Scratchpads: a data-publishing framework to build, share and manage information on the diversity of life.

Background: Natural History science is characterised by a single immense goal (to document, describe and synthesise all facets pertaining to the diversity of life) that can only be addressed through a seemingly infinite series of smaller studies. The discipline's failure to meaningfully connect these small studies with natural history's goal has made it hard to demonstrate the value of natural history to a wider scientific community. Digital technologies provide the means to bridge this gap.

Results: We describe the system architecture and template design of "Scratchpads", a data-publishing framework for groups of people to create their own social networks supporting natural history science. Scratchpads cater to the particular needs of individual research communities through a common database and system architecture. This is flexible and scalable enough to support multiple networks, each with its own choice of features, visual design, and constituent data. Our data model supports web services on standardised data elements that might be used by related initiatives such as GBIF and the Encyclopedia of Life. A Scratchpad allows users to organise data around user-defined or imported ontologies, including biological classifications. Automated semantic annotation and indexing is applied to all content, allowing users to navigate intuitively and curate diverse biological data, including content drawn from third party resources. A system of archiving citable pages allows stable referencing with unique identifiers and provides credit to contributors through normal citation processes.

Conclusion: Our framework http://scratchpads.eu/ currently serves more than 1,100 registered users across 100 sites, spanning academic, amateur and citizen-science audiences. These users have generated more than 130,000 nodes of content in the first two years of use. The template of our architecture may serve as a model to other research communities developing data publishing frameworks outside biodiversity research.