Data management planning

Means, goals, and cultures

Hugo Besemer

Library Wageningen UR

Data management and

Wageningen

Data management planning course for PhD candidates since 2012

Data management plans mandatory for PhD projects and research groups since April 2014

Policy supported by

● “Support hub” for all questions

● Facilities for data publishing

● Code repository

Still working on• Storage

“archiving”• Electronic

laboratory notebooks

• Guidelines for ownership

Institutional data management

planning

Who benefits?

● Policy makers: there is a policy

● PhD researchers are empowered to get answers from their supervisors

● Research groups can sort out procedures and learn across groups

What is needed

● People’s and organizational dynamics (that’s different everywhere)

● Develop a common language!

Two cultures

“A good many times I have been present at gatherings of people

who, by the standards of the traditional culture, are thought

highly educated and who have with considerable gusto been

expressing their incredulity at the illiteracy of scientists. Once or

twice I have been provoked and have asked the company how

many of them could describe the Second Law of

Thermodynamics. The response was cold: it was also negative.

Yet I was asking something which is the scientific equivalent of:

Have you read a work of Shakespeare's?”

C. P. Snow, 1959 Rede Lecture entitled "The Two Cultures and

the Scientific Revolution".

Two cultures: Time is moving on

Lord Snow

● Literary intellectuals

● Natural scientists

Many aginfo meetings

● Knowledge managers

● Techies

What I am experiencing now

● Infrastructure builders

● Empirical scientists

Bemoaning a glorious past

Promises of a brave new world

Promises of a brave new world

Pressed for funding

Different meanings: Data

Infrastructure builders

● Data is the evidence that supports a truth claim. It can be copied to different physical locations, be reformatted - and even be “triplified” or “SKOSified” :=) - and remain itself

Empirical scientists

● Data resides somewhere and comes in a specific “physical” format.

Beyond data: Metadata

Infrastructure builders

● Data about data, to identify or to describe the data and its context

Empirical scientists

● Anything goes: templates, parameters used, data models, laboratory notes, annotations

Data management roles

Infrastructure builders:

● Scientists sit on their data and should be convinced to deposit it in a repository with an open licence

Empirical scientists

● Data is often produced in chains under informal agreements

Data documentation

Infrastructure builders

● Documenting a static dataset at project, file and parameter level

Empirical scientists

● May include laboratory notes etc. during research

● Parameters / variables are an issue!

Storage, archiving

and data publishing

Infrastructure builders

● Fluid terminology

Empirical scientists

● Storage is for daily use during research

● Archiving can be for data that you may want to use at a later stage (e.g. year 1 when you are in year 3) – so no daily backup or fast access required

● People like “data publishing” for datasets deposited in repositories

Legal issues

Infrastructure builders

● Open licenses for data re-use

Empirical scientists

● Agreements between actors in the data chain (students – researchers – supervisors – external parties)

● Interested in open licenses, also as consumers

What about IGAD?

Messages for the discussion on institutional issues

If we want to address institutional issues we need to be aware of different cultures and languages

I did not mention anything specifically agricultural

● but that does not imply that there are no specific institutional issues

For us things started with learning and training activities…..

Thanks

http://www.slideshare.net/HugoBesemer