A3 Book section, Chapters in research books
Toward evolving knowledge ecosystems for big data understanding (2014)


Ermolayev, V., Akerkar, R., Terziyan, V., & Cochez, M. (2014). Toward evolving knowledge ecosystems for big data understanding. In R. Akerkar (Ed.), Big Data Computing (pp. 3-56). Taylor & Francis. https://doi.org/10.1201/b16014-3


JYU authors or editors


Publication details

All authors or editorsErmolayev, Vadim; Akerkar, Rajendra; Terziyan, Vagan; Cochez, Michael

Parent publicationBig Data Computing

Parent publication editorsAkerkar, Rajendra

ISBN978-1-4665-7837-1

Publication year2014

Pages range3-56

Number of pages in the book564

PublisherTaylor & Francis

Place of PublicationBoca Raton, FL

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1201/b16014-3

Publication open accessNot open

Publication channel open access


Abstract

Big Data is a phenomenon that leaves a rare information professional negligent these days. Remarkably, application demands and developments in the context of related disciplines resulted in technologies that boosted data generation and storage at unprecedented scales in terms of volumes and rates. To mention just a few facts reported by Manyika et al. (2011): a disk drive capable of storing all the world’s music could be purchased for about US $600; 30 billion of content pieces are shared monthly only at Facebook (facebook.com). Exponential growth of data volumes is accelerated by a dramatic increase in social networking applications that allow nonspecialist users create a huge amount of content easily and freely. Equipped with rapidly evolving mobile devices, a user is becoming a nomadic gateway boosting the generation of additional real-time sensor data. The emerging Internet of Things makes every thing a data or content, adding billions of additional artificial and autonomic sources of data to the overall picture. Smart spaces, where people, devices, and their infrastructure are all loosely connected, also generate data of unprecedented volumes and with velocities rarely observed before. An expectation is that valuable information will be extracted out of all these data to help improve the quality of life and make our world a better place.
...
This chapter offers a possible approach in addressing the problem of
“understanding” Big Data in an effective and efficient way. The idea is making adequately grained and expressive knowledge representations and fact
collections evolve naturally, triggered by new tokens of relevant data coming
along. Pursuing this way would also imply conceptual changes in the Big Data
Processing stack. A refined semantic layer has to be added to it for providing adequate interfaces to interlink horizontal layers and enable knowledge related functionality coordinated in top-down and bottom-up directions.


Keywordsbig datavelocity

Free keywordsevolving knowledge ecosystem; volume


Contributing organizations


Ministry reportingYes

Reporting Year2014

JUFO rating2


Last updated on 2024-27-03 at 13:55