x-hub: An Infrastructure for the Multi-disciplinary Secondary Use of Data from Experimental Studies in Economics and Social Sciences, with a Focus on Benchmark and Large Groups Experiments
The experimental method is used in a rapidly increasing number of studies in both economics and the social sciences. These sub-disciplines share many topics - public goods, large groups, social preferences - and many theoretical puzzles. But latest findings are hardly visible across community borders. One consequence is that vastly different methodological approaches and criteria are applied, without much transparency about that circumstance. Therefore this project aims to establish an infrastructure that fosters transparency, replicability, and reuse of experimental data across disciplinary borders. Diverging methods and paradigms applicable to primary data sets shall become visible at first sight, such that researchers from any sub-discipline can find and evaluate the data and research under their particular disciplinary perspective. The basis for this will be provided by implementing core elements of any typical research data service unit. A data repository with a low threshold for new data deposits from experimental researchers will be established. Concepts for long-term archiving will be prepared. Metadata schemes will be defined and metadata created, initially taking the perspective of each involved discipline. Persistent identifiers will provide citable research data, and finally, the data will be made available to an international community for secondary use. The added value of using a multi-disciplinary approach will be realized by creating metadata of a 'higher order', which allows for different perspectives on the same data. The elements and the usefulness of the new infrastructure will be put to the test by archiving selected studies from experimental economics, experimental sociology and experimental political science that address research questions under the topic of large groups and benchmark experiments. Substantive and methodological research on the existing data will reveal gains that can be made by merging the experimental economics and social science research traditions. Therefore, a welcome side-benefit of the project will be the opportunity to evaluate the research yield of intensively curated data-sharing services in a real-life example.