The Internet now connects data, compute resources and software from globally distributed resources in real time. Where on planet Earth these resources are geographically located is irrelevant, but to enable online access to them, there is a rising need for programmatic access to both data, and to software to process data across institutional, domain and national boundaries. This requires the development of standardized machine-to-machine interfaces that can loosely couple data and software through agreed formats, interfaces, vocabularies and ontologies, preferably across multiple domains. The complexity of these online infrastructures require that they are built by much wider communities, through effective cooperation and governance, to enable new and innovative forms of interdisciplinary science from globally accessible data stores.
Community efforts are springing up everywhere, both within and across many scientific domains. These communities have similar goals and host parallel working groups that support the mission of advancing scientific research through data interoperability. There is great diversity in the maturity of these organizations and it is clear that there is much to be learned from and with each other to improve coordination and avoid duplication of effort.
Scholarly communication defined by Sloan includes ‘engaging the emerging community of stakeholders and practitioners tackling similar issues’. The time is ripe for identifying the key communities and partnerships within the major scientific domains that are developing infrastructures that enable sharing and processing of scientific data and ‘mapping the landscape’ of these activities to further improve collaborations and partnerships, particularly those ‘umbrella’ alliances that are enabling interdisciplinary data sharing.
Already mapping the landscape exercises are starting to be undertaken because the duplication is becoming increasingly obvious (if not embarrassingly so!). Of particular interest is a tool developed by Dawn Wright of ESRI that was used by EarthCube to map the location of, and types of communities within EarthCube (http://dusk.geo.orst.edu/ec-story)
This BoF is about establishing whether it is felt that there is a need to do a Mapping the Landscape exercise for the major data infrastructure building activities within and beyond RDA.
The BoF initially emerged at P8 through the discussion available here (see presentation files attached): https://www.rd-alliance.org/mapping-landscape-global-collaborations-building-data-infrastructures-rda-8th-plenary-bof-meeting
11th Plenary Interest Group Berlin: Mapping Even More Landscapes: Examining More Tools and Supporting ‘Legends'
10th Plenary IG Montreal: Mapping the Landscape mini Summit: consolidated knowledge of all data organizations
9th Plenary IG Barcelona: Formalising the Mapping of the Landscape Interest Group and Scoping Activities
8th Plenary BoF Denver: Mapping the Landscape of Global Collaborations in Building Data Infrastructures