Information integration (II) (also called information fusion, deduplication

Data deduplication

In computing, data deduplication is a specialized data compression technique for eliminating coarse-grained redundant data. The technique is used to improve storage utilization and can also be applied to network data transfers to reduce the number of bytes that must be sent across a link...

 and referential integrity

Referential integrity

Referential integrity is a property of data which, when satisfied, requires every value of one attribute of a relation to exist as a value of another attribute in a different relation ....

) is the merging of information from disparate sources with differing conceptual, contextual and typographical representations. It is used in data mining

Data mining

Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...

 and consolidation of data from unstructured or semi-structured resources. Typically, information integration refers to textual representations of knowledge but is sometimes applied to rich-media content.

The technologies

Technology

Technology is the making, usage, and knowledge of tools, machines, techniques, crafts, systems or methods of organization in order to solve a problem or perform a specific function. It can also refer to the collection of such tools, machinery, and procedures. The word technology comes ;...

 available to integrate information include string metrics which allow the detection of similar text in different data sources by fuzzy matching.

See also

• Data fusion
  Data fusion
  Data fusion, is generally defined as the use of techniques that combine data from multiple sources and gather that information into discrete, actionable items in order to achieve inferences, which will be more efficient and narrowly tailored than if they were achieved by means of disparate...
  
   (is a subset of Information fusion)
• Sensor fusion
  Sensor fusion
  Sensor fusion is the combining of sensory data or data derived from sensory data from disparate sources such that the resulting information is in some sense better than would be possible when these sources were used individually...
  
  
• Data integration
  Data integration
  Data integration involves combining data residing in different sources and providing users with a unified view of these data.This process becomes significant in a variety of situations, which include both commercial and scientific domains...
  
  
• Data deduplication
  Data deduplication
  In computing, data deduplication is a specialized data compression technique for eliminating coarse-grained redundant data. The technique is used to improve storage utilization and can also be applied to network data transfers to reduce the number of bytes that must be sent across a link...
  
  
• Dataspaces
  Dataspaces
  Dataspaces are an abstraction in data management that aim to overcome some of the problems encountered in data integration system. The aim is to reduce the effort required to set up a data integration system by relying on existing matching and mapping generation techniques, and to improve the...
  
  
• Referential integrity
  Referential integrity
  Referential integrity is a property of data which, when satisfied, requires every value of one attribute of a relation to exist as a value of another attribute in a different relation ....
  
  

General references

1. Dave L. Hall and James Llinas, “Introduction to Multisensor Data Fusion”, Proc. of IEEE , Vol. 85, No. 1, pp. 6 – 23, Jan 1997.
2. Erik Blasch, Ivan Kadar, John Salerno, Mieczyslaw Kokar, Subrata Das, Gerald Powell, Daniel Corkill, and E. Euspini (2006), Issues and Challenges in Situation Assessment (Level 2 Fusion), Journal of Advances in Information Fusion, Vol 1, No 2, Dec. 2006.

Books

• Liggins, Martin E., David L. Hall, and James Llinas. Multisensor Data Fusion, Second Edition Theory and Practice (Multisensor Data Fusion). CRC, 2008. ISBN 978-1-4200-5308-1
• David L. Hall, Sonya A. H. McMullen, Mathematical Techniques in Multisensor Data Fusion (2004), ISBN 1580533353
• Springer, Information Fusion in Data Mining (2003), ISBN 3540006761
• H. B. Mitchell, Multi-sensor Data Fusion – An Introduction (2007) Springer-Verlag, Berlin, ISBN 9783540714637
• S. Das, High-Level Data Fusion (2008), Artech House Publishers, Norwood, MA, ISBN 9781596932814 and 1596932813

External links

• A historical perspective on developing foundations for privacy-friendly client cloud computing: iConsult(TM) Apps using iInfo(TM) Information Integration for iOrgs(TM) Information Systems arXiv:0901.4934.
• Information Integration Using Logical View LNCS 1997.
• International Society of Information Fusion