BioAssay Research Database (BARD): chemical biology and probe-development enabled by structured metadata and result types.

BARD, the BioAssay Research Database (https://bard.nih.gov/) is a public database and suite of tools developed to provide access to bioassay data produced by the NIH Molecular Libraries Program (MLP). Data from 631 MLP projects were migrated to a new structured vocabulary designed to capture bioassay data in a formalized manner, with particular emphasis placed on the description of assay protocols. New data can be submitted to BARD with a user-friendly set of tools that assist in the creation of appropriately formatted datasets and assay definitions. Data published through the BARD application program interface (API) can be accessed by researchers using web-based query tools or a desktop client. Third-party developers wishing to create new tools can use the API to produce stand-alone tools or new plug-ins that can be integrated into BARD. The entire BARD suite of tools therefore supports three classes of researcher: those who wish to publish data, those who wish to mine data for testable hypotheses, and those in the developer community who wish to build tools that leverage this carefully curated chemical biology resource.

Habitat inventory at a regional scale: a comparison of estimates of terrestrial Broad Habitat cover from stratified sample field survey and full census field survey for Wales, UK.

Estimates of terrestrial Broad Habitat cover for Wales from the Countryside Survey 2000 stratified sample field mapping programme in Britain are compared with the findings of a full census field mapping project, the Habitat Survey of Wales. The Countryside Survey sampling regime comprised a stratified random sample of 1 km squares [corrected] covering <0.5% of the land surface. Comparative assessment indicates that although few of the sample-derived estimates for individual Broad Habitats are within 30% of the full census survey results, relative extents accord with data from the complete census survey for all Broad Habitats apart from Arable & Horticultural. The accuracy of this estimate is improved when the national boundary of Wales is taken into account in the sample stratification scheme. It is suggested that cultural land-use differences between countries render cropland habitat extent less predictable from physical environmental parameters than semi-natural habitat extent. It is also shown that the precision of sample-derived cover estimates is influenced by habitat pattern: the error term associated with habitats of broadly equal extent is greater for those with the most clumped distributions.

Repeatability of Phase 1 habitat survey.

As the major part of a Habitat Survey of Wales, over 80% of the land surface was surveyed in the field between 1987 and 1997 using the Phase 1 method. A resurvey of 294 randomly selected points was carried out during the early stages to audit the quality of the data being collected, leading to the development of a set of recommendations for the surveyors to improve the consistency and accuracy of habitat mapping. Recent studies have indicated a high level of discrepancy between organisations in field habitat mapping using the Phase 1 method. The findings of the Phase 1 audit in Wales are presented here to show the level of repeatability that was achieved within an organisation. There was 76% correspondence in habitat mapping between 'surveyor' and 'assessor' at the level of individual Phase 1 habitat classes. The degree of repeatability varied according to habitat strata: it was highest for modified land cover types (88%), lowest for semi-improved types (56%) and intermediate for semi-natural types (75%). An overall estimate of the repeatability of Phase 1 survey in the study area of 83% was obtained by weighting the figures for the three strata by the proportion of land area occupied by each stratum. This figure increased to 85% when habitats were amalgamated into Broad Habitat groups. These results are considerably better than those reported by studies of consistency between organisations. Most of the discrepancies between surveyor and assessor were caused by differences in habitat identification. However, at almost two thirds of the points where such a difference occurred, the assessor noted that the vegetation was transitional or borderline with that mapped by the surveyor.