Genuine Information Needs of Social Scientists Looking for Data
Andrea Papenmeier, Thomas Krämer, Tanja Friedrich, Daniel Hienert, Dagmar Kern
Abstract
Publishing research data is widely expected to increase its reuse and to inspire new research. In the social sciences, data from surveys, interviews, polls, and statistics are primary resources for research. There is a long tradition to collect and offer research data in data archives and online repositories. Researchers use these systems to identify data relevant to their research. However, especially in data search, users' complex information needs seem to collide with the capabilities of data search systems. The search capabilities, in turn, depend to a high degree upon the metadata schemes used to describe the data. In this research, we conducted an online survey with 72 social science researchers who expressed their individual information needs for research data like they would do when asking a colleague for help. We analyzed these information needs and attributed their different components to the categories: topic, metadata, and intention. We compared these categories and their content to existing metadata models of research data and the search and filter opportunities offered in existing data search systems. We found a mismatch between what users have as a requirement for their data and what is offered on metadata level and search system possibilities.
Create a lesson
Related papers
Incremental Pooled LLM Evaluation for Cost-Effective Retrieval Model Selection
Max Nelson, Hanoz Bhathena, Aviral Joshi et al.
Recommender System as Slow and Fast Thinkers
Zichen Yuan, Xiaoxuan Dong, Linkun Dai et al.
Training seeds and model-selection stability in recommender-system evaluation
Juan Manuel Rodriguez, Oleg Lesota, Antonela Tommasel
ViSAR: Training-Free Adaptive-k Retrieval for Visual Document Question Answering
Adrien Mialland, Marc Plantevit, Julien Gallois et al.
Adaptive Test-Time Inference for Text2Cypher with Trace Budgeting and Selective Refinement
Makbule Gulcin Ozsoy
Counter-GEO-Bench: Evaluating Defenses Against Information-Distorting Generative Engine Optimization
Bing Zheng, Zongyao Zhao, Wenming Yang