DAMES, 31/JAN/2012, T6

Opportunities and prospects in social research

Paul Lambert, 31st January 2012

Talk to the seminar ‘Data management in the social sciences and the contribution of the DAMES Node’, a session organised as part of the Data Management through e-Social Science ESRC research Node

www.dames.org.uk

DAMES, 31/JAN/2012, T6

Start by thinking big…

Landes’ (1969) analysis Knowledge-based revolutions Importance of standardising technology for cooperation

(not just creating it) Importance of access to underlying materials – coal, cotton, etc. Uneven development (nationally)

Landes, D.S. (1969). The Unbound Prometheus: Technological Change and Industrial Development in Western Europe from 1750 to the Present. Cambridge: Cambridge University Press.

Emergent uses of computing and the internet, such as in ‘e-Science’ traditions, arguably share similar characteristics

Standardisation, communication, vast volumes of resources Social research data, e.g. large scale surveys and other large

quantitative resources, exemplify these opportunities

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E-Social Science / Digital Social Research

ESRC & JISC initiatives as major UK investment in ‘e-social science’ technology (see www.digitalsocialresearch.net)

e-Science broadly involves using emergent computer technologies with enhanced capacities for communication/collaboration & data processing

Handling and displaying large volumes of complex data E.g. GeoVue; LifeGuide; DReSS; Obesity e-lab

Resources for computationally demanding analyses CQeSS; MoSeS; eStat; NeISS

Standards setting in collaboration, data preparation, data and research support – DRS; MeRC; OeSS; DAMES

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Example: Understanding New Forms of Digital Records (DReSS)

transcribed talk

audio video digital

records system logs

location transcript

code tree

video

system log

..more examples..(strategies for social scientists to tap into the e-Infrastructure)

E-Stat @

National e-Infrastructure for Social Simulation

• Expert led simulation demonstrations

• Combining data resources• Workflows for the simulation

analysis Modify and re-specify existing

simulation templates

www.neiss.org.uk

‘StatJR’ a tool to specify complex statistical models in generic / visual terms

Multilevel modelsMultiple data permutations and analytical alternatives

Ready access to a suite of complex modelling tools

www.bristol.ac.uk/cmm/research/estat/

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e-Science, data management, and research revolutions (!)

‘Data management through e-Social Science’ DAMES (2008-11) – developing services / resources using e-

Science approaches which will help social scientists in undertaking data management tasks

Information / data retrieval (e.g. GESDE systems) Storage and processing of data and metadata (e.g. secure portals

and ‘curation’ and ‘fusion’ tools) …’Data management’ is at the centre of transformations in

the exploitation of information resources… Collaboration / standardisation in constructing empirical results Facility to host and distribute new forms of data Facility to discriminate between the masses of data

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Prospects in social research

The changing terrain of social research and three exciting developments/frontiers: 1) Data access

2) Data management and analysis

3) Log books

Some thoughts on the trajectory of social research developments

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1) Access to data..

Example: Accessing surveys via UK Data Archive

Shibboleth authentication

Download and analyse in Stata, SPSS, etc

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Supplementary (digital) data

E.g. ‘Occupational information resources’ = data files within information on occupations, which can be usefully linked to micro-data about occupations

e.g. GEODE acts as a

library of OIRs,

www.geode.stir.ac.uk

Such resources are often

not widely known about,

but have the ability to

enhance analysis

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Steady accumulation of options / permutations / approaches in…

2a) Data Management

Pre-analysis (and re-analysis) routines

Sensitivity analysis Standardisation,

harmonisation

2b) Data Analysis

Descriptive tools Ongoing development of

complex analytical models

GLLMMs for structural data features, multi-process systems, etc

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E-Stat ebooks (image from doc in prep., Browne et al. 2011)

(Links to product from StatJR)

3) Log books

Software tools for logging work are increasingly well developed

See our workshops on documentation/replication

Other initiatives in sharing records of workE-Stat: Electronic workbooks for the data and model

building process MyExperiment: Depository for project files

These haven’t yet been extensively exploited in survey research – but they should be!

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The idea of workflows

Workflow modelling has an exciting future.. Workflow documentation

o MyExperiment [http://www.myexperiment.org/]o Social survey analysis

• Long, J.S. (2009) Workflow of Data Analysis using Stata. CRC press

At present…Tool development in processDepositing workflows might impose constraints/burdens

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Example of using MS Excel for workflow documentation in survey research

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Who will take the initiative?

Long, J. S. (2009). The Workflow of Data Analysis Using Stata. Boca Raton: CRC Press.1-5: Programming in Stata; 6: Cleaning your data; 7: Analysing data and

presenting results; 8: Protecting your work

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“Because claims in published papers that additional materails are “available from author” usually prove false, at least after a few months, the California Center for Population Research at UCLA recently implemented a mechanism by which additional materials, for example, -do- and –log- files, can be attached to papers posted in its Population Working Paper archive. Other research centers are to be encouraged to do the same”

(p404 of Treiman (2009) Quantitative Data Analysis. NY: Jossey Bass)

Bespoke solutions or the generic/dynamic approaches of e-Science?

Well-known challenges in survey research• We’re data rich, but analysts’ poor

• UK Data Forum (2007); Wiles et al (2009) (http://eprints.ncrm.ac.uk/810/) • Under-use of suitably complex statistical models

• Coordination and communication on data processing • Recodes / Standardisation / harmonisation / documentation

• Lack of generic/accessible representation of tasks• Limited disciplinary/project/researcher cross-over when dealing with data• Specific software orientations

These are not generally problems of scale, but of organisation

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‘Managed’ solutions?

• Data handling/analysis capacity-buildingESRC programmes (NCRM, RDI, RMP); training

workshops/materials; P/G funds; strategic research grant investment

• Documentation/replication policies

• Software for data access and analysisNESSTAR – UK Data Archive data/metadata browserLong (2009) on the Stata softwareRemote access to data (e.g. SDS)

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..train and/or constrain the analysts..

Train them ->

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..constrain the analysis..

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‘Social’ solutions?

Tools and infrastructure for better standards to are built up from within (aided by collaborative technologies)

E.g. GESDE, P-ADLS, MethodBox, www.methodbox.org

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Summary

e-Science would often be seen as about enabling effective research in conditions of abundant resources

In practical terms, for social researchers, this means navigating through the vast array of data and analytical resources, and undertaking robust and replicable work

Likely continuation of mix of generic and specific, managed and social, approaches

DAMES, 31/JAN/2012, T6