This presentation was used for user training at CUED.

1. ©David Castillo Domenici, FreeDigitalPhotos.net
Data Management
Graça Gabriel
“Data that is loved tends to survive.”
Kurt Bollacker
Department of Engineering, Library and Information Service
Attribution-NonCommercial-ShareAlike

2. What is data?
©EpicGraphic.com
PresentationInformationData Knowledge

3. What is data?
The Royal Society. (2012). Science as an open enterprise. Available at
www.oecd.org/sti/sci-tech/38500813.pdf (retrieved 6 January 2014).

4. “’research data’ are defined as factual records
(numerical scores, textual records, images and
sounds) used as primary sources for scientific
research, and that are commonly accepted in the
scientific community as necessary to validate research
findings. A research data set constitutes a systematic,
partial representation of the subject being
investigated.” (OECD, 2007, p.13)
OECD. (2007). OECD Principles and guidelines for access to research from public funding.
Available at www.oecd.org/sti/sci-tech/38500813.pdf (retrieved 18 October 2013).
What is research data?

5. Digital universe
EMC. (2012). The digital
universe in 2020: big data,
bigger digital shadows,
and biggest growth in the
Far East. Available at
http://www.emc.com/leadershi
(retrieved 14 January
2014).

6. • Video;
• Audio;
• Databases;
• Still images;
• Spreadsheets;
• Text documents;
• Instrument measurements;
• Experimental observations;
• Quantitative/qualitative data;
• Slides, artefacts, specimens, samples;
• Survey results & interview transcripts;
• Simulation data, models & software;
• Sketches, diaries, lab notebooks;
• …
Types/formats of research data
©David Castillo Dominici, FreeDigitalPhotos.net
©Supertrooper, FreeDigitalPhotos.net
©Salvatore Vuono,
FreeDigitalPhotos.net
©Mentor Graphics
©zirconicusso,
FreeDigitalPhotos.net
©NOAA
©Evgeni Dinev, FreeDigitalPhotos.net

7. Data types
The Royal Society. (2012). Science as an open enterprise. Available at
www.oecd.org/sti/sci-tech/38500813.pdf (retrieved 6 January 2014).

8. ©Stuart Miles, FreeDigitalPhotos.net

9. Do you know what your funders
expect of your research?
What plans have you made for you
research data?
What type of note-taking have you
designed?

10. Early planning 〉 1. Funding bids requirements
Become familiar with what funders expect in terms of:
•Managing generated data (how you will document and maintain the
research you produce);
•Publishing results (how/where to publish);
•Sharing outputs (open access types);
•Depositing and preserving outputs (how you will ensure your data is
accessible in the long term, such as depositing papers in a repository or
using a recommended data centre for safekeeping).
Help provided by:
Department/group computing officer(s)
Cambridge Research Office
DSpace@Cambridge support staff
Librarians

11. Early planning 〉 2. Data planning
Plan ahead for your data management needs:
•Type of data created
• Consider what data will be created (e.g. interview data and
transcripts, experimental measurements, high resolution
imaging…);
• Consider how data will be created/captured (e.g. recorded, printed,
made available in a website/intranet);
• Consider the equipment/software required (Find out if there is
funding in case new software is needed).

12. Early planning 〉 2. Data planning
Plan ahead for your data management needs:
•Choose what data format(s)
• What discipline-specific norms already exist;
• What software/formats you or colleagues have used in past
projects, and which will be easiest to share with others (e.g.
Microsoft Excel for recording data, SPSS for analysis);
• What formats will be easiest to annotate with metadata;
• What formats are at risk of obsolescence;
• What software is compatible with hardware you already have.

13. Early planning 〉 2. Data planning
Plan ahead for your data management needs:
•Volume of data created
• Consider where data is going to be stored;
• Consider if the scale of data poses challenges when sharing/
transferring data.
•Plan how to sort and analyse data;
•Investigate about Intellectual property rights (IPR) concerning your
research and its dissemination, future related research projects, and
associated profit or credit.

