National Academies Press: OpenBook
« Previous: 5 Research Outputs
Page 77
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making. Washington, DC: The National Academies Press. doi: 10.17226/25965.
×
Page 77
Page 78
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making. Washington, DC: The National Academies Press. doi: 10.17226/25965.
×
Page 78
Page 79
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making. Washington, DC: The National Academies Press. doi: 10.17226/25965.
×
Page 79
Page 80
Suggested Citation:"References." National Academies of Sciences, Engineering, and Medicine. 2020. Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making. Washington, DC: The National Academies Press. doi: 10.17226/25965.
×
Page 80

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

70  References  Burt, M., Cuddy, M., & Razo, M. (2014). Big Data’s Implications for Transportation Operations: An Exploration. Washington, D.C.: U.S. Department of Transportation.  Chitkara, A., Deloison, T., Kelkar, M., Pandey, P., & Pankratz, D. (2020). Enabling data-sharing: Emerging principles for transforming urban mobility. World Business Council for Sustainable Development.  Retrieved March 2020, from  https://docs.wbcsd.org/2020/01/WBCSD_Enabling_data_sharing_Emerging_principles_for_tran  sforming_urban_mobility.pdf  Chowdhury, M., Apon, A., & Dey, K. (2017). Data Analytics for Intelligent Transportation Systems. Cambridge, MA: Elsevier.  Cloud Security Alliance. (2012). Top Ten Big Data Security and Privacy Challenges. Cloud Security  Alliance. Retrieved May 18, 2020, from  https://downloads.cloudsecurityalliance.org/initiatives/bdwg/Big_Data_Top_Ten_v1.pdf  Cuddy, M., Epstein, A., Maloney, C., Westrom, R., Hassol, J., Kim, A., . . . and Bettisworth, C. (2014). The Smart/Connected City and Its Implications for Connected Transportation. Washington, D.C.: U.S.  Department of Transportation. Retrieved from  https://www.its.dot.gov/itspac/Dec2014/Smart_Connected_City_FINAL_111314.pdf  Custers, B., & Ursic, H. (2016, February 1). Big data and data reuse: a taxonomy of data reuse for  balancing big data benefits and personal data protection. International Data Privacy Law, 6(1),  4‐15.  Daki, H., El Hannani, A., Aqqal, A., Haidine, A., & Dahbi, A. (2017). Big Data Management in Smart Grid:  Concepts, Requirements, and Implementation. Journal of Big Data, 4(13).  DAMA International. (2011). The DAMA Dictionary of Data Management, 2nd Edition: Over 2,000 Terms Defined for IT and Business Professionals. Bradley Beach, New Jersey: Technics Publications, LLC.  DAMA International. (2017, March 6). DAMA Data Management Body of Knowledge Framework 2nd Edition (DAMA-DMBOK2). Basking Ridge, NJ: Technics Publications. Retrieved from DAMA  International: https://dama.org/sites/default/files/download/DAMA‐DMBOK2‐Framework‐V2‐  20140317‐FINAL.pdf  Demchenko, Y. (2013, July 17). Defining the Big Data Architecture Framework. Retrieved from NIST:  https://bigdatawg.nist.gov/_uploadfiles/M0055_v1_7606723276.pdf  Demchenko, Y., Canh, N., de Laat, C., Membrey, P., & Gordijenko, D. (2013, August 30). Big Data Security for Big Data: Addressing Security Challenges for Big Data Infrastructure. Retrieved September 5,  2018, from Semantic Scholar:  https://pdfs.semanticscholar.org/184b/b798f1f298e158fdcfe753559bbad65184ab.pdf  District Mobility: Multimodal Transportation in the District. (n.d.). Retrieved February 2020, from District  Mobility: https://districtmobility.org/  El Faouzi, N.‐E., & Klein, L. (2016). Data Fusion for ITS: Techniques and Research Needs. Transportation Research Procedia, 495‐512. 

