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World Grass Species Databases (GrassBase)

Screenshots of the World Grass Species databases

The World Grass Species Databases (GrassBase) have been in development at Kew for over a decade.  These form a repository for species descriptive and synonymy data that aspires to be a global standard and aims to eventually contain a full World Flora of grasses.  The species descriptions are stored in the standard DELTA format and the synonymy database is a purpose designed Microsoft Access database.  The primary objective of this project is to further develop these databases and make them accessible to a broad audience through the World Wide Web.  The objectives include the incorporation of the synonymy data into the Monocot Checklist, development of an interactive key that will assist users with the identification of grasses worldwide.

The first ten months of the project have seen the release of 10,800 web pages (Annex 1) containing species descriptions in 1090 characters for almost all known grass species.  The interactive key associated with this data has been updated with new descriptions, and the synonymy database now provides a link to these species descriptions from the synonyms.  Interest in the database is growing and the data contained therein are being used as the basis of a number of regional Floral treatments and there is considerable interest in incorporating the descriptive data into large phylogenetic studies.

The synonymy database (Annex 2) is currently available for download over the internet.  During 2006 it will be incorporated into the Monocot Checklist database, along with data from collaborators in the USA.  Once within this framework it will form the basis of a tool whereby users can view up-to-date synonymy information, build checklists and link to species descriptions and further data.

The interactive key associated with the descriptive data will be vastly improved by the incorporation of specimen images and illustrations for a large proportion of the species within the database.  The quality of the data will be improved via a feedback mechanism through which users can submit corrections and additions to the database.

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