Official statistics has acknowledged the value of big data and has started exploring the use of diverse sources in several domains. Sometimes, big data objects can be easily connected to statistical units. If a unit identifier is available, the opportunity to link big data to existing statistical micro data can allow enlarging the content, the coverage, the accuracy and the timeliness of official statistics, for example Internet-scraped data could be used with this aim. In this setting, new challenges arise in data integration with respect to linking administrative data. In this work, we describe a real case of integration of web scraped data and a statistical register of agritourisms specifying the novelties and challenges of the procedure.

Exploring solutions for linking Big Data in Official Statistics / Tuoto, T.; Fusco, D.; Di Consiglio, L. - (2018), pp. 49-58. - SPRINGER PROCEEDINGS IN MATHEMATICS & STATISTICS.

Exploring solutions for linking Big Data in Official Statistics

Tuoto T.
;
Di Consiglio L
2018

Abstract

Official statistics has acknowledged the value of big data and has started exploring the use of diverse sources in several domains. Sometimes, big data objects can be easily connected to statistical units. If a unit identifier is available, the opportunity to link big data to existing statistical micro data can allow enlarging the content, the coverage, the accuracy and the timeliness of official statistics, for example Internet-scraped data could be used with this aim. In this setting, new challenges arise in data integration with respect to linking administrative data. In this work, we describe a real case of integration of web scraped data and a statistical register of agritourisms specifying the novelties and challenges of the procedure.
2018
Studies in Theoretical and Applied Statistics
978-3-319-73905-2
Big data; Internet-scraped data; Data integration; Data linkage; Farm register
02 Pubblicazione su volume::02a Capitolo o Articolo
Exploring solutions for linking Big Data in Official Statistics / Tuoto, T.; Fusco, D.; Di Consiglio, L. - (2018), pp. 49-58. - SPRINGER PROCEEDINGS IN MATHEMATICS & STATISTICS.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1608084
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