RDM Principles: Scope

I’m working on adding more practical advice the underpin the University of Leicester Research Data Management Principles.

These start:

The University regards research data as a valuable asset. The management of research data is an integral part of good research practice that allows reliable verification of results, protects the intellectual and financial investment made in its creation, enables it to be shared and prompts new and innovative research.

I’d like these words to be written & read, spoken & heard so they become meaningful to everyone involved with discovery.

The first principle defines Scope:

1. These principles apply to all research conducted at the University, regardless of funding source. They do not imply additional compliance where good practice and relevant research funders’ requirements are already being followed.

In all of my Open Access work I think it is vital to take a researcher centred approach rather than my colleagues feeling imposed upon in some faceless way which could feel like unnecessary bureaucracy or unsympathetic to their specialist workflows. I think in this fledgling state of open scholarship I would do well to identify and lower any barriers perceived by our users. At the same time, we are taking a shared approach as an institution.

My job is about supporting researchers, streamlining professional tasks, selling the benefits of open scholarship and making sure we deliver tangible benefits, not just hype. We are building for the future and some aspirations won’t be delivered immediately and may be changed. Also, some researchers are already doing Open Scholarship and we can highlight their work and learn from them.

I expect we will support people at different levels of abstraction – from overviews for strategic management through project level approaches to working with researchers looking to usefully describe a particular dataset. We will be working with researchers in many fields and many interdisciplinary groups. We will be working with people a different stages of projects. Our task is to get useful information for each researcher – not too much nor too little.

In this first principle I think we are:

• Including pretty much all researchers. Colleagues in some fields may not feel they are working with research data at all. However, in observing the universe and creating the structure of knowledge many researchers do produce material that could be useful to others. We need many subject specific examples from actual research: perhaps drafts showing the process of creating prose,  interview transcripts, comment on photographs, lab book notes, computer model parameters etc.

• Our document has: Research data are defined as any material created or collected for the purposes of analysis to generate and validate original research results, irrespective of the format of data. Research data may be digital, paper based or in other forms. Examples of different types of research data include datasets, images, text (such as transcripts of interviews), audio and video recordings, computer scripts.

• Including all funders: ensuring funders see professionals supported by competitive research infrastructure for open scholarship. This can include internal sources of funding.
• Reassuring researchers this isn’t an extra compliance burden from their employer. Researchers already understand their own data. We can link to the requirements of funders and I think why the funders are moving to Open Scholarship: the benefits to researchers and to the world.

What do we mean by “good practice”? Hmmm!

UK Data Archive have best practice for researchers revised May 2011. I find the language at UK Data Archive: Planning for Sharing pretty clear though I don’t know yet how applicable it would be outside ESRC fields.