Rebekah Cummings, GSE&ISLibbie Stephenson, SSDA

DATA MANAGEMENT FOR EDUCATION RESEARCH

GSE&IS

2GOALS FOR TODAY’S

SESSION

Understand opportunities and reasons for data management planning

Learn about best practices for collecting and organizing research data

Learn about best practices for protecting privacy and confidentiality in data

Learn about resources and support available to researchers at UCLA

In this session you will:

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3

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Dat

a Li

fe-c

ycle

http://www.data-archive.ac.uk/create-manage/life-cycle

GSE&IS

4DATA MANAGEMENT

PLANS

What is a data management plan?

Why do I need to write one?

What tools are available to help me?

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5WHAT IS A DATA

MANAGEMENT PLAN?

A data management plan is a document that describes what you will do with your data

during your research and after you complete your research

From Carly Strasser, Caliufornia Digital Library

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GSE&IS

6WHAT IS A DATA

MANAGEMENT PLAN, PART 2

Elements of a data management plan

What are your data?

What formats will you be using?

How will you describe this data?

What intellectual property and privacy rights are associated with this data?

How will you share this data? If you don’t plan on sharing it, why not?

How much will your data management cost?3/28/2008

GSE&IS

7WHY CREATE A DATA

MANAGEMENT PLAN?

Fulfill requirements from funding agencies

Fulfill requirements from journals

Regardless of the requirements, good data management is an essential skill for researchers. 3/28/2008

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8WHY ALL THESE NEW

REQUIREMENTS?

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9TOOLS FOR CREATING A

DMP

DMP Tool - https://dmp.cdlib.org

ICPSR - http://www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/elements.html

The UCLA Social Science Data Archive (that’s us!) - http://dataarchives.ss.ucla.edu/

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10PLANNING & ORGANIZING

DATA COLLECTION

What kind of data is being collected?

What methods will you use to collect the data?

How would describe your data so that others can use it without your help?

Where do you plan to store your data? If you plan to share your data with others, how do you plan to do this?

Where can you get training?

Where can you get help?3/28/2008

In p

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GSE&IS

11 DIFFERENT FILE TYPES = DIFFERENT DATA MANAGEMENT

Video

Audio

Qualitative

Quantitative

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•Project overview•Participants•Privacy•Intended use now and in the future•Equipment and Software•Metadata

GSE&IS

12DATA COLLECTION –

VIDEO

•Create a Project overview

*Participants and events, main point of the video, structure, participant/observer/interviewer relationship

*Specific problems you hope the video will solve

*Intended uses; whether or not publicly sharable

*Consent of participants; Protection of privacy/confidentiality

•Choose pre- and post-production or analysis software: *open source vs proprietary standards

•Keep detailed metadata – keep lots of copies3/28/2008

13 METADATA – VIDEO

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•Type/Format *DVD, HD, mpeg, mov,

•Run time*hours, min, sec

•Title•Producer/author•Date(s)

*real time video was made•Location(s)

*place of production*geographical areas

•Content *annotations

*subject •System req, for access

*Windows media*QuickTime*RealPlayer •Download req.

*size of file*software needed

•Contact info •Persistent identifier •Other documentation

*annotations, docs •Video clips (if app.)

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Data collection – Audio

•As with video, begin with a Project overview •Equipment - portable audio recorder most useful (pre- and post-

recording) • Software for recording and editing

*Computing specification needed and what is available to you*Open source vs proprietary software

• Plan how you will manage during and after project*Always keep original file and edited file copies; use highest quality possible*Web hosting/streaming , CD or DVD storage*Licensing and privacy issues

• Maintain your metadata from the very beginning*File naming conventions*File formats – MP3, WAV, AIFF or lossless FLAC (compressed or uncompressed)

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Metadata – AudioKey pieces of information needed:

• Structural *Relationship to other audio files in same project *Time period*Geographic and location details

• Descriptive *Title, Creator, Subject, Description of project, content and Coverage

• Administrative*Rights, licensing, who can use

• Technical schemas (most important for re- use and preservation)

*AudioMD*Adobe's XMP (Extensible Metadata Platform)*MPEG-7

• Embedded*Do not rely on this as a metadata schema or preservation resource

GSE&IS

16DATA COLLECTION –

QUALITATIVE

Examples : In-depth/unstructured interviews,

including video

Semi-structured interviews

Structured interview questionnaires containing substantial open comments

Focus groups

Unstructured or semi-structured diaries

Observation field notes/technical fieldwork notes

Case study notes

Minutes of meetings

Press clippings

Court transcripts

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File format: text , ascii, rtf, etc.