14. Early planning 〉 2. Data planning
Plan ahead for your data management needs:
•Investigate about data protection and ethics
According to the Data Protection Act 1998 (governs the processing of
personal data), information must follow eight data protection principles:
• processed fairly and lawfully
• obtained for specified and lawful purposes
• adequate, relevant and not excessive
• accurate and, where necessary, kept up-to-date
• not kept for longer than necessary
• processed in accordance with the subject's rights
• kept secure
• not transferred abroad without adequate protection

15. “Plagiarism is defined as submitting as one's
own work, irrespective of intent to deceive,
that which derives in part or in its entirety from
the work of others without due
acknowledgement. It is both poor scholarship
and a breach of academic integrity.”
(Cambridge University, 2011)
). © Thomas Hawk via Flickr
Early planning 〉 3. A note on plagiarism

16. Early planning 〉 4. Note-taking
Design a reading grid to take notes of the main ideas/data/research
(including specific citations that you may want to use later on).
•Quivy and Campenhoudt
Quivy, R.; Campenhoudt, L. (2008). Manual de investigação em ciências sociais (5 ed.).
Lisboa: Gradiva.
Main ideas/content Evaluation of
ideas/content
1. e.g. Theory A considers… (pages x-x) e.g. Different
theories;
Take further
research on those
supporting theory
x and theory y;
2. e.g. Theory B considers…
3. e.g. Theory C…

17. Early planning 〉 4. Note-taking
• The Cornell Method
Pauk, W. (1993). How to study in college (5th
ed.). Boston: Houghton Mifflin Co.
Major themes Detailed points
1st
main point
e.g. There are several types of theories
More detailed information.
e.g. Theory A explains…
More detailed information.
e.g. Theory B explains…
e.g. Theory C explains…
2nd
main point
e.g. Why do some believe in theory A
e.g. Reason 1…
e.g. Reason 2…
critical evaluation
e.g. Both theories A and B do not explain the occurrence of xxx.

18. Early planning
Further information
Cambridge University Intellectual Property Rights Regulations
DSpace@Cambridge IPR page
JISC Legal IPR page
DPA 1998: advice for Cambridge staff and students
University page about the Data Protection Act 1998
UK Data Archive Duty of confidentially
The Information Commissioners's Office Guide to data protection
JISC Legal Guide to data protection
Contact the Protection Office: data.protection@admin.cam.ac.uk
University self-taught courses:
Data Protection Training for Academic Staff ;
Data Protection Training for Administrators

19. LEKO via Jalopnik, ThePimp.Blog

20. How do you organise your files?
How do you name your files?
Do you create metadata to help describe your
data?
Do you manage your emails?
How do your organize your bibliographic
references?
Do you have remote access to your data?

21. • Adhere to existing procedures (within your research group,
Department or preferred by your supervisor);
• Use folders and subfolders
• Name folders appropriately (e.g. after the areas of work and not after
individual researchers or students);
• Be consistent with a naming scheme;
• Structure folders hierarchically (limited number of folders for the
broader topics, and more specific folders within these);
• Separate on-going and completed work;
• Be consistent with filenames
• Choose a standard vocabulary: use a revision numbering system
(e.g. xxxx_v01.doc; 1930film0001.tif); specify the amount of digits to
use (standard: eight-character limit);
Organize your data 〉 1. Naming and organizing files

22. • Be consistent with filenames
• Decide on the use of dates so that documents are displayed
chronologically;
• Include a version control table for important documents;
• Avoid characters such as / : * ? < > | (because they are reserved for
the operating system) and spaces (use hyphens or underscores
particularly with files destined for the Web);
• When drafts are circulating, decide how to identify individuals (e.g.
xxxx_gdcf2_v01.doc);
• Mark the final document as “Final” and prevent further changes.
• Review records (assess materials regularly or at the end of a project to
ensure files aren’t kept needlessly);
• Backup your files/data/favourites.
Organize your data 〉 1. Naming and organizing files

23. • Use metadata (data about data -
usually embedded in the data
files/documents themselves) to add
information to your documents (e.g.
use Microsoft Office’s “Document
properties”).
• Create both study-level information
about the research and data
creation, as well as descriptions
and annotations at the variable,
data item or data file level;
• Provide searchable information to
help you/others find information.
Organize your data 〉 2. Documentation and metadata

24. • Standard metadata fields:
• Title (Name of the dataset or research project);
• Creator (organization or people who created the data);
• Identifier (number used to identify the data);
• Subject(s) (keywords describing the subject or content of the data);
• Funders;
• Rights (known intellectual property rights held for the data);
• Access information (where/how data can be accessed by others);
• Significant dates (project start and end date; release date; data
lifespan; update schedule);
• Methodology (how the data was generated);
• Code lists (explanation of codes or abbreviations used);
• Versions (date/time stamp for each file);
• List of file names (list of all data files associated with the project).
Organize your data 〉 2. Documentation and metadata

25. Organize your data 〉 2. Documentation and metadata
Further information
Data Documentation Initiative
UK Data Archive: Documenting your data
MIT Libraries Documentation and metadata
Library of Congress Authorities
JISC Digital Media Approaches to describing images
Help provided by Dspace@Cambridge:
support@repository.cam.ac.uk

26. Organize your data 〉 3. Use RSS feeds
• Structure information from the web (news
websites, blogs, etc.) into a feeds reader (e.g.
feedly, digg reader, NewsBlur, NetVibes);
©Vector, www.youtoart.com
• Set up journal alerts or
citation alerts (from
databases).

