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SWANS : Semantic Web Analytics: Processing Big Data on Energy Consumption

SWANS  proposes  a  big  data  processing  service-based  framework  for  supporting  experts  and  non-experts  analysis  on  energy  consumption.  Building  big  data  collections  implies  analyzing  intranets,  deep  web  and  open  web  data,  to  discover  events  that  cause  different  energy  consumption  behaviors,  for  example,  high  consumption of energy. SWANS main challenges are the efficient manipulation of huge amounts of data on  the cloud with data coming from heterogeneous data sources producing different types of data, smart meters, sensors, home and personal utilities.   The main objective in SWANS is to address the theoretical aspects of the semantic analytics service–based  framework  on  the  cloud  thanks  to  the  complementary  expertise  of  all  partners  and  to  begin  a  fruitful  collaboration around Energy Information Systems for energy-care through the development of some big data  analysis tools. The Energy Semantics Web Analytic framework will incorporate: (1) the automatic and semiautomatic  extraction  of  meta4data  from  semantically  heterogeneous  collections;  and  (2)  analytical  processing  that  exploits  domain  ontologies  and  associated  knowledge  bases,  with  new  implementations  of  map-reduce algorithms on the cloud. 


Participating Members

Cheick BA


Mirian HALFELD FERRARI ALVES (Project coordinator)


Action's Web Page