Data underlying research paper “Developing an open data intermediation business model: insights from the case of Esri”

by Ashraf Shaharudin, Bastiaan van Loenen, and Marijn Janssen from Delft University of Technology (TU Delft), the Netherlands.

This folder contains data underlying the research paper “Developing an open data intermediation business model: insights from the case of Esri”. It consists of:

1. De-identified interview transcripts

2. Informed consent form template

Note about the de-identified interview transcripts:

The de-identified interview transcripts should be read in the context of the research on open data ecosystem and the role of Esri as open data intermediaries.

The 27 interviews, involving 29 interviewees, were conducted between April 2023 and April 2024 based on the semi-structured approach. We shared the tentative interview questions with the interviewees in advance (for the majority, at least three working days prior). Since they are semi-structured interviews, the ultimate interview questions may differ from the tentative questions.

We removed personally identifiable information from the transcripts. Some interviewees may risk being identifiable if their organization is known. Hence, we removed the organization and country information from all transcripts.

With verbal communication, some sentences may be less incomprehensible in writing. Thus, we did minimal edits when transcribing to improve the comprehensibility where necessary, but the main objective was to keep the transcripts as close to verbatim as possible.

Note about the informed consent form template:

We sent the informed consent form to every interviewee in advance and requested that they return it to us before or during the interview.

All interviewees whose interview transcripts are recorded in this document give permission for the anonymized transcript of their interview, with personally identifiable information redacted, to be shared in 4TU.ResearchData repository so it can be used for future research and learning.

Acknowledgement:

This research is part of the 'Towards a Sustainable Open Data ECOsystem' (ODECO) project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955569. The opinions expressed in this document reflect only the author’s view and in no way reflect the European Commission’s opinions. The European Commission is not responsible for any use that may be made of the information it contains.

