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Living objects: towards flexible big data sharing
Keywords:
Data sharing, Data control, Offloading, Enrichment, Persistent objects, Data as a Service (DaaS), Big dataAbstract
Data sharing and especially enabling third parties to build new services using large amounts of shared data is clearly a trend for the future and a main driver for innovation. However, sharing data is a challenging and involved process today: The owner of the data wants to maintain full and immediate control on what can be done with it, while users are interested in offering new services which may involve arbitrary and complex processing over large volumes of data. Currently, flexibility in building applications can only be achieved with public or non-sensitive data, which is released without restrictions. In contrast, if the data provider wants to impose conditions on how data is used, access to data is centralized and only predefined functions are provided to the users. We advocate for an alternative that takes the best of both worlds: distributing control on data among the data itself to provide flexibility to consumers. To this end, we exploit the well-known concept of object, an abstraction that couples data and code, and make it act and react according to the circumstances.
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Published
2013-10-01
How to Cite
Marti, J., Queralt, A., Gasull, D., & Cortes, T. (2013). Living objects: towards flexible big data sharing. Journal of Computer Science and Technology, 13(02), p. 56–63. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/611
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Invited Articles
