DataPool benefits-evidence table
JISC, funder of DataPool, of other projects in research data management, and many more projects on widening use of digital technology in education, tends to focus on areas close to practical exploitation. On the R&D spectrum, it is typically towards the development end. For project managers, therefore, there is an emphasis on procedures and tools to increase the impact of practical outcomes – evaluation, sustainability, exit strategies, technology transfer, etc.
Another planning tool being adopted in the Managing Research Data Programme (MRD) 2011-13, of which DataPool is a part, is benefits-evidence analysis. As this description suggests, the idea is to elaborate prospective benefits of a project, and then identify the evidence that will demonstrate whether or not the benefit has been realised. It is as much about informing the process of getting to the results, and identifying which results are important and achievable, as the results themselves.
Hence, JISC MRD projects were invited to Bristol for a 2-day programme workshop at the end of November to present their benefits-evidence slides. If this sounds a little repetitive, it is but not uninteresting, especially as in preparing for the workshop all projects had essentially to engage in the same analysis, and were therefore armed not just with their own slide but ready to comment on others.
For project managers used to working towards outputs (products or services arising from the project) and outcomes (effects of the outputs on users in the target community), benefits are another factor. Hence, the JISC MRD programme has recruited a team of evidence gatherers, to work with and assist projects to hone and refine the benefits they are working towards and the consequent evidence measures. “Those are more outputs than benefits” I was advised, fairly, during open discussion on some ‘benefits’ in my slide. But then I had seeded the slide with points to discuss rather than a definitive list, and unwittingly extended the project’s previously discussed benefits.
So after the workshop I was grateful for the advice of Laura Molloy, evidence gatherer for DataPool, on aligning our pre- and post-workshop benefits lists.
After all that effort it would be a remiss not to reveal our benefits-evidence table that emerged from the process. For the record, here are the benefits DataPool will seek to demonstrate in its final months into early 2013.
DataPool: Benefits-Evidence
| 1 Improved RDM skills across the target community, including researchers and professional support staff | Qual reporting on effectiveness of training events. Feedback from training courses and deskside consultations, DMP and email help services. More staff running RDM support services, increased service offer. |
| 2 Greater visibility and use of institution’s research data / research outputs through sharing, collaboration, reuse | Qual case study describing improved dataset exposure. Qual evidence of DMP engagement, including early indications of access routes. * Quant indication of increase in dataset downloads. No. of datasets stored in data repository. Accesses of open datasets vs closed datasets vs shared datasets. |
| 3 Sustained institutional support for RDM / sustainability for RDM infrastructure at institution | No. of training opportunities introduced. Scope of: deskside consultations, DMP support service. Results from case studies – engagement with existing data facilities. Assessment of added value for institution of using institutional storage over other options – report. |
| 4 Improved use/uptake of RDM infrastructure | Quant account of ‘bid preparation consultations’, inc. qual narrative of referrals to data policy and DMP help. Case study on working with data policy – feedback on uptake of policy. Quant tracking of higher attendance at training. Accesses to RDM guidance documents. No. of deskside consultations. * Quant indication of improved uptake of institutional storage and deposit options. No. of large data projects switching to institutional data service. |
| 5 Time / costs saved by improved RDM infrastructure | Identifying early cost-benefits – combined case studies report, inc large data projects, open data, imaging, disciplinary efficiencies. Assessment of added value for institution of using institutional storage over other options – report (see 3). |
* This evidence not expected to be available during DataPool Project, following launch of RDM repository service by project end, but will be collected in ongoing work at Southampton University on institutional RDM. Table by Steve Hitchcock for DataPool, in collaboration with Wendy White, Dorothy Byatt. We gratefully acknowledge the feedback and suggestions from Laura Molloy, JISC evidence gatherer.
The University of Southampton has a 10 year roadmap for research data, of which DataPool represents the first stretch of road, so there is a commitment to go further, but the clearer the steer from DataPool the faster the progress afterwards.
As a little light relief from projects’ benefits-evidence slides, a presentation on the Southampton roadmap and business plan was given at the Bristol workshop. That will be covered in a separate post.
How will you know which benefits have been achieved as the project moves forward? This post is tagged with the label ‘benefits’. All updates reporting evidence from the table above will use this tag. Tags can be found in the column immediately to the right of this one, and up, from this point in the post.
This is how other JISC MRD projects are tackling these challenges and what benefits-evidence are being targetting:
- Benefits of Research360, University of Bath
- Benefits and evidence, Research Data @Essex
- JISCMRD Benefits & Evidence WS, MiSS Project, University of Manchester