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Encyclopedia of Big Data Technologies pp 1–6Cite as

Data Fusion

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Introduction and Key Concepts of Information Fusion: Data, Models, and Context

Information fusion (IF) is a multi-domain-growing field aiming to provide data processes for situation understanding (Liggins et al. 2008). Globally, fusion systems aim to integrate sensor data and information/knowledge databases, contextual information, mission goals, etc., to describe dynamically changing situations. In a sense, the goal of information fusion is to obtain continuous refinements of estimates and assessments of a subset of the world based on partial observations and the evaluation of the need for additional sources or modification of the process itself, to achieve improved results.

The capability to fuse digital data and generate useful information is conditioned by the quality of inputs, whether device-derived or text-based. Data are generated in different formats, some of them unstructured and may be inaccurate, incomplete, ambiguous, or contradictory. The key aspect in modern DF...

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References

  • Amazon (2017) https://aws.amazon.com/. Accessed Oct 15th 2017

  • Bettini C, Brdiczka O, Henricksen K, Indulska J, Nicklas D (2010) A survey of context modelling and reasoning techniques. Pervasive Mob Comput 6(2):161–180

    Article  Google Scholar 

  • Biermann J, Garcia J, Krenc K, Nimier V, Rein K, Snidaro L (2014) Multi-level fusion of hard and soft information. 17th International Conference on Information Fusion, Salamanca. July 2014

    Google Scholar 

  • Biermann J, Garcia J, Krenc K, Nimier V, Rein K, Snidaro L (2016) Standardized representation via BML to support multi-level fusion of hard and soft information. Symposium IST/SET-216 Information Fusion (Hard and Soft) for Intelligence, Surveillance & Reconnaissance (ISR). Norfolk Virginia, USA 4, 5 May 2015

    Google Scholar 

  • Bishop C (2004) Pattern recognition and machine learning. Springer, New York

    MATH  Google Scholar 

  • Caragea C, McNeese N, Jaiswal A, Traylor G, Kim H-W, Mitra P, Wu D, Tapia A-H, Giles L, Jansen B-L, Yen J (2011) Classifying text messages for the Haiti earthquake. Proceedings of the 8th International ISCRAM Conference – Lisbon, Portugal, May 2011

    Google Scholar 

  • Gómez J, García J, Patricio MA, Molina JM, Llinas J (2011) High-level information fusion in visual sensor networks. In: Ang K-L, Seng K-P (eds) Information processing in wireless sensor networks: technology, trends and applications, IGI Global, Hershey, Pennsylvania

    Google Scholar 

  • Liggins M, Hall D, Llinas J (2008) Handbook of multisensor data fusion: theory and practice, 2nd edn. CRC Press, Boca Raton, Florida

    Google Scholar 

  • Microsoft (2017) https://cloud.microsoft.com/en-us/. Accessed Oct 15th 2017

  • Snidaro L, Garcia J, Corchado JM (2014) Guest editorial: context-based information fusion. Inf. Fusion, Special Issue on Context-Based Information Fusion, 2014

    Google Scholar 

  • Snidaro L, García J, Llinas J, Blasch E (2016) Context-enhanced information fusion. Boosting real-world performance with domain knowledge. Springer, Basel, Switzerland

    Google Scholar 

  • Steinberg A-N, Bowman C (2009) Revisions to the JDL data fusion model, Chap. 3. In: Liggins M, Hall D, Llinas J (eds) Handbook of multisensor data fusion. CRC Press, London, pp 45–68

    Google Scholar 

  • Szuster P, Molina J-M, Garcia J, Kolodziej J (2017) Data fusion in cloud computing: big data approach. European Conference on Modelling and Simulation, ECMS 2017, Budapest, Hungary, May 23–26, pp 569–575

    Google Scholar 

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Author information

Authors and Affiliations

  1. Applied Artificial Intelligence Group, Universidad Carlos III de Madrid, Colmenarejo, Spain

    Jesús Garcia, José Manuel Molina, Antonio Berlanga & Miguel Angel Patricio

  2. Computer Science and Engineering, Universidad Carlos III de Madrid, Colmenarejo, Spain

    Jesús Garcia, José Manuel Molina, Antonio Berlanga & Miguel Angel Patricio

Authors
  1. Jesús Garcia
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  2. José Manuel Molina
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  3. Antonio Berlanga
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  4. Miguel Angel Patricio
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Corresponding author

Correspondence to Jesús Garcia .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Sherif Sakr

  2. Sch of Info Techno, Building J12, University of Sydney Sch of Info Techno, Building J12, Sydney, Australia

    Albert Zomaya

Section Editor information

  1. Database Systems Group, Technische Universität Dresden, Dresden, Saxony, Deutschland

    Maik Thiele

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Garcia, J., Molina, J.M., Berlanga, A., Patricio, M.A. (2018). Data Fusion. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_5-1

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  • DOI: https://doi.org/10.1007/978-3-319-63962-8_5-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63962-8

  • Online ISBN: 978-3-319-63962-8

  • eBook Packages: Springer Reference MathematicsReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Data Fusion
    Published:
    24 May 2022

    DOI: https://doi.org/10.1007/978-3-319-63962-8_5-2

  2. Original

    Data Fusion
    Published:
    14 February 2018

    DOI: https://doi.org/10.1007/978-3-319-63962-8_5-1

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