ISSN: 2167-6461
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Big Data Q2 Unclaimed
Big Data is a journal indexed in SJR in Information Systems and Computer Science Applications with an H index of 36. It has an SJR impact factor of 0,839 and it has a best quartile of Q2. It has an SJR impact factor of 0,839.
Type: Journal
Type of Copyright:
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Open Access Policy:
Type of publications:
Publication frecuency: -
- €
Inmediate OANPD
Embargoed OA- €
Non OAMetrics
0,839
SJR Impact factor36
H Index48
Total Docs (Last Year)124
Total Docs (3 years)1701
Total Refs613
Total Cites (3 years)116
Citable Docs (3 years)4.5
Cites/Doc (2 years)35.44
Ref/DocOther journals with similar parameters
Journal of Network and Systems Management Q2
Mobile Networks and Applications Q2
Semantic Web Q2
Journal of High Technology Management Research Q2
Journal of Intelligent Information Systems Q2
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Aims and Scope
Best articles by citations
Should We Regulate Digital Platforms?
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View moreGetting the Dirt on Big Data
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View morePeta Vs. Meta
View moreIdentifying and Investigating Unexpected Response to Treatment: A Diabetes Case Study
View moreWhat Do RDF and SPARQL bring to Big Data Projects?
View moreParadigms for Realizing Machine Learning Algorithms
View moreCurating Big Data Made Simple: Perspectives from Scientific Communities
View moreDOOMED: Direct Online Optimization of Modeling Errors in Dynamics
View moreBig Data 2.0: Cataclysm or Catalyst?
View moreThe Reliability of Big "Patient Satisfaction" Data
View moreThe Uses of Big Data in Cities
View moreThe Lessons Oscar Taught Us: Data Science and Media & Entertainment
View moreBig Data and the Rise of Machines in Financial Markets
View moreAuthors' Response to Gong's, "Comment on Data Science and its Relationship to Big Data and Data-Driven Decision Making"
View moreEfficient State Management for Scaling Out Stateful Operators in Stream Processing Systems
View moreBig Data for Social Good
View moreBig Data in Aging Research: An Interview with Aubrey de Grey
View moreAn Interview with Duncan Watts
View moreLa Cura, An Open Source Cure for Cancer
View moreImproving Predictive Accuracy in Elections
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