Abstract
Innovators Marketplace, a market-like workshop where cards showing existing pieces of knowledge in various domains are combined to create ideas of services/products and thrown into demand-driven communication to choose practical ideas, has been extended to a setting of the market of data. This extension is called Innovators Marketplace on Data Jackets, a workshop in which each prepared card called a data jacket represents the digest knowledge about a dataset, that is, a kind of metadata. Data jackets are disclosed, whereas the corresponding data are not, and participants of the workshop create ideas for combining and analyzing data using the visualized correlation of data jackets. In this chapter, this workshop is described as a systematic process for reasoning on incomplete models , where each data jacket is regarded as an incomplete local model in the domain of the data, and communication is launched for satisfying requirements in the market (regarded as incomplete global models) by restructuring and combining local models. The data jacket may initially include atoms and terms in the domain, not connected via complete causal relations. Via the communication, however, links including causal relations appear and are revised toward obtaining a glocal model corresponding to a solution to satisfy requirements in the marketplace. In this process, the local model corresponding to each element is also revised to obtain useful knowledge digesting the corresponding data.
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Abbreviations
- DJ:
-
data jacket
- EELD:
-
evidence extraction and link discovery
- FOL:
-
first-order logic
- KJ:
-
Kawakita Jiro
- MBR:
-
model-based reasoning
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Acknowledgements
This study has been supported by JST CREST, and discussions with Kozo Keikaku Engineering Inc. and other major collaborators have been reflected to this chapter.
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Ohsawa, Y., Hayashi, T., Kido, H. (2017). Restructuring Incomplete Models in Innovators Marketplace on Data Jackets. In: Magnani, L., Bertolotti, T. (eds) Springer Handbook of Model-Based Science. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-30526-4_48
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