L IBBIE STEPHENSON, DATA ARCHIVIST (RETIRED)

UCLA SOCIAL SCIENCE DATA ARCHIVE

LIBBIE@G.UCLA.EDU

HTTPS://DATAVERSE.HARVARD.EDU/DATAVERSE/ SSDA_UCLA

Data Curation for Quantitative Social Science Research:

A Case Study

NISO Virtual Conference: Data Curation – Cultivating Past Research

Data for Future Consumption August 31, 2016

DISCLAIMER

I am retired from UCLA so my comments reflect my own experience and expertise. They do not necessarily reflect the ideas, opinions or practices of anyone at UCLA.

These materials are free for you to use, but please cite accordingly.

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OVERVIEW

About the Archive

About the data we manage

What we are trying to do

What we actually do

Some illustrations

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ABOUT THE ARCHIVE

Operating since 1964 -- before email, PC’s, Internet, laptops, smart phones; Manage survey/quantitative data stored on media from punch cards to cloud

Staff have library science degrees; statistical and technical expertise; quantitative social science background

Serve all UCLA quantitative researchers: Provide reference, cataloging/metadata, long term archiving; support in data rescue, management, security.

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SURVEY/QUANTITATIVE

RESEARCH

Carried out in the U.S. since 1940’s -- post WW2

1960’s -70’s -- ICPSR & academic archives

1970’s -- growth of data oriented professional associations (IASSIST, APDU, IFDO, CESSDA)

Focused on society and social norms

Predict outcomes; test assumptions; study change over time; run experiments

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Note: in any discipline we also need to understand the work flow of the research and the way individuals approach their work.

CURATION GOALS

Researcher driven philosophy of open access, data sharing, reuse

Collaborative, multi-unit or multi-institutional

Ensure data conservation and long term usability, as well as discovery and access

Processes and work flows support disaster planning

Use of best and trusted digital repository policies, models, practices, and work flows

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POLICIES SUPPORT PRACTICE

Foundational, essential to a strong data curation infrastructure.

Encompasses what is acquired/collected, curation levels and scope, ensures long term usability, drives processes and work flows

Social Science Data Archive policy

TOOL : Policy-making for Research Data in Repositories by Ann Green, Stuart Macdonald and Robin Rice.

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OUR STEPS IN CURATION

Initial contact

Data Quality Review and Appraisal

Ingest Verification Metadata Physical storage

Access

Preservation

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INITIAL CONTACT

Data Curation Profile

Data Management Plan

Guide to Social Science Data Preparation and Archiving

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APPRAISAL

Archival Collection Policy

Also depends on:

Resources to process

Long term resources

Fitness, usefulness

Data Deposit Form signatures and completeness; commitment to share data; privacy and confidentiality

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DATA QUALITY REVIEW

Use of statistical packages, emulator, Adobe Pro, Excel, Colectica, Text editor

Verify deposit package, check sums, freq’s, compare data to documentation

Completeness of codebook, question text, sampling, weighting, recodes, methods

Disclosure analysis, check for personal identifiers and assess privacy/confidentiality of respondents

Documentation converted to PDF/A

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EXAMPLE: WHAT KIND OF DATA?

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CODEBOOK DOCUMENTS THE

COLUMNS

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5002 01 01 302000 001 101 10004B121068965

Each item is called a variable. We refer to the numeric content of each item as a value.

COMPARE FREQS TO CODEBOOK

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VALUES VALUE LABELS

VARIABLE

RUN MARGINALS/FREQUENCIES

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Sex of Respondent Frequency Percent Valid Percent Cumulative Percent Valid MALE 856 45.1 45.1 45.1 FEMALE 1041 54.9 54.9 100.0 Total 1897 100.0 100.0 What is your race - ethnicity Frequency Percent Valid Percent Cumulative Percent Valid White 618 32.6 32.6 32.6 Hispanic 475 25.0 25.0 57.6 Black 474 25.0 25.0 82.6 Asian or Pacific Islander 282 14.9 14.9 97.5 Native American or Alaskan native 17 .9 .9 98.4 Identifies more than one of the above groups 20 1.1 1.1 99.4 DON'T KNOW 2 .1 .1 99.5 REFUSED 9 .5 .5 100.0 Total 1897 100.0 100.0

INGEST – PHYSICAL FORMATS

Virus check, run check sums, address versioning, fixity, file naming conventions

Convert files to archival formats if required

Back copies to external media

Copy datasets to Dataverse; Safe Archive tool

Use of secure file transfer client

SQL/PHP scripts for local holdings file

Compression software (7-zip)

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Address disaster plan and file access (public and local); Security requirements; LOCKSS

INGEST– BIBLIOGRAPHIC METADATA

Bibliographic metadata enables search and discovery:

Establish bibliographic-level identity for unique items

Bibliographic record to WorldCat/Voyager

Add record to holdings database (SQL)

Create Dataverse record; Assign persistent identifier

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Produce and review with investigator

WHAT ELSE DO WE NEED TO

KNOW ABOUT THE DATA?

