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Ochrona dziedzictwa kulturowego a działania na dużych szybkozmiennych zbiorach danych – perspektywa kryminologiczna

Authors: Szymon Buczyński;

Ochrona dziedzictwa kulturowego a działania na dużych szybkozmiennych zbiorach danych – perspektywa kryminologiczna

Abstract

Recent technological revolutions in data and communication systems enable us to generate and share data much faster than ever before. Sophisticated data tools aim to improve knowledge and boost confdence. That technological tools will only get better and user-friendlier over the years, big data can be considered an important tool for the arts and culture sector. Statistical analysis, econometric methods or data mining techniques could pave the way towards better understanding of the mechanisms occurring on the artmarket. Moreover crime reduction and prevention challenges in today’s world are becoming increasingly complex and are in need of a new technique that can handle the vast amount of information that is being generated. This article provides an examination of a wide range of new technological innovations (IT) that have applications in the areas of culture preservation and heritage protection. The author provides a description of recent technological innovations, summarize the available research on the extent of adoptionon selected examples, and then review the available research on the each form of new technology. Furthermore the aim of this paper is to explore and discuss how big data analytics affect innovation and value creation in cultural organizations and shape consumer behavior in cultural heritage, arts andcultural industries. This paper discusses also the likely impact of big data analytics on criminological research and theory. Digital criminology supports huge data base in opposition to conventional data processing techniques which are not only in suffcient but also out dated. This paper aims at closing a gap in the academic literature showing the contribution of a big data approach in cultural economics, policy and management both from a theoretical and practice-based perspective. This work is also a startingpoint for further research.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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