OAR conference notes – Andrew Treloar

Dr Andrew Treloar – ANDS Establishment Project

Blue print for ANDS = Towards the Australian Data Commons (TADC) – developed during 2007 by ANDS Technical Working Group

TADC: Why data? Why now? – increasing data-intensive research; almost all data is now born digital; “Consequently, increasingly effort and therefore funding will necessarily be diverted to data and data management over time”

TADC: Role of data federations – with more data online, more can be done; increasing focus on cross-disciplinary science

Changing Data, Changing Research – e.g. Hubble data has to be released 6 months after creation

ANDS Goal = to deliver greater access, easier and more effective data use and reuse

ANDS Implementation assumptions:

  • ANDS doesn’t have enough money to fund storage, and so is predicated on institutionally supported solutions
  • Not all data shared by ANDS will be open
  • ANDS aims to leverage existing activity, and coordinate/fund new activity
  • ANDS will only start to build the Australian Data Commons
  • ANDS governance and management arrangements are sized for the current funding

Realising the goal – need to:

  • Seed the commons by connecting existing stores
  • Increase (human) capability across the sector in data management and integration

ANDS structure = four programs:

  1. Developing Frameworks (Monash) – about policies, national understandings of data management, and research intensive organisations = assisting OA by encouraging moves in favour of discipline-acceptable default data sharing practices
  2. Providing Utilities (ANU) – Services Roadmap, national discovery service, collection registry, persistent identifier minting and management = assisting OA by improving discoverability particularly across disciplines (ISO2146)
  3. Seeding the Commons (Monash) – recruit data into the research data commons = assisting OA by increasing the amount of content available, much of it (hopefully) OA
  4. Building Capabilities (ANU) – improving human capability for research data management and research access to data – esp. early career researchers teaching them good data management practices from the beginning = assisting OA by advocating to researchers for changed practices