Book extract 2021 (7): Linking data – using semantic technologies

Do you know the fallacy of disconnected data? It goes something like this: (chap. 6.3 Data management)

“Most organizations are full to bursting with databases specifically designed to support one application or another. There is also data in documents, spreadsheets and other data stores, and it is simply a matter of convenience that most of this data is not available to other parts of an organization. Buy the right tool (or hire enough open source developers to build the right tool ) and you reach digital nirvana.”

“That just doesn’t accomplish much. Why?
● Synchronizing existing data systems is difficult, costly, and typically yields very little return on investment.
● Each system has different representations of the “same” conceptual data, and in many cases these representations differ significantly from one system to another.
● The identity of objects is rarely consistent within an organization from one system to the next, let alone from one organization to the next.
● Data warehousing or data lakes, while an important requirement in data management, only solve a plumbing problem and very rarely solve the more complex context and language problem in specific business contexts.”

Semantic technologies combined with “knowledge engineering” can remedy this situation: cf. chap. Networked data management with semantic technologies

“From a strategic perspective, a shift is taking place in data management, away from document- or dossier-centric management to data-centric management supported by a semantic
Knowledge representation; i.e., specifically, data strategists are saying goodbye to folder-based file systems, hierarchical classifications, and repositories, in favor of hyperlinked structures. … (read more in the Practical Guide on p. 257)



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