The University of Melbourne
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HASS Data Curation Framework (DCF)

online resource
posted on 2020-11-02, 05:26 authored by Mike JonesMike Jones, Joanne Mihelcic

The final report product of an investigation into data curation requirements with data custodians and Humanities Arts and Social Science (HASS) researchers. The Tinker (HASS DEVL) Project began with a scoping study, identifying existing frameworks and principles, and developing a high-level Data Curation Framework to test with experts around Australia. Also attached is an excerpt of a deeper case study into two significant research collections which informed and complimented the DCF.

Elements of this work became the focus for round table discussions, held in Melbourne, Brisbane, and Adelaide. These invaluable sessions provided an opportunity to talk about the concept of "data curation", existing frameworks, and gaps in existing resources. The discussions also aimed to find out more about what a HASS data curation framework contains, and how it should be represented to potential users. Findings from the workshops are available here.

Building on data curation capability for HASS the activity was viewed as an ongoing process. These first steps are considered foundations to be continued, that can aid in connecting existing resources through key data curation concepts, to provide case studies and other material to help make collections of data more usable, interoperable, and sustainable. The DCF aims to provide:

• A clear common language:

- shared understanding between collaborators/custodians

- to work through the challenges associated with data curation

- consistent means for describing curation that has been applied

- conceptual model to understand tools, standards, systems, processes to improve DC

- conceptual lens to explore gaps

- towards HASS data increasingly accessible, understandable, and usable over time

• Specifically for HASS researchers, research teams, and other custodians responsible – for the curation of reference datasets, of current or ongoing value.

• To help researchers and data custodians understand, evaluate, and apply these existing standards and policies more effectively.




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