Data Leaves: Scenario-oriented Metadata for Data Federative Innovation
| Autor: | Ohsawa, Yukio, Sekiguchi, Kaira, Maekawa, Tomohide, Yamaguchi, Hiroki, Hyuk, Son Yeon, Kondo, Sae |
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| Rok vydání: | 2022 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | A method for representing the digest information of each dataset is proposed, oriented to the aid of innovative thoughts and the communication of data users who attempt to create valuable products, services, and business models using or combining datasets. Compared with methods for connecting datasets via shared attributes (i.e., variables), this method connects datasets via events, situations, or actions in a scenario that is supposed to be active in the real world. This method reflects the consideration of the fitness of each metadata to the feature concept, which is an abstract of the information or knowledge expected to be acquired from data; thus, the users of the data acquire practical knowledge that fits the requirements of real businesses and real life, as well as grounds for realistic application of AI technologies to data. Comment: 10 pages, 6 figures, 1 table |
| Databáze: | arXiv |
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