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RESEARCH DATA
MANAGEMENT

IYAD ABOU-RABII
DDS PGCertPharm PGDipOMFS MRes PhD DentPharm FADFE
What You’ll Learn

Why you should manage your data
How and where to store your research data
What are the different types ...
Data Transfer and storage
WHY YOU SHOULD MANAGE YOUR DATA
The impact of e-Science and the global network
• “Research data is a form of infrastructur...
WHY YOU SHOULD MANAGE YOUR DATA
WHY YOU SHOULD MANAGE YOUR DATA

• The benefits of good data management comprise
• Researcher Control • Secure and Backed-...
HOW TO MANAGE YOUR
DATA

Whilst good data management
is fundamental for high quality
research data and therefore
research ...
HOW TO MANAGE YOUR
DATA

• Organising files and

file format
• Documentation and

metadata
• Storage
• Access and Security
ORGANISING FILES AND FILE FORMAT (file name)

• Vocabulary/Descriptors
• Avoid general words as lead descriptors that conv...
ORGANISING FILES AND FILE FORMAT (file format)

• Is there a risk that the file format will become obsolete in the short/m...
Organising files and file format (file format)
Organising files and file format (file format)
DOCUMENTATION AND METADATA
• Metadata for online data catalogues or discovery tools are often structured to include

some ...
EXTERNAL
REPOSITORIES
• Benefits of digital repositories
• Increases the accessibility of

your data and raises the impact...
EXTERNAL
REPOSITORIES
• Identifying and locating external

repositories
• Databib is a tool for helping

people identify a...
EXTERNAL
REPOSITORIES

• Identifying and locating

external repositories
• The Directory of Open

Access Repositories
(Ope...
STORAGE
• Key questions when considering storage:
• Is the storage dependable and reliable? Is there a danger that data ma...
STORAGE
• Cloud services provide remote online systems for the storage

and back-up of data files. They offer a range of s...
STORAGE
• Cloud services may not be used to store:
• Personal data covered by the Data Protection Act (for example,

perso...
ACCESS AND SECURITY
• Key questions when considering storage
• Is the storage dependable and reliable? Is there a danger t...
Data Presentation
HOW TO PRESENT DATA
It would probably be best to organize the results around answering the
hypothesis and / or the researc...
QULITATIVE STUDY
The naturalistic inquiry is likely to produce large quantities of data that
represent words and ideas.

R...
QULITATIVE STUDY
The sources of information are the following:
1. Interview transcripts.
2. Field notes.
3. Wide variety o...
QULITATIVE STUDY
Each qualitative analysis requires that the researcher devise his or
her own method for presenting result...
QULITATIVE STUDY
The results usually presents the outcome of multiple analysis of data.

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^*(34565%
1233&^
%&^**)
...
QUANTITATIVE DATA ANALYSIS
QUANTITATIVE DATA ANALYSIS

Making sense of numbers.
Using numbers to inform decision-making.
QUANTITATIVE DATA ANALYSIS
Categorical
Nominal: names
Ordinal: 1st, 2nd, 3rd.
Continuous
Ratio: consistent distance betwee...
A COMMON MISTAKES

Not everything can be quantified!
A COMMON MISTAKES
Consider practical vs. statistical significance. Don’t be beholden to
statistics. Inferential statistics...
A COMMON MISTAKES
Beware the correlation-causation fallacy.
DATA PRESENTATION

• TABLES

• CHARTS

• TEXT
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

La...
DATA PRESENTATION
TABLES
What's make a good table?
•
•
•
•

Readable,
logical data placement
Clear column and row headings...
DATA PRESENTATION
TABLES
Numbers

•Numbers are usually confusing to the audience. Use as few as possible

and allow extra ...
DATA PRESENTATION
TABLES
Statistics
•Use the same scale for numbers on a slide. Don’t compare

thousands to millions.
•Cit...
DATA PRESENTATION
CHARTS
DATA PRESENTATION
CHARTS
•

Charts need to be clearly labeled. You can make more
interesting charts by adding elements fro...
DATA PRESENTATION
CHARTS
What's make a good graph?

