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In recent years, rather than enclosing data within a single organization,exchanging and combining data from different domains has become an emergingpractice. Many studies have discussed the economic and utility value of dataand data exchange, but the characteristics of data that contribute to problemsolving through data combination have not been fully understood. In big dataand interdisciplinary data combinations, large-scale data with many variablesare expected to be used, and value is expected to be created by combining dataas much as possible. In this study, we conduct three experiments to investigatethe characteristics of data, focusing on the relationships between datacombinations and variables in each dataset, using empirical data shared by thelocal government. The results indicate that even datasets that have a fewvariables are frequently used to propose solutions for problem solving.Moreover, we found that even if the datasets in the solution do not have commonvariables, there are some well-established solutions to the problems. Thefindings of this study shed light on mechanisms behind data combination forproblem-solving involving multiple datasets and variables.

Data Combination for Problem-solving: A Case of an Open Data Exchange Platform