Mapping interview transcript records: theoretical, technical and

cartographic challenges

CCRI Gloucester University

14.02.2013

Dr Scott Orford WISERD, Cardiff University

Overview

• Background to research

• Geo-tagging interview transcripts

• Geo-visualization and mapping

• Spatial metrics

• Some emerging issues

• Use of QGIS in localities research

• Conclusions

WISERD

WISERD

• Major investment in research infrastructure in Economic and Social

Sciences across Wales

• Major innovations in qualitative, quantitative and mixed methods

• Establish flexible and integrated sets of data relating to Wales

• Strategy for generating research grant bids and sustainability

• Links with WAG, ONS and Local Authorities across Wales

• Links with Other Centres and Programmes in Cardiff

Emerging research

• Collaborative Qualitative GIS research project involving both GI professionals and qualitative researchers from backgrounds with little association with spatial literacy or mapping

• Attempt to understand the different geographies that policy makers make use of in their day-to-day work

• Context of Welsh devolution where some policy areas devolved to WG some still remit of Westminster

• Provide empirical support to theoretical concepts of relational space (Jones, 2009)

• GIS augmented traditional qualitative analytical methods

Locating the research

Conventional

GIS Qual-GIS

Spatial

Humanities “Visual GISting”

(Gregory & Hardie,

2011)

WISERD Localities

Central and West Coast Region (Aberystwyth)

A55 Corridor (Bangor)

Heads of Valleys (Cardiff)

Interviews

• In-depth interview 120 stakeholders across 3 localities who have links to 8 policy areas

Crime, public space & policing Education and young people

Language, citizenship & identity Environment, tourism and leisure

Health, wellbeing and social care Economic development and regeneration

Housing and transport Employment and training

Transcipts

• Interviews recorded and transcribed by professional company

• Analysed in CAQDAS package (Atlas.ti)

• Parsed through qualitative meta-data generator using Web Services to geo-tag places and semantically tag words

Min Max Ave Std

Pages 11 235 34 25

Words 4828 48301 12306 5942

WISERD Qualitative meta-data generator

Linked to ESDA Qual-GIS

(WISERD GeoPortal)

GIS tools &

Spatial search

Text

search

Map layers

User account

management Full metadata

Reporting for surveys

Innovative metadata

visualisation for

qualitative data (here

showing word clouds

and place name

charting)

Part of WISERD GeoPortal

Status bar

Qualitative

data mapping

(place names

in interview

transcripts)

• Place names geo-tagged with page, line number and word number in transcript

• Also, all transcripts manually geo-tagged to allow success of automated geo-tagging to be evaluated

Geo-tagging

• Place names in the transcripts identified and extracted with page and line number

• geo-tagged to a single point using the OS 1:50,000 scale gazetteer

Place names Min Max Ave Std

Counts 8 269 73 48

% words 0.60 0.27 0.60 0.27

Ave per page 0.42 8.00 2.43 1.46

Problems of geo-tagging

place names (Southall, et al. 2011)

• Identifying place names in transcripts

• Place name spelling mistakes in transcripts (esp Welsh place names)

• Vernacular names with no official geography

• Confounding place names with different geographical features

• Multiple places with the same name (geotag)

GeoVisualization

• Geo-visualization is an important aspect of Qualitative GIS and a function that has been used to justify and promote its use (Knigge & Cope, 2009)

Conventional dot mapping using proportional sized circles for each place mentioned in the transcripts

A kernel density surface of the places mentioned in the transcripts of all the stakeholders from the local authority of Ceredigion

Centrographic Maps where point locations are replaced by statistical summaries of the locations such as standard deviational ellipses and mean centres

Spatial Metrics

• GIS allows the construction of basic spatial metrics

• Can augment quantitative measures generated through analysis of coding of interview transcripts

• Provide support for discursive narratives of geographical themes in transcripts

Percentage of places mentioned in each Local Authority according to the local authority of the

stakeholder interviewee

Welsh Local

Authorities

Blaenau

Gwent Ceredigion Gwynedd

Merthyr

Tydfil Pembrokeshire

Cynon

Taff Wrexham

Blaenau Gwent 62.6 3.9 1.6

Ceredigion 0.5 66.3 1.2 1.5 8.7 3.2

Gwynedd 2.4 63.8 0.3 0.2 0.3 4.0

Merthyr Tydfil 2.7 0.6 71.2 7.9

Pembrokeshire 2.4 12.6 0.5 0.5 75.4 0.8

Rhondda Cynon

Taff 3.7 7.5 60.2

Wrexham 0.5 4.3 1.0 73.8

Average Euclidean distances from centre of Local Authority to places mentioned in transcript

Local Authority

Locality Mean (km)

Standard

Deviation

Count

(places)

Merthyr Tydfill C

11 24 584

Rhondda Cynon Taff

C

15 23 1044

Wrexham B

16 35 321

Blaenau Gwent C

17 36 751

Ceredigion A

30 33 704

Pembrokeshire A

34 39 423

Gwynedd B

37 37 1002

Average Euclidean distances from centre of Local Authority to places mentioned in transcript

Policy Area Mean (km)

Standard

Deviation Count Crime, public space and policing 15 23 69 Language, citizenship and identity 21 32 121 Health, wellbeing and social care 23 27 68

Housing and transport 27 29 116

Employment and training 28 29 83

Education and young people 42 37 247

All Policy Areas 30 33 704

Discussions • QGIS negotiate issues such as data sharing, confidentiality,

disclosure and what can and cannot be presented to people outside of the team.

• Added value to conventional qualitative analysis

• Value of the spatial metrics that could not be created in the CAQDAS

• Some spatial patterns uncovered in CAQDAS analysis but only treated discursively

• Cannot analyse or interpret maps / spatial metrics in isolation of transcripts or context of interview -

complimenting qualitative research (mixed methods) • What is relevant in the geo-tagged data

Research Process

Interviewees

Transcripts

Geo-tagging

GIS Geo-visualisation /

spatial metrics

Future Research

• Analysis of automated geo-tagging software

• Development of non-disclosive cartographic techniques

• Further analysis of maps and spatial metrics and how they can be interpreted meaningfully in the context of interviews

• EQUALISA - transcript mapping and exploratory tool

Acknowledgements

• This paper is based on research supported by the Wales Institute of Social and Economic Research, Data and Methods (WISERD), funded by the Economic and Social Research Council (ESRC) (Grant Reference: RES-576-25-0021) and the Higher Education Funding Council for Wales (HEFCW)