Why Is Data Integration So Hard?
Reinhold Stahl and
Patricia Staab
Chapter Chapter 4 in Measuring the Data Universe, 2018, pp 23-33 from Springer
Abstract:
Abstract Data integration is a multi-step process, starting with the logical centralisation of data in a common system. Then, a common order system, a unified data modelling method, is established to enable automated handling of the data. A common understanding will then be achieved through semantic harmonisation. Data integration allows linking and subsequent processing of data from different sources. Essential for this is this three-step standardisation, which unfortunately has to overcome many obstacles. Some lie in the technology, some in the silo thinking of different parties involved. It may be concerns regarding privacy, or the lack of incentive due to seemingly low market potential. As a result, previous information technology standards for data were either industry-specific silo solutions or limited to a formal framework.
Date: 2018
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-76989-9_4
Ordering information: This item can be ordered from
http://www.springer.com/9783319769899
DOI: 10.1007/978-3-319-76989-9_4
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().