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17DATA ANALYSIS –

QUALITATIVE

Dedoose*Cross-platform app for analyzing text, video, and spreadsheet data (analyzing qualitative, quantitative, and mixed methods research).

NVivo, ATLAS-ti and MAXQDA *Organizes projects into raw data, coding tree, coded data, and associated memos and notes to be saved

NUD*IST – no longer really used, prefer Nvivo

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18METADATA -

QUALITATIVE Interviews, transcriptions, oral histories, etc.

*Unique identifier, a name or number, uniform layout, numbered pages*Note date, place, interviewer name and interviewee details*Use speaker tags, have line breaks between turn-takes*Use pseudonyms to anonymize personal identifying information

Metadata schema QuDEx *Analysis software can output to this schema*Covers:

*creator *method *date/time *place *size, *unique identifier*codes *coding structure 3/28/2008

GSE&IS

19 DATA COLLECTION - QUANTITATIVE

Surveys, numerically coded records, spreadsheets

Variety of methods: f-2-f, phone, mail, web*Survey monkey, Qualtrix

Documented with questionnaire, codebook*Question wording, universe, sampling, weighting, unit of analysis, geography, time period, coding format/structure,

Consent of participants; Protection of privacy/confidentiality

Choose pre- and post-production or analysis software: *open source vs proprietary standards

Keep detailed metadata3/28/2008

GSE&IS

20METADATA -

QUANTITATIVE Hypothesis, data collection method

Names of those involved in the project

File structure: question text, variables, variable names/labels, value names/labels, values, frequencies, missing data, recodes, branching, interviewer instructions

Disclosure analysis

Storage formats, distribution formats , persistent identifier

Source of data if not from survey

Source of funding, if any

Data Documentation Initiative (DDI) 3/28/2008

GSE&IS

21DATA PROTECTION-

CONFIDENTIALITY

If your research involves human subjects, you will need to consider both legal and ethical obligations in managing and sharing your data.

Confidentiality refers to the agreement between the researcher and the participant about how the participant's identifiable private information will be handled, managed, and disseminated.

As a researcher, you need a clear view about how to protect the privacy of your research subjects.

From: MANTRA: Research Data Management Training http://datalib.edina.ac.uk/mantra/dataprotection.html

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GSE&IS

22CONFIDENTIALITY,

PART 2

How to minimize risk of disclosure:

If possible, collect the necessary data without using personally identifying information.

If personally identifying information is required, de-identify your data upon collection or as soon as possible thereafter.

Avoid transmitting unencrypted personal data electronically.

Be careful with indirect identifiers.

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23DATA MANAGEMENT

ROLLOUT SURVEY

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JISC Data Management Rollout Project Survey Results- 2012- http://damaro.oucs.ox.ac.uk/outputs.xml

GSE&IS

24INTELLECTUAL

PROPERTY

Know your rights as a data producer and data consumer.

Ownership of data

Three legal mechanisms for sharing data:

1. Contracts

2. Licenses

3. Waivers 3/28/2008

GSE&IS

25 RESOURCES UKDA tools for creating and managing data:

http://www.data-archive.ac.uk/media/2894/managingsharing.pdf

MANTRA – online learning tool/tutorial http://datalib.edina.ac.uk/mantra/

JISC Digital Media Advice http://www.jiscdigitalmedia.ac.uk/advice/ http://www.jiscdigitalmedia.ac.uk/creating

UCLA SSDA resources for data management http://www.sscnet.ucla.edu/issr/da/archive%20tutorial/preparingdata.html

ICPSR resources for documenting and preserving http://www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/framework.html

Qualidata http://www.esds.ac.uk/qualidata/about/introduction.asp

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26QUESTIONS AND

DISCUSSION

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