1) The document discusses best practices for managing research data, including organizing files, documenting data with metadata, storing data securely both internally and externally, and presenting data through tables, charts, and text for publication and sharing. 2) Key recommendations for data management include using logical file naming conventions, non-proprietary file formats, and documenting data with standard metadata fields. External repositories can increase data accessibility and preservation. 3) Effective data presentation involves using tables and charts to clearly visualize quantitative and qualitative findings. Graphs should have clear titles and labels while tables should have logical data placement. Text should concisely summarize results.

1. RESEARCH DATA
MANAGEMENT
IYAD ABOU-RABII
DDS PGCertPharm PGDipOMFS MRes PhD DentPharm FADFE

2. What You’ll Learn
Why you should manage your data
How and where to store your research data
What are the different types of research data
How to present your data
What makes your data presentation good

4. Data Transfer and storage

5. WHY YOU SHOULD MANAGE YOUR DATA
The impact of e-Science and the global network
• “Research data is a form of infrastructure, the basis for data intensive
research across many domains” – EC Riding the Wave
report, 2010
• “Funders expect research to be international in scope. A third of all articles
published are internationally collaborative” – Royal Society,
2011
The governmental and funder imperative
• “Publicly-funded research data must be made available for secondary
scientific research” – ESRC research data policy

6. WHY YOU SHOULD MANAGE YOUR DATA

7. WHY YOU SHOULD MANAGE YOUR DATA
• The benefits of good data management comprise
• Researcher Control • Secure and Backed-up Storage - of working data during the life of the
project
• Secure Long Term Storage - for data through an archiving and curation
service,
• Discovery
• Provision of Support Materials
• Compliance

8. HOW TO MANAGE YOUR
DATA
Whilst good data management
is fundamental for high quality
research data and therefore
research excellence, it is crucial
for facilitating data sharing and
ensuring the sustainability and
accessibility of data in the longterm and therefore their re-use
for future science.
(UK Data Archive)

9. HOW TO MANAGE YOUR
DATA
• Organising files and
file format
• Documentation and
metadata
• Storage
• Access and Security

10. ORGANISING FILES AND FILE FORMAT (file name)
• Vocabulary/Descriptors
• Avoid general words as lead descriptors that convey little
information such as ‘draft’, ‘document’, ‘summary’, etc.
• Spaces – remove spaces or use underscores and hyphens to
separate words, e.g. ‘project-225-descriptions-08.xls’
• Dates – agree on a logical use of dates so that they display
chronologically, e.g YYYY-MM-DD. The Year-Month-Day format
makes files easier to find chronologically.
• File versions – label file versions numerically, e.g. ‘1.0, 1.1, 1.2, etc’

11. ORGANISING FILES AND FILE FORMAT (file format)
• Is there a risk that the file format will become obsolete in the short/medium term?
• Is the format open?
• Is the format specification publicly available?
• Is the format suitable for extracting and discovering data or simply for viewing data?
• Is the chosen format an accepted standard?
• What formats will be easiest to share?
• Are there any discipline-specific requirements?
• What formats will be easiest to annotate with metadata?

12. Organising files and file format (file format)

13. Organising files and file format (file format)

14. DOCUMENTATION AND METADATA
• Metadata for online data catalogues or discovery tools are often structured to include
some or all of the following:
• Title
• Date
• Subject descriptors
• Creator(s) (Creator of the dataset;
main researchers involved)
• Storage location of the data
(including identifier information)
• Origin of the data
(creation/acquisition of the data)
• Time references for the data (key
dates associated with the data: start,
end, release, etc)
• Funders
• Access conditions
• File format
• Terms of use of the data.

15. EXTERNAL
REPOSITORIES
• Benefits of digital repositories
• Increases the accessibility of
your data and raises the impact
of your research.
• Preserves your data by ensuring
it is secure and readable.
• Raises your research profile
through open access.
• Required by your funding body.