71 Galgano, S., Talas, M., Whyte, W., Petit, J., Benevelli, D., Rausch, R., & Sim, S. (2016). Connected Vehicle Pilot Deployment Program Phase1, Security Management Operating Concept -New York City. Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/31725 Gastineau, A., Johnson, T., & Schultz, A. (2009). Bridge Health Monitoring and Inspections Systems - A Survey of Methods. St. Paul, MN: Minnesota Department of Transportation. Gettman, D., Toppen, A., Hales, K., Voss, A., Engel, S., & El Azhari, D. (2017). Integrating Emerging Data Sources into Operational Practice. Washington, DC: Federal Highway Administration. Gopalakrishna, D., Garcia, V., Ragan, A., English, T., Zumpf, S., Young, R., . . . Hsu, E. (2016). Connected Vehicle Pilot Deployment Program Phase 1, Security Management Operational Concept – ICF/Wyoming. Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/30810 Gudivada, V. D. (2016). Data Quality Centric Application Framework for Big Data. ALLDATA 2016 : The Second International Conference on Big Data, Small Data, Linked Data and Open Data,. International Academy, Research and Industry Association (IARIA). Harrison, F., Duke, W., Eldred, J., Pack, M., Ivanov, N., Crosset, J., & Chan, L. (2019). NCHRP Research Report 920: Management and Use of Data for Transportation Performance Management: Guide for Practitioners. Washington, DC: National Academy of Sciences. Retrieved March 13, 2020, from https://download.nap.edu/cart/download.cgi?record_id=25462 Hassell, J. (2018, August 15). Thinking Beyond Traditional Data Life Cycle Management. Retrieved from Hortonworks, Inc.: https://hortonworks.com/article/thinking-beyond-traditional-data-life-cycle- management/ IBM Corporation. (2013, August). The fundamentals of data lifecycle. Retrieved from IT.Toolbox.com: http://hosteddocs.ittoolbox.com/TheFundimentals.PDF James, R., Newton, D., Bishop, M., Bare, J., Bollo, R., Wolpert, A., . . . Timcho, T. (2018). Smart Columbus: Systems Engineering Management Plan (SEMP) for Smart. Washington, D.C.: U.S. Department of Transportation. Retrieved from https://smart.columbus.gov/uploadedFiles/SCC-B-SEMP- Systems_Engineering_Management_Plan-Final_508.pdf Jeong, S., Hou, R., Lynch, J. P., Sohn, H., & Law, K. H. (2017). A Big Data Management and Analytics Framework for Bridge Monitoring. Structural Health Monitoring. Johnson, S., Novosad, S., Miller, D., Buckel, W., McNamara, D., Reich, S., & Concas, S. (2017). Connected Vehicle Pilot Deployment Program Phase 2, Data Management Plan –Tampa (THEA). Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/32763 Kim, H. Y., & Cho, J.-S. (2018). Data Governance Framework for Big Data Implementation with NPS Case Analysis in Korea. Journal of Business and Retail Management Research. Retrieved April 2020, from https://jbrmr.com/cdn/article_file/content_24232_18-04-20-02-28-48.pdf Kitchener, F., English, T., Gopalakrishna, D., Garcia, V., Ragan, A., Young, R., . . . Serulle, N. U. (2017). Connected Vehicle Pilot Deployment Program Phase 2, Data Management Plan –Wyoming.

