K. Majka
Applications of Knowledge Discovery in Massive Transportation Data: The Development of a Transportation Research Informatics Platform (TRIP).
Majka, K.; Nagler, E.; James, A.; Blatt, A.; Pierowicz, John; Anastasopoulos, P. Ch.; Fountas, Grigorios
Authors
E. Nagler
A. James
A. Blatt
John Pierowicz
P. Ch. Anastasopoulos
Dr Grigorios Fountas G.Fountas@napier.ac.uk
Associate
Abstract
Transportation researchers and practitioners have access to unprecedented amounts of data but lack the tools to easily store, manipulate, and analyze these data. The Transportation Research Informatics Platform (TRIP) is an informatics-based system designed to manage massive amounts of transportation data and provide researchers an efficient way to conduct analytics on big data. The objectives of TRIP include creating the ability to handle massive amounts of transportation data; utilize open-source technologies and tools to ingest, store, align, and process data; accept structured, semistructured, and unstructured datasets from any source; provide an efficient way to query data without indepth knowledge of metadata; integrate with open-source and consumer off-the-shelf analytics products; and provide visualization tools to offer greater insights into data. TRIP architecture is flexible and built on opensource state-of-the-art technology developed with big data in mind. Although predominantly developed for transportation safety research, TRIP is domain agnostic and capable of addressing issues pertaining to operations and maintenance given the ingestion of the appropriate datasets.
Citation
Majka, K., Nagler, E., James, A., Blatt, A., Pierowicz, J., Anastasopoulos, P. . C., & Fountas, G. (2019). Applications of Knowledge Discovery in Massive Transportation Data: The Development of a Transportation Research Informatics Platform (TRIP). Federal Highway Administration
Report Type | Technical Report |
---|---|
Acceptance Date | Sep 1, 2017 |
Publication Date | 2019-01 |
Deposit Date | Sep 24, 2018 |
Publicly Available Date | Feb 6, 2019 |
Pages | 95 |
Keywords | Informatics, analytics, big data, ingest, align, safety, operations, maintenance, visualization, |
Public URL | http://researchrepository.napier.ac.uk/Output/1304701 |
Additional Information | Publication number: FHWA-HRT-19-008 |
Contract Date | Feb 6, 2019 |
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Copyright Statement
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161. http://www.ntis.gov
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