16. EXTERNAL
REPOSITORIES
• Identifying and locating external
repositories
• Databib is a tool for helping
people identify and locate
online repositories of research
data. Users and bibliographers
create and curate records that
describe data repositories that
users can search. The list is a
working document and it is
provided for information
purposes only by the DataCite
service.

17. EXTERNAL
REPOSITORIES
• Identifying and locating
external repositories
• The Directory of Open
Access Repositories
(OpenDOAR) contains a
listing of over 2,000 open
access repositories
relevant to academic
research, but was last
updated in July 2010.

18. STORAGE
• Key questions when considering storage:
• Is the storage dependable and reliable? Is there a danger that data may be
lost?
• Are the data replicated with backups at different locations?
• Are backups made with sufficient frequency so that you can restore in the
event of data loss?
• Are the data secure? Is data integrity protected?
• Is access for use and re-use assured?
• Does the storage meet the requirements of the university, the funder, and
legislation?

19. STORAGE
• Cloud services provide remote online systems for the storage
and back-up of data files. They offer a range of service features
including:
• Automatic and scheduled backups
• Local backup
• File encryption during storage and also backup
• Restores
• Laptop and network drive support for Mac and Windows

20. STORAGE
• Cloud services may not be used to store:
• Personal data covered by the Data Protection Act (for example,
personal data related to staff, students or research participants),
unless the University has negotiated explicit contracts with providers
of cloud services, such as it has with Blackboard
• Data or other information covered by legal, commercial and/or
contractual restrictions (for example, research output from
commercially funded project), unless this is explicitly allowed for by
contractual documentation, and/or
• Other data or information which is confidential and/or proprietary to
the University.

21. ACCESS AND SECURITY
• Key questions when considering storage
• Is the storage dependable and reliable? Is there a danger that
data may be lost?
• Is the data secure? Is data integrity protected?
• Is access for use and re-use assured?
• Does the storage meet the requirements of the university, the
funder, and legislation?
• Security and ethics

22. Data Presentation

23. HOW TO PRESENT DATA
It would probably be best to organize the results around answering the
hypothesis and / or the research questions.
Quantitative
Quantitative
(numbers, statistics)
(numbers, statistics)
Qualitative
Qualitative
(words, ideas)
(words, ideas)

24. QULITATIVE STUDY
The naturalistic inquiry is likely to produce large quantities of data that
represent words and ideas.
Raw Data
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Analysis
Texts
Tables
Graphics
Pictures
Charts

25. QULITATIVE STUDY
The sources of information are the following:
1. Interview transcripts.
2. Field notes.
3. Wide variety of records.
4. Documents.
5. Etcetera.

26. QULITATIVE STUDY
Each qualitative analysis requires that the researcher devise his or
her own method for presenting results.
Purpose

“Make sense” of the data.
Method

Inductive analysis.
1. Unitizing (Coding operation)
2. Categorizing (Organizing into categories based on similarities)

27. QULITATIVE STUDY
The results usually presents the outcome of multiple analysis of data.
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Data
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Analysis
Statements
I, II, III, IV
Texts
Tables
Graphics
Pictures
Charts

28. QUANTITATIVE DATA ANALYSIS

29. QUANTITATIVE DATA ANALYSIS
Making sense of numbers.
Using numbers to inform decision-making.

30. QUANTITATIVE DATA ANALYSIS
Categorical
Nominal: names
Ordinal: 1st, 2nd, 3rd.
Continuous
Ratio: consistent distance between each point
Interval: there is a zero starting point
There is an important difference in how you work with categorical and
continuous variables!

31. A COMMON MISTAKES
Not everything can be quantified!

32. A COMMON MISTAKES
Consider practical vs. statistical significance. Don’t be beholden to
statistics. Inferential statistics are a tool, not the answer!

