An Evaluation of Knowledge Discovery Techniques for Big Transportation Data

Details

• Creators:
  Majka, Kevin
• Corporate Creators:
  Transportation Informatics University Transportation Center ; CUBRC Inc. ; State University of New York at Buffalo
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Data analysis
  • Data mining
  • Data quality
  • Information processing
  • Research
  • Transportation
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report June 2016 - September 2018
• Corporate Publisher:
  Transportation Informatics University Transportation Center
• Abstract:
  In an ever growing internet of things (IoT) environment the amount of data produced and available for analysis is growing exponentially. In order to access and process these data sources new methods and tools are needed that can sufficiently process big data as well as ensure the quality and completeness of the data. For researchers and practitioners the use of technology should enhance their workflows and enable questions to be answered faster using all available relevant data. An intelligent architecture or software stack enables the data self service in a transparent way. This research proposes a prototype system that would enable researchers to efficiently work with ‘Big Data’ sources.
• Format:
  PDF
• Funding:
  DTRT13-G-UTC48
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/64081/dot_64081_DS1.pdf
• File Type:
  [PDF - 1.77 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha256:a2f5ce54e2e85ef9bf183f763b9335d5b1d190152d0a680db1846da1424d113e