27. Organize your data 〉 4. Manage your email
• Structure your folders by subject, activity or project;
• Set up a separate folder for personal emails (create
filters so they go directly here);
• Archive old emails (even if it’s in an "Archive" folder);
• Delete useless emails and block junk email;
• Limit the use of attachments (use alternative ‘data
sharing’ options) but, if important, save them.
• Try applications to help you manage your email (see “
7 great services for taking back control of your inbox”)

28. • Keep track of every
bibliographic reference
used/seen;
• Use a reference management
software;
• Backup your bibliographic data.
Organize your data 〉 5. Managing references
Further information
University Library webpage about
Mendeley, Zotero and EndNote

29. Organize your data 〉 6. Remote access
©winnond,
FreeDigitalPhotos.net
• Use a single technology/method of remote
access
or
• Decide on clear rules for managing your
remote access technologies
• Designate one device as your “master”
storage location;
• Transfer the latest versions of your files to
your master device ASAP, every time that you
do work away from your master storage
location;
• Back up your important files regularly.

30. • Departmental/college Virtual Private Network (VPN)
See the University Computing Service Info sheet
• Desktop Services Account
See the University Computing Service
Introduction to Desktop Services
• Research group’s CamTools site (Moodle in the future)
See CamTools site
CamTools Helpdesk camtoolshelp@admin.cam.ac.uk
• Online services that provide storage (e.g. DropBox)
• Online/desktop programs to storage and keep track of the
changes made to documents (e.g. Git)
Organize your data 〉 6. Remote access

31. • Key printed data should be kept in a secure location where access
can be restricted to authorised personnel or in locked cupboards;
• Keep our sensitive electronic data password protected, encrypted
or sett privileged levels of access (including backups);
• Do not use printouts with sensitive data as scrap paper. Chose
efficient methods of disposing (like shredding);
• Computer terminals should not be left unattended and should be
logged off at the end of each session;
• Protect your computer with anti-virus, firewall and anti-keylogging;
Organize your data 〉 7. Keep your data safe

32. • Choose strong passwords (use a mix of upper and lower case letters
and digits/punctuation characters)
• If you store passwords on a computer system, encrypt the file;
• Never give your password to other people;
• Frequently change passwords.
Organize your data 〉 7. Keep your data safe
Further information
University Computing
Service
Password? What password?
CUED
Departmental policy on data pr
• Store crucial data in more than one secure
location
• Networked drives;
• Personal computers/laptops;
• External storage devices (CDs, DVDs, USB
flash drives);
• Remote or online systems for storing
(Dropbox, Mozy, A-Drive, etc.).

33. Further information
See: http://datalib.edina.ac.uk/mantra/

34. Jones, S. (2011). How to Develop a Data Management and
Sharing Plan. Edinburgh: Digital Curation Centre. Available at:
http://www.dcc.ac.uk/resources/how-guides/develop-data-plan#s
(retrieved 17 February 2014).
Further information

35. ©Pixabay.com

36. How do you decide what to
keep/delete?
Where/how are you going to
preserve your data?

37. Preserving your data 〉 1. Information in the cloud
EMC (2012). The
digital universe in
2020: big data,
bigger digital
shadows, and
biggest growth in the
Far East. Available
at
http://www.emc.com/lea
(retrieved 14
January 2014).

