TY - GEN
T1 - Privacy-aware data gathering for urban analytics
AU - Nunez-del-Prado, Miguel
AU - Esposito, Bruno
AU - Luna, Ana
AU - Morzan, Juandiego
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Nowadays, there are a mature set of tools and techniques for data analytics, which help Data Scientists to extract knowledge from raw heterogeneous data. Nonetheless, there is still a lack of spatiotemporal historical dataset allowing to study everyday life phenomena, such as vehicular congestion, press influence, the effect of politicians comments on stock exchange markets, the relation between food prices evolution and temperatures or rainfall, social structure resilience against extreme climate events, among others. Unfortunately, few datasets are combining from different sources of urban data to carry out studies of phenomena occurring in cities (i.e., Urban Analytics). To solve this problem, we have implemented a Web crawler platform for gathering a different kind of available public datasets.
AB - Nowadays, there are a mature set of tools and techniques for data analytics, which help Data Scientists to extract knowledge from raw heterogeneous data. Nonetheless, there is still a lack of spatiotemporal historical dataset allowing to study everyday life phenomena, such as vehicular congestion, press influence, the effect of politicians comments on stock exchange markets, the relation between food prices evolution and temperatures or rainfall, social structure resilience against extreme climate events, among others. Unfortunately, few datasets are combining from different sources of urban data to carry out studies of phenomena occurring in cities (i.e., Urban Analytics). To solve this problem, we have implemented a Web crawler platform for gathering a different kind of available public datasets.
KW - Data collection
KW - Open data
KW - Privacy
KW - Urban analytics
KW - Data collection
KW - Open data
KW - Privacy
KW - Urban analytics
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85046003979&origin=inward
U2 - 10.1007/978-3-319-90596-9_5
DO - 10.1007/978-3-319-90596-9_5
M3 - Conference contribution
SN - 9783319905952
T3 - Communications in Computer and Information Science
SP - 61
EP - 75
BT - Information Management and Big Data
T2 - Communications in Computer and Information Science
Y2 - 1 January 2019
ER -