Clear title
Simple clear axis labels
Elements that allow the reader to...
DATA PRESENTATION
CHARTS
What's wrong with this?
DATA PRESENTATION
CHARTS
What's wrong with this?
DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages
Make it a habit to animate your c...
DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages
•First select the chart you impor...
DATA PRESENTATION
CHARTS
Tips For Better Data Presentation
Present information in
stages

You can animate your
chart by Se...
DATA PRESENTATION
TEXT

Thirteen students participated in the minority mentoring program. A
strong positive correlation wa...
DATA PRESENTATION
TEXT
Put your conclusion on the
title

Always put the conclusion from your slide on the slide title. Sin...
DATA PRESENTATION
TEXT
Use images to make your message more
memorable
Sometimes in a data presentation, numbers can be col...
DATA PRESENTATION
TEXT
Use visual representation of
numbersmake data come to life by using small icons to act as units.
Yo...
DATA PRESENTATION
TEXT
Remember
• Data should tell a story
• Tailor your presentation to your

audience(s) or readers
• Use multiple formats to h...
Data presentation and transfer
Data presentation and transfer
Data presentation and transfer
Data presentation and transfer
Data presentation and transfer
Data presentation and transfer
Data presentation and transfer
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Data presentation and transfer

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  • Since the conclusion is clearly mentioned on the title, audience’s eyes are naturally led to the relevant numbers on the table.
  • So if you use it for an insignificant point, your audience will remember your presentation for the wrong reason.
  • Transcript of "Data presentation and transfer"

    1. 1. RESEARCH DATA MANAGEMENT IYAD ABOU-RABII DDS PGCertPharm PGDipOMFS MRes PhD DentPharm FADFE
    2. 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
    3. 3. Data Transfer and storage
    4. 4. 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
    5. 5. WHY YOU SHOULD MANAGE YOUR DATA
    6. 6. 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
    7. 7. 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)
    8. 8. HOW TO MANAGE YOUR DATA • Organising files and file format • Documentation and metadata • Storage • Access and Security
    9. 9. 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’
    10. 10. 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?
    11. 11. Organising files and file format (file format)
    12. 12. Organising files and file format (file format)
    13. 13. 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.
    14. 14. 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.
    15. 15. 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.
    16. 16. 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.
    17. 17. 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?
    18. 18. 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
    19. 19. 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.
    20. 20. 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
    21. 21. Data Presentation
    22. 22. 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)
    23. 23. QULITATIVE STUDY The naturalistic inquiry is likely to produce large quantities of data that represent words and ideas. Raw Data Akajfj kjs 9kivkiwv piwjv Ado afcf &^%&^**) !@@$ kljah ajjqa op Aas HKK iip ouou !@@$$*& Analysis Texts Tables Graphics Pictures Charts
    24. 24. QULITATIVE STUDY The sources of information are the following: 1. Interview transcripts. 2. Field notes. 3. Wide variety of records. 4. Documents. 5. Etcetera.
    25. 25. QULITATIVE STUDY Each qualitative analysis requires that the researcher devise his or her own method for presenting results. Purpose  “Make sense” of the data. Method  Inductive analysis. 1. Unitizing (Coding operation) 2. Categorizing (Organizing into categories based on similarities)
    26. 26. QULITATIVE STUDY The results usually presents the outcome of multiple analysis of data. !@@$$*& ^*(34565% 1233&^ %&^**) !@@$ 89763e1 764543 122 45 $%&*)() Raw 098 0904 Data 12 Analysis Statements I, II, III, IV Texts Tables Graphics Pictures Charts
    27. 27. QUANTITATIVE DATA ANALYSIS
    28. 28. QUANTITATIVE DATA ANALYSIS Making sense of numbers. Using numbers to inform decision-making.
    29. 29. 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!
    30. 30. A COMMON MISTAKES Not everything can be quantified!
    31. 31. A COMMON MISTAKES Consider practical vs. statistical significance. Don’t be beholden to statistics. Inferential statistics are a tool, not the answer!
    32. 32. A COMMON MISTAKES Beware the correlation-causation fallacy.
    33. 33. DATA PRESENTATION • TABLES • CHARTS • TEXT
    34. 34. 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
    35. 35. 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
    36. 36. 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.
    37. 37. 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.
    38. 38. DATA PRESENTATION CHARTS
    39. 39. 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.
    40. 40. 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
    41. 41. DATA PRESENTATION CHARTS What's wrong with this?
    42. 42. DATA PRESENTATION CHARTS What's wrong with this?
    43. 43. 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
    44. 44. 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.
    45. 45. DATA PRESENTATION CHARTS Tips For Better Data Presentation Present information in stages You can animate your chart by Series or by category.
    46. 46. 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).
    47. 47. 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.
    48. 48. 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.
    49. 49. DATA PRESENTATION TEXT Use visual representation of numbersmake data come to life by using small icons to act as units. You can
    50. 50. DATA PRESENTATION TEXT
    51. 51. 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

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