Presentation on theme: "5. Resourcing Adherence, review and long-term management www.dmtpsych.york.ac.uk."— Presentation transcript:
5. Resourcing Adherence, review and long-term management
Who’ll do what when? Resourcing is about people, organisations, time and money In both your funding bid and data management plan you are encouraged to say who’ll do what in order for your data management plan to be implemented, what this will cost and how much time it will take Depending on where you are in the projects lifetime this may only be a sketch outline Ideally you should be making use of existing departmental or institutional provision You should be as realistic as possible in terms of resource allocation. Good data management can take up to 10-20% of your time Should be resourced and funded appropriately. Don’t forget that funding applications also now assess the quality of their Data Management Plans
A resourcing example It is a good idea to split day-to-day tasks from those that may be carried out less frequently Resource allocation may also be assigned based on seniority so that more in-depth tasks are completed by the Principal Investigator An outline example is shown below:
How will data management be funded? Funding to implement a Data Management Plan should cover funding during the projects lifetime and funding after the project ends During a projects lifetime –Generally funded in one of two ways: If using departmental or institutional file servers and backup procedures typically funded through overheads built into the grant. Some institutions charge for file space through! A fraction of the paid time of personnel + equipment After a project ends –Could be front loaded, e.g. some institutions charge up front for the volume of data x by the number of years you want to make it available –Some institutions have their own repository which handle this as a function of institutional overheads –National or funder maintained repositories, e.g. the UK Data Archive, may provide longer term storage at no additional cost to the project and in effect is met by the funder
Adherence Adherence refers to the process of checking that the Data Management Plan is on track and that the various tasks outlined have been completed – are you doing what you said you’d do? Within the plan itself there should be a section that defines who and how adherence will be checked For example, if a study intends to carry out various sub studies one might say that metadata and other descriptive data should be created no later than two weeks after data analysis is complete – this is a good principle as metadata will be created when the meaning is fresh in everyones mind and also the time window gives a benchmark against which adherence can be evaluated Verifying backups work is also a form of adherence Funding bodies may also wish to check adherence via written statements or site visits for example Final deposit into a recognised repository also ultimately demonstrates adherence You need to think about quality and not just box ticking!
Review Review refers to the process of checking whether the Data Management Plan for a project still makes sense at a given point in a projects lifecycle – this is closely related to checking for adherence It may be that it has been identified that the backup strategies employed do not quite deliver and that an alternative method may need to be deployed The review process is intended to allow for “tweaks” to the plan to be made to keep it on track and/or to deal with changes to the project As with adherence it is good practice to set regular intervals for plan reviews and also to say who will carry out the review, e.g. Principal Investigator or Project Manager It is also possible that your department, institution or funding body may also wish to carry out or validate a review inline with adherence checks You should keep a track record of revisions to plans and if changes are made outline the reasons for these and criteria for assessing adherence
Long-term management Long-term management relates to how the data will be looked after once the project completes Issues to consider include: –Who will physically look after the data? –Who will maintain it? –Who will back it up? –How long it will remain available? –Who will be able to access the data? –Will storage technology be updated? –Will data and metadata be transcribed as new standards emerge? If you deposit within a recognised repository, e.g. the UK Data Archive, these and many other issues will need to be addressed by them rather than you – it’s one less thing to worry about! Within a Data Management Plan it is useful to outline how long term stewardship will occur. As you can see you it’s in your best interest to deposit your data within a recognised repository at the end of a project rather than take over the responsibility yourself!
Summary Resourcing: who’ll do what when. How will data management activities be funded? Both during the projects lifetime and after it ends! Adherence: how will you check that you are doing what you said you’d do with regards to data management. Is the plan being stuck to. Review: how will the plan be reviewed on an ongoing basis and how will changes be made if needed. Does the plan still work. Long-term management: How and who will look after the data once the project finishes. Exit strategy
Is it a good idea to say who will do what and when or is that too restrictive? How likely is it that adherence and review are seen as a “box ticking” exercise? Would an external peer review of a Data Management Plan during the lifetime of a project be a better option? Should an individual researcher ever try to handle their data over the long term? Time to think about data Small group exercises