Description of the study

Citation

Funding source

Methodology

Sampling

Publications

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EXAMPLE - DATAVERSE

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Links to tools to manage collections

Navigate to and search for studies

Studies can be downloaded or analyzed online

VARIABLE LEVEL SEARCH

CAPABILITIES

Enables searching across many studies at once.

Enables searching shared catalogs of multiple archives

TOOLS: Colectica Repository and NESSTAR

Requires local or remote hosting of software.

Can share the metadata files for repurposing.

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DATA DOCUMENTATION

INITIATIVE

Document, Discover, and Interoperate

“International standard for describing data that result from observational methods in the social, behavioral, economic, and health sciences”

“Facilitates interpretation and understanding -- both by humans and computers”

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INGEST-VARIABLE LEVEL METADATA

Descriptive metadata of detailed information about the data enables understandability and reuse:

Create variable-level metadata, using Colectica or NESSTAR to produce standardized metadata records

Create DDI record; full DDI codebook

Migrate DDI to Colectica Repository

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Produce and review with investigator

NESSTAR

EXAMPLE - IMPORTING DATA

Use the Data tab to import files from SPSS or STATA formats.

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Label

Question

text

Numeric

values

Variable Details include variable name, label, description or question text, and types of coding.

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EXAMPLE DDI FROM COLECTICA

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DDI fields are in red; used to create documentation; can be repurposed

PRESERVATION AND CURATION

Continuous monitoring of file formats; migrate to new formats when: New operating system; New version of statistical software New mode of file transfer; Code change

Monitoring of database function; software updates or redesigns

Monitoring of servers, external media health; replace as needed

Data forensics; check sums; validation; authentication; version control; format migration; refresh media; record preservation metadata -- DDI

Review disaster plan and collection policy at regular intervals

Review new or revised regulations for intellectual property; security; data producers/distributors; funding agencies

Review with original depositor, their data management plans, changes in access or user permissions

26 Focus is on functional-level preservation and long term usability through use of DDI and continuous review.

UNCOMFORTABLE TRUTHS

Data management in institutions requires high level administrative participation; new, sustained funding; and differently trained staff

Data management planning is not a static event but a continuous process to ensure long term independently understandable informed reuse of research

There is an urgent need for standards, tools, and best practice models for many different file formats and disciplines

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NEXT STEPS FOR PRACTITIONERS

“Crucial metadata about data are not always being captured or created and linked to data in repositories. Storage and persistence of data submissions isn't enough. We need data archivists and librarians to commit to partnering with researchers to curate data -- to review incoming data for usability, confidentiality, and completeness of descriptive information.”

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Ann Green (2016) Email communication Used with permission

ANY QUESTIONS?

THANK YOU!

Social Science Data Archive, UCLA

Box 951484 Los Angeles, CA 90095-1484 310-825-0716

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LINKS

Social Science Data Archive dataverse.harvard.edu/dataverse/ssda_ucla

Data Seal of Approval www.datasealofapproval.org/en/

National Digital Stewardship Alliance ndsa.org/activities/levels-of-digital-preservation/

Open Archival Information System www.oclc.org/research/publications/library/2000/lavoie-oais.html

Social Science Data Archive Policy data-archive.library.ucla.edu/SSDA_collectionAndArchivingPolicy.pdf?_ga= 1.3255478.786669706.1378228281

Data Curation Profile datacurationprofiles.org/

Data Management Planning at ICPSR www.icpsr.umich.edu/icpsrweb/content/datamanagement/dmp/index.html

ICPSR Guide to Data Preparation www.icpsr.umich.edu/icpsrweb/content/deposit/guide/

Colectica www.colectica.com/

NESSTAR www.nesstar.com/index.html

DDI www.ddialliance.org/

Dataverse dataverse.org/

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