced by anthropogenic factors. In doing so, the need to capture meta-data that accurately describes the biological "source" material used in such experiments is growing in importance. Here, we provide an overview of the formation of the "Env" community of environmental OMICS researchers and its efforts at considering the meta-data capture needs of those working in environmental OMICS. Specifically, we discuss the development to date of the Env specification, an informal specification including descriptors related to geographic location, environment, organism relationship, and phenotype. We then describe its application to the description of environmental transcriptomic experiments and how we have used it to extend the Minimum Information About a Microarray Experiment (MIAME) data standard to create a domain-specific extension that we have termed MIAME/Env. Finally, we make an open call to the community for participation in the Env Community and its future activities.