Both the metagenomics and the biodiversity communities face a major challenge: capturing detailed data on the environmental and the ecological context from which samples are drawn. Without these 'metadata' (data about the primary, biological data), the value of the primary data is greatly diminished. To capture these different types of metadata, biologists/ecologists need tools that allow them to survey the literature in the relevant areas, identify the key concepts and vocabulary in the articles, and extract data and metadata into an appropriate representation for further processing, querying and exchange. The goal of this research is to create a proof-of-concept demonstration of interactive tools for the capture and curation of metadata, working in close collaboration with the metagenomics and biodiversity communities to understand their requirements. The text mining community has demonstrated significant progress: results from the recent BioCreative workshop (April 2007) show that text mining tools can identify mentions of key biological entities in running text and map these mentions to associated unique identifiers (e.g., Entrez Gene identifiers) at 80-90% accuracy. Much of this progress has been driven by a close association between curators of mature biological databases and the text mining community. Groups such as GOA, MINT, IntAct, Flybase, MGI, SGD, Wormbase have expert curators, a documented curation process, and they produce large quantities of expert curated data. These resources have provided good testbeds for evaluating new tools against human curated "gold standard" test sets. The question now is how to apply this progress to create tools to support curators in an interactive process for extraction and mapping of critical information, such as gene/protein identifiers, geospatial information, or habitat information. These tools will support emerging communities, such as the metagenomics and biodiversity communities; they also can be put into the hands of both ontology builders to speed design of ontologies, and authors for capture of metadata at the source, rather than relying on post-publication expert curation. This work will have impact in four distinct areas: first, it will support the metagenomics and biodiversity communities, to speed capture of metadata; second, it will provide new challenges to the text mining community, to integrate tools into an interactive pipeline to support real curation activities; furthermore, such interactive tools can have major impact on the ability to create new ontologies and controlled vocabularies, through exploration of concepts in the literature; and finally, such tools can provide a prototype for author-driven annotation, to support capture and encode metadata at the source, as a kind of "automated spell-checker" for annotations.
