| 期刊全称 | Big Data Factories | | 期刊简称 | Collaborative Approa | | 影响因子2023 | Sorin Adam Matei,Nicolas Jullien,Sean P. Goggins | | 视频video | | | 发行地址 | Provides basic researchers and practitioners direct guidelines and best case scenarios for developing activities related to data factoring.Presents methods for teaching data factoring.Proposes a set o | | 学科分类 | Computational Social Sciences | | 图书封面 |  | | 影响因子 | The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as “data factoring” emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing..The book proposes a research-development agenda that can undergird an ideal data factory approach. Several programmatic chapters discuss specialized issues involved in data factoring (documentation, meta-data specification, building flexible, yet comprehensive data ontologies, usability issues involved in collaborative tools, etc.). The book also presents case studies for data factoring and processing that can lead to building better scientific collaboration and data sharing strategies and tools..Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related | | Pindex | Book 2017 |
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发表于 2025-3-21 16:35:12
