What is Research Data?
Providing a single, authoritative definition of research data in the visual arts is challenging.
Research data could be described as: "data which arises out of, and evidences, research...examples of visual arts research data may include sketchbooks, log books, sets of images, video recordings, trials, prototypes, ceramic glaze recipes, found objects, and correspondence (Garrett and Gramstadt, 2012)."
Research data may also be defined as: "evidence which is used or created to generate new knowledge and interpretations. 'Evidence' may be intersubjective or subjective; physical or emotional; persistent or ephemeral; personal or public; explicit or tacit; and is consciously or unconsciously referenced by the researcher at some point during the course of their research. As part of the research process, research data may be collated in a structured way to create a dataset to substantiate a particular interpretation, analysis or argument. A dataset may or may not lead to a research output, which regardless of method of presentation, is a planned public statement of new knowledge or interpretation (Garrett, 2012)."
For a further exploration of the meaning of research data in the visual arts, see the following toolkit: Introduction to Research Data.
Why is Research Data Management (RDM) important?
Managing research data (or organising your 'stuff') effectively can:
- ensure you meet research funder expectations (See the Research Councils UK Common Principles on Data Policy)
- make it easier to understand successive iterations of your research
- make it easier to re-visit your research if changes are required, for example by a journal editor or exhibition curator
- enable easier access to your research for re-use in other projects
- avoid the serious implications of having to re-do your research from scratch, for example due to data loss or inaccessible data
For some suggestions about how to make the organisation process more effective, see the following toolkit:
Research Data Management Planning.