The WISERD locality research programme comprised a series of locality studies, carried out by six full-time researchers, based in Aberystwyth, Bangor, and Cardiff Universities. The Locality Research Programme had five key aims: i) providing a way of researching the imagined and material experiences of stakeholders and communities; ii) examining the processes and practices of devolution in sub-national settings; iii) acting as an interface with policy stakeholders in different parts of Wales; iv) gaining a unique research and policy insight through mixed methods and integrated spatial data concerns; v) contributing to methodological development and research capacity building. A total of 120 interviews were undertaken with key actors across seven unitary authorities within three localities (Heads of the Valleys (Cardiff locality) - principally the Unitary Authorities of Merthyr Tydfil, Rhondda Cynon Taf and Blaenau Gwent); Ceredigion and Pembrokeshire coast (Aberystwyth locality) - including Montgomeryshire (North Powys); and North Wales (Bangor locality) along the A44 corridor(the Unitary Authorities of Gwynedd and Wrexham). Interviews were completed in two tiers: Tier 1: Unitary Authority senior management; Tier 2: managers in other bodies with responsibility for service delivery. The number of interviews per locality and tier is below: Aberystwyth Locality Ceredigion Tier 1 8 interviews Ceredigion Tier 2 5 interviews Pembrokeshire Tier 1 7 interviews Pembrokeshire Tier 2 3 interviews Other Tier 1 1 interview Other 2 12 interviews Bangor Locality Gwynedd Tier 1 6 interviews Gwynedd Tier 2 16 interviews Wrexham Tier 1 8 interviews Wrexham Tier 2 5 interviews Cardiff Locality Blaenau Gwent Tier 1 6 interviews Blaenau Gwent Tier 2 5 interviews Merthyr Tydfil Tier 1 5 interviews Merthyr Tydfil Tier 2 5 interviews Rhondda Cynon Taf Tier 1 9 interviews Rhondda Cynon Taf Tier 2 11 interviews Other Tier 2 8 interviews The interviews were based around the following 8 themes 1. Education and young people 2. Crime, public space and policing 3. Health, well-being and social care 4. Language, citizenship and identity 5. Employment and training 6. Environment, tourism and leisure 7. Economic development and regeneration 8. Housing and transport. The questions and themes asked are in the following interview schedule: Section 1: Stakeholder identity We are interviewing you with regard your role/job as …. Can you describe your job? What do you do? How did you get in to your current role? Who do you engage with and why? What does success look like in your role? Where do you see yourself in three or four years’ time? Section 2: Stakeholder perceptions of place/locality What’s your patch? Who are the people you work with - what are their patches? How does your [patch] relate to those [patches]? (relationality across scales) Are there any other key relationships to your [patch] and for your role? What is your [patch] like now? If you had to describe it someone who has not been here, how would you describe it? In what way is this place different to others? What are people like in the [patch]? Ask about ‘good’ areas and ‘bad’ areas Are there differences within the [patch]? How has [patch] changed? For better for worse? How have different parts of the [patch] been affected differently? Or, if no differences described above: Is this the case across [patch]? How have people coped? How haven’t they coped? (Coping strategies: how have people adapted their lives to these issues?) How do you think the needs of [patch] will change in the future? What has impacted on changes in your [patch]? How have you come to know this? (what patch is like now and how it has changed and how it will change) Do you do any data collection on this? Difference between personal and professional know ledges (e.g. I have lived here all my life OR I have talked to these people with work) What information / data would you like to know but don’t, how would this improve your capacity to do your job? Why don’t you have this data (does it exist; do they have access)? How can this be changed? What are the key issues that are going on here? And how does this relate to other places? Follow up on issues How do you know this? How do these issues impact + and - on the lives of those in the locality? What was/is your role in helping to address or maintain these issues? Other people’s roles in helping to address or maintain these issues. Barriers and facilitators to helping address or sustain them. Section 3: Power and resources Who makes decisions that affect your patch What are the crucial resources for you to conduct your work? To what extent are these available? Where do you get resources from? How could resource availability be better? How does the availability of resources impact on success? – what is available what is lacking and sharing and competition over these resources? To what extent can people affect decisions about their locality? Who? How? Which decisions? To what extent? Is this the case across the [patch]? Refer back to their definition of success – what are the barriers and facilitators to achieving this? What is Wales? What issues do you think will be the key things for us to follow and what would you hope would be the result of this? The interviews were recorded on digital recorders, transcribed by a professional company and checked by researchers. The quality of a) interviews and b) transcripts vary to some degree across the corpus. Some interviews are longer and fuller than others; some transcripts are closely and some more loosely transcribed. Placenames in the text were geo-parsed and geo-coded to six digit OS national grid references by researchers. These were then used to create GIS shapefiles of points of places mentioned in the transcripts There are two parts to data for this work: RESTRICTED and UNRESTRICTED. The RESTRICTED data (which are NOT available) comprise: • 135 audio files of the localities interviews • 120 non-anonymised interview transcripts • 120 consent forms for each interview • Excel files containing useful but potentially disclosive information on the interviews (eg interviews name; position; contact details; length of interview in minutes; number of pages of transcript etc). The UNRESTRICTED data comprises: • Locality GIS boundary data – GIS shapefiles of the boundaries of each (3) locality area • Locality interview place name GIS data containing: o 120 GIS shapefiles of point data of places mentioned in each interview. o 80 GIS polygon ellipse shapefiles of places mentioned in each interview generated from the point data. This has been categorised by theme (8) and Unitary Authority (a total of 7) in each Locality (3). o 80 GIS spatial mean point shapefiles of places mentioned in each interview generated from the point data. This has been categorised by theme (8) and Unitary Authority (total of 7) in each Locality (3). • 120 anonymised interview transcripts • Excel files containing useful non-disclosive information on the interviews (eg length of interview in minutes; number of pages of transcript etc) Contents of the UNRESTRICTED folder can be shared (with the acknowledgement of WISERD)

Tags survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES Summary BES Research, Applications, and Education Description Geocoded for Baltimore County. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey. This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because of its higher spatial accuracy than other databases describing US Cen... Visit https://dataone.org/datasets/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F336%2F610 for complete metadata about this dataset.