Future agenda: repositories, and the research process
2 likes401 views
This document discusses research data management in the context of non-standard archiving of research outputs, with a focus on challenges in the arts and humanities. It notes that while data reuse has long been integral to various creative disciplines, archiving creative research data presents unique issues not present in scientific disciplines. These include the personal nature of creative works, differentiating between research and personal works, issues with non-digital materials, and the blurry boundaries of creative research processes. The document raises questions around concepts like evidence, facts, and replication in subjective creative research.
![ Definitions vary from discipline to discipline, and from funder to funder…
Here’s a science-centric definition:
“The recorded factual material commonly accepted in the scientific community as
necessary to validate research findings.” (US Office of Management and Budget,
Circular 110)
[Addendum: This policy applies to scientific collections, known in some disciplines
as institutional collections, permanent collections, archival collections, museum
collections, or voucher collections, which are assets with long-term scientific value.
(US Office of Science and Technology Policy, Memorandum, 20 March 2014)]
And another from the visual arts:
“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.”
(Leigh Garrett, KAPTUR project: see http://kaptur.wordpress.com/
2013/01/23/what-is-visual-arts-research-data-revisited/)
So what is ‘data’ exactly?](https://image.slidesharecdn.com/mdslidesnottingham-140514045603-phpapp02/85/Future-agenda-repositories-and-the-research-process-7-320.jpg)
Future agenda: repositories, and the research process
- 1. Non-Standard Archiving of Research Outputs Workshop Future agenda: repositories, and the research process Tom Phillips, A Humument (1970, 1986, 1998, 2004, 2012…) Martin Donnelly, Digital Curation Centre, University of Edinburgh Nottingham Trent University, 13 May 2014
- 2. What is research data management? “the active management and appraisal of data over the lifecycle of scholarly and scientific interest” Data management is a part of good research practice. - RCUK Policy and Code of Conduct on the Governance of Good Research Conduct
- 3. The old way of doing (science) 1. Researcher collects data (information) 2. Researcher interprets/synthesises data 3. Researcher writes paper based on data 4. Paper is published (and preserved) 5. Data is left to benign neglect, and eventually ceases to be accessible
- 4. The new way of doing (science) Plan Collect Assure Describe Preserve Discover Integrate Analyze SHARE …and RE-USE The DataONE lifecycle model
- 5. Other models are available… Ellyn Montgomery, US Geological Survey
- 6. Drivers and benefits of RDM TRANSPARENCY: The evidence that underpins research can be made open for anyone to scrutinise, and attempt to replicate the findings of others. EFFICIENCY: Data collection can be funded once, and used many times for a variety of purposes. RISK MANAGEMENT: A pro-active approach to data management reduces the risk of inappropriate disclosure of sensitive data, whether commercial or personal. PRESERVATION: Lots of data is unique, and can only be captured once. If lost, it can’t be replaced.
- 7. Definitions vary from discipline to discipline, and from funder to funder… Here’s a science-centric definition: “The recorded factual material commonly accepted in the scientific community as necessary to validate research findings.” (US Office of Management and Budget, Circular 110) [Addendum: This policy applies to scientific collections, known in some disciplines as institutional collections, permanent collections, archival collections, museum collections, or voucher collections, which are assets with long-term scientific value. (US Office of Science and Technology Policy, Memorandum, 20 March 2014)] And another from the visual arts: “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.” (Leigh Garrett, KAPTUR project: see http://kaptur.wordpress.com/ 2013/01/23/what-is-visual-arts-research-data-revisited/) So what is ‘data’ exactly?
- 8. Scientific and other methods… The scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry must be based on empirical and measurable evidence subject to specific principles of reasoning. The Oxford English Dictionary defines the scientific method as: “a method or procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses.” Source: http://en.wikipedia.org/wiki/Scientific_method An art methodology differs from a science methodology, perhaps mainly insofar as the artist is not always after the same goal as the scientist. In art it is not necessarily all about establishing the exact truth so much as making the most effective form (painting, drawing, poem, novel, performance, sculpture, video, etc.) through which ideas, feelings, perceptions can be communicated to a public. With this purpose in mind, some artists will exhibit preliminary sketches and notes which were part of the process leading to the creation of a work. Sometimes, in Conceptual art, the preliminary process is the only part of the work which is exhibited, with no visible end result displayed. In such a case the "journey" is being presented as more important than the destination. Source: http://en.wikipedia.org/wiki/Art_methodology
- 9. There’s nothing new about data re-use in the Arts and Humanities; it’s an integral part of the culture, and always has been… Think Kristeva’s intertextuality, Barthes’ ‘galaxy of signifiers’, Shakespeare’s plots, Lanark’s assorted ‘plagiarisms’, Edwin Morgan’s ‘found’ newspaper poems, Marcel Duchamp, variations on a theme, collage and intermedia art, T.S. Eliot, sampling/hip-hop, etc etc (http://www.slideshare.net/martindonnelly/data-reuse-in-the-arts) However, it’s often more fraught than data re-use in other areas (such as the Sciences) For starters, people tend not to think of their sources or influences as ‘data’, and the value and referencing systems are quite different Furthermore, practice/praxis based research is pretty much the sole preserve of the Humanities, and research/production methods are not always rigorously methodical or linear… Strengths and weaknesses re. data in the Arts and Humanities
- 10. Some characteristics of Arts and Humanities data are likely to require a different kind of handling from that afforded to other disciplines Arts ‘data’ is often personal, and creative data in particular may not be factual in nature. Furthermore, it may be quite valuable or precious to its creator. What matters most may not be the content itself, but rather the presentation, the arrangement, the quality of expression… This tends to be why Open Access embargoes are often longer in the Arts and Humanities than other areas Digital ‘data’ emerging in the Arts is as likely to be an outcome of the creative research process as an input to a workflow. This is at odds with the scientific method, and how most RDM resources are described. Problems re. data in the Arts and Humanities
- 11. Are the goals – or indeed the concepts – of evidence, facts, validation, replication still central in disciplines reliant on subjectivity, interpretation, argument and qualities of expression? How do we identify, preserve and share ephemera, emotions, the unconscious…? How do we protect rights around creative data? What are the financial/ ownership issues accompanying creative / Arts research? Is it clear where creative research begins and ends? How can we differentiate between funded research and unfunded personal work? What complexities are introduced by practice-driven research? To what extent is non-digital material a problem? Can we share approaches to this with other subject areas (e.g. biology, geology)? What other characteristics do Arts and Humanities data have in common with those of the Sciences? Which other disciplines share these issues more generally? A few questions around data in the Arts and Humanities
- 12. Business case (“could anyone die?”) Retention and embargo periods Scope Respect des fonds? Scale Multiplicity of (file) formats and creation/storage media Linking analogue and digital, structuring collections Commercial considerations and IPR… personal data? Access arrangements / digitisation Metadata (NISO): descriptive (for discovery), administrative (for reuse), structural (for inter-relating objects) – obviously this also costs money… Archiving issues around Arts and Humanities data
- 13. Need – what do we need to archive? Is it evidence without which the research outcomes are in doubt? Want – do we want to archive materials for other reasons? Does preserving preparatory/developmental work provide a richer experience/understanding of the creative work and process? How do we make a business case for this? Liminality Many creative researchers are on fractional contracts, and there is not always a clear delineation between professional work and personal practice. Where and how do we locate the line? More practically, the same notebook or sketchbook may be used for both professional and personal purposes. Its contents may be messy, personal, confusing. Is an artwork ever finished, or just abandoned? (c.f. Paul Valéry) How do we know? Sometimes the demo version is better… Possible discussion points