One of Copenhagen's bridges being opened, so we can sail through!
1. Funders and data policy
* Lots of interest in the data value checklist - compare UK and Australian data value checklist
* It's cheaper to keep data rather than recreate it
* Can you require open availability of data brought into a project? Case by case negotiation
* Multiple funders - which data policy will be applied?
* CODATA preparing a toolkit for funders about open data policy
* Role of institutional repositories? Data centres are good places to handle data pools
* Need clear metadata!
* How to handle data management plans once the project is over? Fund data management post-project. Should remain institutional responsibility.
* Identifiers - need researcher identifiers, funder acknowledgements, DOIs - all to pull together project information and data
* Are there international approached in data management plans?
2. Institutional policy
* Most institutions don't have a policy yet because they're not easy to create
* What other steps need to be done before policy?
* Hierarchy - who to get involved - academic champions
* Broad overview - what are the needs of researchers - don't want extra admin
* Don't contradict other policies or legislation
* Smaller institutions don't have monet or effort to get into big data infrastructures
* policy can guide researchers on what to do with their data
* What should be deposited, what should be kept
* How can we help insitutions develop data management plans?
* Guidelines on developing data management policies
* What kind of questions do we need to know before drafting policy?
3. Researchers and publishers
* Current examples are life and environmental sciences
* we need other examples in other fiels
* Researchers need acknowledgement for their work on data - not having it stops them shring
* Quality issues are important - need principles for peer review of research data
* Users of data are candidates to review it
* there are varying degrees of openness in peer-review - which will be appropriate for data?
* What stopes researchers sharing data? Quality, promotion, confidence in the value of the data
* We can give researchers more confidence in their data by promoting community standards
* Change beahviour so that data management is done every day, instead of just at the beginning and end of the project.
* Publishers can influence researchers when it comes to data management.
* Metrics are needed, data citation, but also alt.metrics
* Need for good examples of data management to educate researchers
* Need a list of trusted databases/repositories
* URLs aren't trusted, because they break!
* Finland is constructing a national data catalogue, containing a mix of metadata records and data
* OpenAIRE data model and services are using trust levels for entities and (automatic and man-made) relations
* Need to guarantee long term data availability for enhanced publications to be trustworthy, or at least know what bits will last for how long
* Level of trust needed to develop services to show levels of preservation
* Services should still exist for low trust objects - e.g.g use a robot to check if the object is still there, and if not, drop the connection.
* Are there licensing restrictions for metadata?
* Case studies of scientific communities should be published as soon as possible
* Credit for researchers is important
* Libraries have a role too - even if there is a fear of data management
* Universities are very disparate - makes it hard politically to agree on data policy.