38. Preserving your data 〉 2. What to keep/delete
• Does your funder/university needs to keep data and /or make it
available for a certain amount of time?
• Is the data a vital record of a project/organisation/consortium and
therefore needs to be retained indefinitely?
• Do you have the legal and intellectual property rights to keep and
re-use the data? If not, can these be negotiated?
• Does sufficient metadata exist to allow data to be found wherever
it is stored?
• If you need to pay to keep the data, can you afford it?
• Only store what you need to keep! Storage costs money and/or effort
and storing massive amounts of data require a well thought plan to
organize it so that information is easily found;

39. Further information
The University Computing Services provides up to 500 MB of
centralised file storage space through the public workstation facility
(PWF), which also allows you to store and access files online.
Some colleges/departments/research groups provide networked
storage (ask your local computing officers for details).
Digital Curation Centre The value of digital curation
UK Data Archive FAQ
Engineering Research Information Management Project (ERIM)
National Preservation Office Caring for CDs and DVDs
Wikipedia List of backup software
Wikipedia Comparison of online back-up services
Preserving your data 〉 3. Storage

40. Preserving your data 〉 4. Long-term storage
• Digital repositories
Provide online archival storage – usually open access – and care for
digital materials, ensuring that they remain readable for as long as the
repository survives.
e.g. Dspace@Cambridge
• Archive/data center
Ensure data safe-keeping in the long term: datasets are fully documented
with all bibliographical details and users of the data are aware of the
need to acknowledge the data sources in publications.
e.g. Archaeology Data Service

41. Digital Curation Centre.
(cop. 2004-2014). DCC
curation lifecycle model
[image]. Available at
http://www.dcc.ac.uk/res
ources/curation-lifecycle-
model (retrieved 17
February 2014).
Summary

42. ©SOMMAI, FreeDigitalPhotos.net

43. Should you share your data/research?
Are there impediments to sharing
data/research?
Do you have/need a marketing plan to
publicise your research?

44. • Scientific integrity - publishing your data and citing its location in
published research papers can allow others to replicate, validate, or
correct your results, thereby improving the scientific record.
• Funding mandates - UK research councils are increasingly mandating
data sharing so as to avoid duplication of effort and save costs.
• Raise/Increase the impact of your research - those who make use of
your data and cite it in their own research will help to increase your
impact within your field and beyond it.
• Preserve your data for future use – anyone can benefit by being able
to identify, retrieve, and understand the data yourself after you have lost
familiarity with it, perhaps several years hence.
Market your data 〉 1. Reasons to share

45. • Teaching purposes - your data may be ideal for others to learn how to
collect and analyse similar types of data themselves.
• Making publicly funded research available publicly - there is a
growing movement for making publicly funded research available to the
public, as indicated for example, in the Organisation for Economic Co-
operation and Development (OECD) Principles and Guidelines for
Access to Research Data from Public Funding.
• Increase transparency through creating, disseminating and curating
knowledge.
• Increase collaboration - the use of archived data by other researchers
may lead to with the data owner and to co-authorship of publications
based on re-use of the data.
Market your data 〉 1. Reasons to share

46. • If your data has financial value or is the basis for potentially valuable
patents that could be exploited by the University, it may be unwise to
share it, even with a data licence or terms and conditions attached.
• If the data contains sensitive, personal information about human
subjects, it may violate the Data Protection Act, ethics codes, or your
own written consent forms to share it, even with other researchers.
(often there are ways to anonymise the data to remove the personally
identifying information from it, thus making it sharable as a public use
dataset).
• If parts of the data are owned by others, such as commercial entities
or authors, then even if you have derived wholly new data from the
original sources you may not have the rights to share the data with
others.
Market your data 〉 2. Reasons not to share

47. • Publish in Open Access journals or deposit a copy into
DSpace@Cambridge;
• Enhance your online presence though social media (Facebook,
Twitter, start and maintain a blog);
• Use author identification (researcherID from Web of Science; Scopus
ID, ORCID);
• Share research in ”academic” platforms (LinkedIn, Academia.edu,
ResearchGate, Microsoft Academic Search, Mendeley);
• Keep track of different metric statistics (number of citations);
Market your data 〉 2. How do you market?

48. Market your data 〉 2. How do you market?
Further information
Digital Curation Centre Overview of major funders’ data policies
SHERPA JULIET searchable international database of funders'
open access and archiving requirements
Times Higher Education supplement "Research intelligence -
Request hits a raw spot" (15 July 2010)
Dspace@Cambridge
DOAJ – Directory of Open Access Journals (with information on
OA journal preservation program and OA quality standards
OAD – Open Access Directory

49. Summary
Guidance Leaflet by DICE, SHARD and PrePARe projects.

51. Thank you
Graça Gabriel
gdcf2@cam.ac.uk

52. Department of Engineering, Library and Information Service
cued-library@eng.cam.ac.uk
Telephone: +44 1223 332626