1. Everything you need to know about data management plans
Marta Teperek
Office of Scholarly Communication, University of Cambridge
@martateperek
Introduce the presenters
Explain their backgrounds and different areas of expertise
16 November 2016

2. https://dmponline.dcc.ac.uk/
Before we start…
Does everyone have an account with DMPonline?

3. Interactive session – computers needed in part 2
Before we start…
Fire alarms
Refreshments
Comfort breaks
Interactive session – computers needed in part 2
Ask questions at any time
Slides will be available

4. Outline of this session:
Content
Outline of this session:
Part 1: Introduction to data management plans:
Why?
What?
How?
Part 2: Introduction to DMPonline
Create a data management plan using an online tool
Peer review your colleague’s data management plan

5. Your department/institution Why did you come to this workshop?
Introduction
Who are you?
Your name and role
Your department/institution
Why did you come to this workshop?

6. Have you created a data plan before?

7. Why do we suddenly need to have data management plans?
You’re probably saying to yourself: why do we suddenly have these extra requirements and why do we need to worry about data plans

8. Changing policy landscape
So they have created important policies on how research should be managed and shared

9. Research Data Policies
“Publicly funded research data are a public good (…), which should be made openly available with as few restrictions as possible…”
The general expectation is that publily funded research is a public good and should be shared as widely as possible.
This statement comes from Research Councils UK – UK government funding bodies, but actually the very same thing applies to other funders across the world: we have here ERC and EC from EU, we have NIK, Bill and Melinda Gates (USA).
Your funders probably also have rules.

10. Research Data Policies
The general expectation is that publily funded research is a public good and should be shared as widely as possible.
This statement comes from Research Councils UK – UK government funding bodies, but actually the very same thing applies to other funders across the world: we have here ERC and EC from EU, we have NIK, Bill and Melinda Gates (USA).
Your funders probably also have rules.

11. Why do funders require this?
Ensure better data management practice (reproducible research)
Ensure that researchers are prepared to share their data

12. Ensuring better data management practice
You must do it
EPSRC do random checks to make sure data are shared in publications that acknowledge their funding

13. Immediate reaction:
It would take me 5 years to find all my data!
The postdoc who had the data left the lab
Should be writing down all protocols?
Data management is a waste of time
Nobody will understand my data
No surprise if researchers did not know how to effectively manage their data

14. Research reproducibility crisis
Nature 533, 452–454 (26 May 2016) doi: /533452a

15. Research relies on the principle that we share our findings
Sharing research data is fundamental to being an academic
Research relies on the principle that we share our findings
Without the supporting data, publications are just claims
It is because sharing your research is fundamental to being an academic

16. Datasets available ‘on request’ is not available

17. Datasets available ‘on request’ are not available
Data availability decreases by 17% per year
Chance of address working decreases by 7% per year

18. Datasets available ‘on request’ are not available

19. Need for a plan Data management plan = assurance to the funder:
You are aware of their data management and sharing expectations
You will manage your data well
You will be prepared to share your data
You will make appropriate resource allocation for this
Selfish reason: you will find your data easily
So data management plan assures the funder that you understand what you are supposed to do with your research outputs 

20. What needs to be covered in a data management plan?
We got the ‘why’
Now the ‘what’
What needs to be covered in a data management plan?

21. What to include in a data management plan
Core elements of a data management plan:
Identify the types of data you are working with
Decide on your data organisation strategy and data standards
Day to day management of data
What are your plans for data sharing?
Will you experience any problems with data sharing?
Will you require any additional resources?

22. Identify the type of data you are working with
Types of data
Identify the type of data you are working with
Genomic data?
Proteomic data?
Patient data?
Will you generate your own data?
Will you re-use somebody else’s data?

23. Data organisation and standards
Decide on your data organisation strategy and data standards
Copyright:
Make sure your data doesn’t look like this…
***
***

24. How will you organise your data?
Slido

25. Example of data organisation structure
Add Rinocloud video (first 1.30) -
Copyright:

26. Data organisation strategy should:
Be consistent
Be meaningful to you and your colleagues
Allow you to find files easily
Include physical samples as well!

