Genuine Information Needs of Social Scientists Looking for Data

Papenmeier, Andrea; Krämer, Thomas; Friedrich, Tanja; Hienert, Daniel; Kern, Dagmar

doi:10.1002/pra2.457

Cited by 7 publications

(4 citation statements)

References 25 publications

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“…Bourke, 2022), and on studying with an analytical focus emerging practices of the workflows, including discovery (e.g. Ince et al 2022b;Papenmeier et al, 2021;Sun et al, 2022). In these studies, the user needs, whilst mentioned, are never or rarely a core focus and in conducting our review of the literature we had to extract and separate them from the analytical work of the authors.…”

Section: Discussionmentioning

confidence: 99%

“…This to an extent implies an increasing complexity in the tools and platforms for discovery, and again a need for integration (as seen also earlier), this time of technologies rather than resources. Papenmeier et al (2021) suggest that there is a mismatch between users' information needs and the capabilities of existing data search systems, particularly in the context of data discovery in the research workflow. This is based on an analysis of dataset requests and queries from 72 social scientists.…”

Section: Literature Reviewmentioning

confidence: 99%

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CoDesign for Discovery in Social Sciences and Humanities

De Paoli,

Forbes,

Andreini

et al. 2024

LIBER

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GoTriple is a novel discovery platform for Social Sciences and Humanities (SSH) in Europe. Discovery is a phase of research where scholars seek to locate resources for their work, such as publications or previous projects. The paper details the work done for involving the SSH community in the codesign of GoTriple, focusing on the research discovery activities. It is an investigation of the user needs and barriers toward digital discovery for the SSH community, conducted through codesign. This work encompassed interviews, a questionnaire, codesign workshops and evaluation activities. The paper reports on some outcomes for the codesign and how user needs were identified and served by novel designs supporting discovery for SSH. This process of design is both concerned with creating digital tools for discovery and with the creation of a community of users that could make the platform thrive. The main contribution of the work is therefore the identification of the user needs for digital discovery in SSH and a series of insights on the design with the user community. The paper comprises a report on how codesign principles do support such work.

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

CoDesign for Discovery in Social Sciences and Humanities

De Paoli,

Forbes,

Andreini

et al. 2024

LIBER

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show abstract

“…To evaluate the performance of the DataChat prototype, we generated and tested 105 natural language questions about ICPSR datasets. These questions were inspired by a prior study of “genuine information needs” (Papenmeier et al 2021) for specific social science data stakeholder perspectives from education, funding agencies, and data management units. These questions provide a preliminary evaluation of DataChat's overall ability and versatility.…”

Section: Preliminary Evaluationmentioning

confidence: 99%

DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization

Fan,

Lafia,

et al. 2023

Proceedings of the Association for Information Science and Tech

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Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter‐university Consortium for Political and Social Research (ICPSR), offer standardized metadata and search tools to support data search. Metadata standards emphasize the machine‐readability of data and its documentation. There are opportunities to enhance dataset search by improving users' ability to learn about, and make sense of, information about data. Prior research has shown that context and expertise are two main barriers users face in effectively searching for, evaluating, and deciding whether to reuse data. In this paper, we propose a novel chatbot‐based search system, DataChat, that leverages a graph database and a large language model to provide novel ways for users to interact with and search for research data. DataChat complements data archives' and institutional repositories' ongoing efforts to curate, preserve, and share research data for reuse by making it easier for users to explore and learn about available research data.

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“…However, existing systems do not tend to include explicit, contextual information about how data have been reused by others or curated, for example, in search indexes (Sun & Khoo, 2017). Generally, users' information needs are often far more detailed and expressive than the dataset search queries that they issue (Papenmeier et al, 2021). In this study, we analyze query logs to develop a baseline understanding of users' expressed information needs and search behaviors when seeking social science data.…”

Section: Introductionmentioning

confidence: 99%

Exploratory and directed search strategies at a social science data archive

Lafia,

Million,

Hemphill

2024

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Researchers need to be able to find, access, and use data to participate in open science. To understand how users search for research data, we analyzed textual queries issued at a large social science data archive, the Inter-university Consortium for Political and Social Research (ICPSR). We collected unique user queries from 988,475 user search sessions over four years (2012-16). Overall, we found that only 30% of site visitors entered search terms into the ICPSR website. We analyzed search strategies within these sessions by extending existing dataset search taxonomies to classify a subset of the 1,554 most popular queries. We identified five categories of commonly-issued queries: keyword-based (e.g., date, place, topic); name (e.g., study, series); identifier (e.g., study, series); author (e.g., institutional, individual); and type (e.g., file, format). While the dominant search strategy used short keywords to explore topics, directed searches for known items using study and series names were also common. We further distinguished exploratory browsing from directed search queries based on their page views, refinements, search depth, duration, and length. Directed queries were longer (i.e., they had more words), while sessions with exploratory queries had more refinements and associated page views. By comparing search interactions at ICPSR to other natural language interactions in similar web search contexts, we conclude that dataset search at ICPSR is underutilized. We envision how alternative search paradigms, such as those enabled by recommender systems, can enhance dataset search.

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Genuine Information Needs of Social Scientists Looking for Data

Cited by 7 publications

References 25 publications

CoDesign for Discovery in Social Sciences and Humanities

CoDesign for Discovery in Social Sciences and Humanities

DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization

Exploratory and directed search strategies at a social science data archive

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