2026-04-29T02:54:13Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

8e1cf57df4eb90d58a631ed5efb868f9773b1816543a79abb7107afefc43abd1 2025-06-17T03:14:07Z language:enopenaire_data

DDI study level documentation for study 10.7802/1.1943 Looking for data (Expert interviews) Looking for data (Expert interviews) Looking for data (Expert interviews) 10.7802/1.194310.7802/1.194310.7802/1.194310.7802/1.1943 Friedrich, Tanja Friedrich, Tanja GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften information retrievalsurvey researchinformation retrievalsurvey research These interview data are part of the project "Looking for data: information seeking behaviour of survey data users", a study of secondary data users’ information-seeking behaviour. The overall goal of this study was to create evidence of actual information practices of users of one particular retrieval system for social science data in order to inform the development of research data infrastructures that facilitate data sharing. In the project, data were collected based on a mixed methods design. The research design included a qualitative study in the form of expert interviews and – building on the results found therein – a quantitative web survey of secondary survey data users. For the qualitative study, expert interviews with six reference persons of a large social science data archive have been conducted. They were interviewed in their role as intermediaries who provide guidance for secondary users of survey data. The knowledge from their reference work was expected to provide a condensed view of goals, practices, and problems of people who are looking for survey data. The anonymized transcripts of these interviews are provided here. They can be reviewed or reused upon request. The survey dataset from the quantitative study of secondary survey data users is downloadable through this data archive after registration. The core result of the Looking for data study is that community involvement plays a pivotal role in survey data seeking. The analyses show that survey data communities are an important determinant in survey data users' information seeking behaviour and that community involvement facilitates data seeking and has the capacity of reducing problems or barriers. The qualitative part of the study was designed and conducted using constructivist grounded theory methodology as introduced by Kathy Charmaz (2014). In line with grounded theory methodology, the interviews did not follow a fixed set of questions, but were conducted based on a guide that included areas of exploration with tentative questions. This interview guide can be obtained together with the transcript. For the Looking for data project, the data were coded and scrutinized by constant comparison, as proposed by grounded theory methodology. This analysis resulted in core categories that make up the "theory of problem-solving by community involvement". This theory was exemplified in the quantitative part of the study. For this exemplification, the following hypotheses were drawn from the qualitative study: (1) The data seeking hypotheses: (1a) When looking for data, information seeking through personal contact is used more often than impersonal ways of information seeking. (1b) Ways of information seeking (personal or impersonal) differ with experience. (2) The experience hypotheses: (2a) Experience is positively correlated with having ambitious goals. (2b) Experience is positively correlated with having more advanced requirements for data. (2c) Experience is positively correlated with having more specific problems with data. (3) The community involvement hypothesis: Experience is positively correlated with community involvement. (4) The problem solving hypothesis: Community involvement is positively correlated with problem solving strategies that require personal interactions.These interview data are part of the project "Looking for data: information seeking behaviour of survey data users", a study of secondary data users’ information-seeking behaviour. The overall goal of this study was to create evidence of actual information practices of users of one particular retrieval system for social science data in order to inform the development of research data infrastructures that facilitate data sharing. In the project, data were collected based on a mixed methods design. The research design included a qualitative study in the form of expert interviews and – building on the results found therein – a quantitative web survey of secondary survey data users. For the qualitative study, expert interviews with six reference persons of a large social science data archive have been conducted. They were interviewed in their role as intermediaries who provide guidance for secondary users of survey data. The knowledge from their reference work was expected to provide a condensed view of goals, practices, and problems of people who are looking for survey data. The anonymized transcripts of these interviews are provided here. They can be reviewed or reused upon request. The survey dataset from the quantitative study of secondary survey data users is downloadable through this data archive after registration. The core result of the Looking for data study is that community involvement plays a pivotal role in survey data seeking. The analyses show that survey data communities are an important determinant in survey data users' information seeking behaviour and that community involvement facilitates data seeking and has the capacity of reducing problems or barriers. The qualitative part of the study was designed and conducted using constructivist grounded theory methodology as introduced by Kathy Charmaz (2014). In line with grounded theory methodology, the interviews did not follow a fixed set of questions, but were conducted based on a guide that included areas of exploration with tentative questions. This interview guide can be obtained together with the transcript. For the Looking for data project, the data were coded and scrutinized by constant comparison, as proposed by grounded theory methodology. This analysis resulted in core categories that make up the "theory of problem-solving by community involvement". This theory was exemplified in the quantitative part of the study. For this exemplification, the following hypotheses were drawn from the qualitative study: (1) The data seeking hypotheses: (1a) When looking for data, information seeking through personal contact is used more often than impersonal ways of information seeking. (1b) Ways of information seeking (personal or impersonal) differ with experience. (2) The experience hypotheses: (2a) Experience is positively correlated with having ambitious goals. (2b) Experience is positively correlated with having more advanced requirements for data. (2c) Experience is positively correlated with having more specific problems with data. (3) The community involvement hypothesis: Experience is positively correlated with community involvement. (4) The problem solving hypothesis: Community involvement is positively correlated with problem solving strategies that require personal interactions. GermanyGermany The experts interviewed in this study are reference staff from a social science data archive. cross-sectioncross-section Non-probability Sample - Purposive SampleNon-probability Sample - Purposive Sample Face-to-face interviewInterview.FaceToFacePersönliches InterviewInterview.FaceToFace Restricted Access - To get access to the research data, the original data depositor's consent is needed.Eingeschränkter Zugang - Für den Zugang zu den Forschungsdaten muss eine Einwilligung der Datengebenden eingeholt werden. http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_1.1943 2023-03-11 ddi:codebook:2_5