27. Will you use any file naming conventions?
In 3 years time would you know what these are?

28. Example file naming convention
Add examples from the OSC drive

29. Data organisation and standards
Will you adhere to any discipline-specific metadata standards?
Biosharing is a database of standards to be used in life sciences. You can simply search and see the available community standards.
TIP: Funders like to see statements that you will adhere to standards. So make sure you name and reference the standard you will adhere to in your data plan.

30. How will you store your data during the project duration?
Active data storage
How will you store your data during the project duration?
Is your data going to be safe?
Will you back up your data?
Unsure? Help available:

31. Cloud services comparison
Space included
1 TB
Unlimited
15GB
Price (per annum)
Free
£55-66
Free (1 TB is £95.88)
File history
Yes
30 days
Support available
Webpages from UIS
Unsupported
Where are files stored?
Within EU
Anywhere
Live editing
Yes – dependent on browser
Only with an Office 365 licence
What types of data can be shared?
Unclassified, Cambridge only, or confidential data
Unclassified or public data
Never share on any cloud service: Level 3: Personal and strictly confidential information
This covers documents that contain highly sensitive information or personal details that are for the eyes of the recipient only where delegated authority is not appropriate.

32. Day to day data management
How are you going to ensure proper data management?
Will there be any quality checks for data collection/analysis in your group?
Who will be responsible for what?
Safety: especially key when working with patient’s data!!! Most of the time this will require encryption of your storage devices.

33. After the end of your project
Will you share your data?
When will you share your data?
How are you going to share your data?
Are your plans in line with your funder’s expectations?
Remember to check out funders policies

34. Typical sharing requirements
Most funders expect you to:
Make your data available upon publication
Store data for (at least) 10 years
Describe your data
Deposit your data in suitable data repositories and add a link to your data in your publication
Remember to check out funders policies

35. Date the policy was last checked or updated.
Funder names arranged alphabetically. Click on the hyperlink to see the full-length policy.
Key policy highlights
Most probably your institution has detailed guidance on funders policies. In Cambridge we have a dedicated RDM website where guidance on top 20 funders’ data policies is provided:
Ask your institutional support – most probably they have dedicated services for this.
Or if your institution doesn have anything, try out Sherpa Julier: – a tool allowing you to look up funders policies
Date the policy was last checked or updated.

36. What is a repository?
What is a repository?
A place where things can be stored and shared

37. What kinds of repositories are there?
There are different kinds of repositories:
for ‘everything’
for datasets
for software
for protocols
for institutions
And many, many more!
Choose the best repository for the type of data you have.

38. What kinds of repositories are there?
Repositories for ‘everything’

39. What kinds of repositories are there?
Repositories for datasets
General purpose
Discipline-specific
Re3data.org is a registry of data repositories – over 1,000 data repositories registered there. Simply searchable and you can find the repository most suitable for your data.

40. What kinds of repositories are there?
Repositories for software +
For software management it is best to use GitHub and to make snapshots of software on Zenodo (they have an integration, so you simply press a button to archive your software and get a DOI for it).

41. What kinds of repositories are there?
Repositories for protocols
If you develop new protocols, or your lab uses a protocol, consider sharing as well.
TIP: Funders like sharing – sharing protocols will make your application stronger, and you will demonstrate evidence of adherence to standards.

42. What kinds of repositories are there?
Repositories for images – under construction
If you develop new protocols, or your lab uses a protocol, consider sharing as well.
TIP: Funders like sharing – sharing protocols will make your application stronger, and you will demonstrate evidence of adherence to standards.

43. Cambridge research repository
Repositories for institutions
Many institutions have their own repositories. Cambridge has its research repository since Any Cambridge researcher can deposit their research there.