33. A COMMON MISTAKES
Beware the correlation-causation fallacy.

34. DATA PRESENTATION
• TABLES
• CHARTS
• TEXT

35. DATA PRESENTATION
TABLES
Age
GPA
Gender
Hours
Dick
20
1.9
M
1
Edward
19
1.5
M
1
Emmett
20
2.1
M
2
Lauren
20
2.4
F
3
Mike
19
2.75
M
4
Benjie
18
3
M
4
Joe
19
2.85
M
5
Larry
17
2.75
M
5
Rose
18
3.3
F
5
Bob
18
3.1
M
6
Kate
19
3.4
F
7
Sally
21
4
F
8
Sylvia
23
3.9
F
8
Sum
251
36.95
59
Avg
19.308
2.8423
4.5385
Variance
2.3974
0.5437
5.6026
Std Dev
1.5484
0.7374
2.367
19
2.85
5
Median

36. DATA PRESENTATION
TABLES
What's make a good table?
•
•
•
•
Readable,
logical data placement
Clear column and row headings
A title at the top Reporting units

37. DATA PRESENTATION
TABLES
Numbers
•Numbers are usually confusing to the audience. Use as few as possible
and allow extra time for the audience to do the math.
•Numbers should never be ultra precise:
•
“Anticipated Revenues of $660,101.83” looks silly. Are your
numbers that accurate? Just say $660 thousand.
•If you have more than 12-15 numbers on a slide, that’s probably too
many.
•Using only one number per sentence helps the audience absorb the
data.

39. DATA PRESENTATION
TABLES
Statistics
•Use the same scale for numbers on a slide. Don’t compare
thousands to millions.
•Cite your source on the same slide as the statistic, using a smaller
size font.

40. DATA PRESENTATION
CHARTS

41. DATA PRESENTATION
CHARTS
•
Charts need to be clearly labeled. You can make more
interesting charts by adding elements from the drawing toolbar.
•
Numbers in tables are both hard to see and to understand.
There is usually a better way to present your numerical data than
with columns and rows of numbers. Get creative!
•
PowerPoint deletes portions of charts and worksheets that are
imported from Excel, keeping only the leftmost 5.5 inches. Plan
ahead.

42. DATA PRESENTATION
CHARTS
What's make a good graph?
Clear title
Simple clear axis labels
Elements that allow the reader to get the point
A legend explaining graph elements
A scale appropriate to the data
Clear reporting units
Reveals a story
Minimum of clutter

43. DATA PRESENTATION
CHARTS
What's wrong with this?

44. DATA PRESENTATION
CHARTS
What's wrong with this?

45. DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages
Make it a habit to animate your charts before presenting them. It makes
your numbers less intimidating and helps your audiences get more
information from your charts.
First the axes are explained
Then line graph of data X is
shown
followed by the line graph of
data Y

46. DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages
•First select the chart you imported from excel file.
•Go to animations -> Custom animation and select the kind of animation you
want to use. This animates the whole chart.
•Then, go to the custom animation menu and click on the drop down arrow
next to the animation you selected.
•Go to Effect options and you will see a pop up box which gives you the
option to choose chart animation.

47. DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages
You can animate your
chart by Series or by
category.

51. DATA PRESENTATION
TEXT
Thirteen students participated in the minority mentoring program. A
strong positive correlation was found between the number of hours
mentored and achieved GPA (.965), between hours mentored and gender
(.578), and between gender and achieved GPA (.622).

52. DATA PRESENTATION
TEXT
Put your conclusion on the
title
Always put the conclusion from your slide on the slide title. Since
your audience naturally scan your slides top down, a clear title helps
them find your key message fast.

53. DATA PRESENTATION
TEXT
Use images to make your message more
memorable
Sometimes in a data presentation, numbers can be cold and intimidating.
Using relevant images can make your information more inviting.

54. DATA PRESENTATION
TEXT
Use visual representation of
numbersmake data come to life by using small icons to act as units.
You can

55. DATA PRESENTATION
TEXT

57. Remember
• Data should tell a story
• Tailor your presentation to your
audience(s) or readers
• Use multiple formats to help get your
message to all types of learners