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- Publisher
- Springer Journals
- Copyright
- Copyright © 2017 by Allerton Press, Inc.
- Subject
- Computer Science; Information Storage and Retrieval
- ISSN
- 0005-1055
- eISSN
- 1934-8371
- DOI
- 10.3103/S0005105517050028
- Publisher site
- See Article on Publisher Site
Abstract
Common approaches and technologies applied to digital data storage and processing in various disciplines are analyzed. It is shown that regardless of a specific subject area, working with large data set obtained as a result of experimenting or modeling requires similar methodological support, involving data curation, metadata support, and data genesis and quality annotation. The interdisciplinary field called “The properties of materials and substances” is analyzed as an example of a discipline that actively applies digital data. New approaches to the integration of data with heterogeneous properties that take into account structural data variations by the class of substances, the state of sample, experimental conditions, and other factors are investigated.
Journal
Automatic Documentation and Mathematical Linguistics – Springer Journals
Published: Dec 7, 2017