44. Selfish reason: share once and don’t be bothered
Corresponding authors: Or

45. Selfish reason: share once and don’t be bothered

46. Cambridge repository is well ‘googleable’
The repository is well indexed in Google
TIP: If your institutional repository is well indexed by Google, mention this in your data plan – this will demonstrate to your funder that your data is well discoverable = more impactful = they will like it more

47. Repository use 14 October 2016 – 13 November 2016
Repository use 14 October 2016 – 13 November 2016
26,274 visits

48. If you share your data – use it to your benefit
Persistent link(s) – DOIs - enable data citation
Impress your funder – make your data discoverable and your research impactful – ideas:
indicate statement on data availability in publication(s)
deposit data in well-indexed (or well-known) repository(ies)
publishing a 'data paper' to accompany the dataset
Scientific Data from Nature (
Wellcome Trust Open Research (
providing reference on project/institutional websites
publicising information about the data on social media
Cambridge does this for you
Funders like statements like these
Make sure to include them in your data plan

49. Wellcome Open Research publishing platform

50. Wellcome Open Research publishing platform

51. Limitations to sharing
Will you experience any problems with sharing your data?
Personal/sensitive data
Commercially-confidential data
Big data?
If so, you need to explain this to your funder from the very beginning.
Think about possible limitiations to data sharing. These (if you will experience them) need to be carefully explained from the start of the project.

52. Will you require any additional resources?
people infrastructure: data managers?
costs of active data storage: consult your IT support
costs of licences for software to support data management
Electronic Lab Notebooks?
costs of data ingestion by the repository/long-term preservation:
Repositories might charge to ensure sustainability
Cambridge is charging at £4/GB (for datasets above 20GB) – it is a one off charge
Think about possible limitiations to data sharing. These (if you will experience them) need to be carefully explained from the start of the project.

53. Let’s look for the ‘how’ Is there any help available?
We got the ‘why’
We got the ‘what’
Let’s look for the ‘how’
Is there any help available?

54. Cambridge data management plan support page
Sample plans
Funders’ guidance
Template not there?
Cambridge researchers are lucky – there are dedicated help pages for DMP creation.
There is detailed funders guidance on DMP, and also sample plans that anyone can download and see.

55. Cambridge data management plan support page
Researchers can simply prepare their plan in a Word doc, and when they want the plan to be reviewed, they can simply submit it to the data team at Cambridge for comments.

56. https://dmponline.dcc.ac.uk/
DMPonline
For those of you who don’t have dedicated DMP support, or simply don’t want to use institutional services, you can use a freely available web tool to create data plans. The tool has been developed by the Digital Curation Centre and is made available to everyone.

57. Practical exercises with DMPonline
Introduction to DMPonline
Think of a project you want to get funded and the funding body you wish to apply to for funding
Select the appropriate funder
Use DCC guidance
Answer the questions - be prepared to share

58. Practical exercises with DMPonline
Review:
Invite your colleague as a collaborator (with edit access)
Review each other’s plans and give suggestions
Give feedback to each other
Q&A

59. Today we have covered: Lessons learnt
Why funders require data management plans
What to write in data management plans
How to create them
Practical experience of DMP online

60. Training and support
Update

61. Feedback from PhD students on our RDM workshops
For tailored session requests
From RDM workshop for GSLS on 11 November

62. Questions and feedback
This is our first workshop on data management plans… …please help us improve it

63. Take home message:
Cambridge data services are predominantly for Cambridge researchers, but the webpages are freely accessible to anyone, so you can all use as a good starting point for your data management needs/questions

64. Questions: info@data.cam.ac.uk
Thank you
Questions:
@CamOpenData

65. How to handle personal data?
Don’t collect it!
Gain informed, preferably open and written, consent
Anonymise data
Remove identifiers
Aggregate results
Generalise a variable
Remove outliers
Use managed access repositories

66. Resources for working with personal/sensitive data
Clinical School website:
Carolyn Read
University Ethics website
Dr Rhys Morgan
Our website (University resources)
MRC guidelines
ESRC guidelines
Collapse into 1 slide

67. Other parts of the University:
Unsure if your strategy for data management is right?
Clinical School:
Compliance requirements: Carolyn Read
Storage requirements: Richard Bartlett
Contacts:
Other parts of the University:
Information Management team:

68. Information Management team support form
Unsure if your strategy for data management is right?
Information Management team support form Or