72 Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/32296 Kolleda, J., Garcia, D., & Poling, T. (2016). Connected Vehicle Pilot Deployment Program Phase 1, Security Management Operational Concept-Tampa Hillsborough Expressway Authority (THEA). Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/30827 Levin, O. (2013). Big Data Ecosystem Reference Architecture. Microsoft Corporation. Retrieved September 5, 2018, from http://bigdatawg.nist.gov/_uploadfiles/M0015_v1_1596737703.docx McQueen, B. (2017). Big Data Analytics for Connected Vehicles and Smart Cities. Norwood, MA: ARTECH HOUSE. Microsoft. (2019, January 8). Data Lakes. Retrieved January 22, 2019, from Microsoft: https://docs.microsoft.com/en-us/azure/architecture/data-guide/scenarios/data-lake Miller, K., Miller, M., Moran, M., & Dai, B. (2018). Data Management Life Cycle. College Station: Texas A&M Transportation Institute. Retrieved from https://static.tti.tamu.edu/tti.tamu.edu/documents/PRC-17-84-F.pdf Mobility Data Specification Project. (n.d.). Retrieved February 3, 2020, from Github: https://github.com/openmobilityfoundation/mobility-data-specification Multi-Dimensional Thinkers. (2018, 8 15). Multi-Dimensional Data Management Framework V3.0. Retrieved from Multi-Dimensional Thinkers: http://www.multidimensionalthinkers.com/The- Multi-Dimensional-ex-Data-Atom-Data-Management-Framework/ Multi-Dimensional Thinkers. (2020, March 13). Multi-Dimensional Data Management Framework V4.0. Retrieved January 15, 2019, from Multi-Dimensional Thinkers: https://www.multidimensionalthinkers.com/gallery/wre%20- %20the%20multi%20dimensional%20(v4.0)%20data%20management%20framework%20(a3%2 0electronic)%2020181020.pdf OECD/ITF. (2015). Big Data and Transport: Understanding and Assessing Options. Paris: OECD Publishing. Retrieved February 2019, from https://www.itf- oecd.org/sites/default/files/docs/15cpb_bigdata_0.pdf Pecheux, B. B., Miller, S., & Shah, V. (2017). Sustainable Enterprise Information Portals. Washington, DC: National Academy of Sciences, Transportation Research Board. Pecheux, K. K., Pecheux, B., & Carrick, G. (2019). NCHRP Research Report 904 Leveraging Big Data to Improve Traffic Incident Management. Washington, DC: National Academy of Sciences. Pecheux, K., & Pecheux, B. (pending publication). Data Integration, Sharing, and Management for Transportation Planning and Traffic Operations. Washington, DC: National Academy of Sciences. Picciano, A. G. (2012). The Evolution of Big Data and Learning Analytics in American Higher Education. Journal of Asynchronous Learning Networks, 16(3), 9-20. Retrieved January 22, 2019, from https://files.eric.ed.gov/fulltext/EJ982669.pdf

73 Rathore, M. M., Ahmad, A., Paul, A., & Rho, S. (2016). Urban planning and building smart cities based on the Internet of Things using Big Data analytics. Computer Networks, 63-80. Roe, C. (2017, December 18). What is Data Governance? Retrieved from Dataversity: http://www.dataversity.net/what-is-data-governance/ Rouse, M. (2013, October ). Big Data Management. Retrieved from Search Data Management: https://searchdatamanagement.techtarget.com/definition/big-data-management Soares, S. (2018, 8 15). Big Data Governance: A Framework to Assess Maturity. Retrieved from IBM Corporation: https://www.ibmbigdatahub.com/blog/big-data-governance-framework-assess- maturity Spirion. (2019). Data Lifecycle Management. Retrieved May 2020, from Spirion: https://www.spirion.com/data-lifecycle-management/ Stiglich, P. (2018, 8 15). Data Governance vs. Data Management. Retrieved from Perficient: https://blogs.perficient.com/2012/06/12/data-governance-vs-data-management/ Taylor, C. (2017, June 8). Big Data Architecture. Retrieved January 22, 2019, from Datamation: https://www.datamation.com/big-data/big-data-architecture.html Turck, M. (2018, June 26). Matt Turck. Retrieved 2019, from Great Power, Great Responsibility: The 2018 Big Data & AI Landscape: https://mattturck.com/BigData2018/ Van Duren, D., Rausch, R., & Benevelli, D. (2017). Connected Vehicle Pilot Deployment Program Phase 2, Data Management Plan. Washington, D.C.: U.S. Department of Transportation. Retrieved from https://rosap.ntl.bts.gov/view/dot/35363 Wang, W., & Lu, Z. (2013, April). Cyber Security in the Smart Grid: Survey and Challenges. Computer Networks, 57(5), 1344-1371. Wells, D. (2017, January 17). The Next Generation of Data Governance. Retrieved January 22, 2019, from Eckerson Group: https://www.eckerson.com/articles/the-next-generation-of-data-governance

Next: Appendix A Online Survey »
Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making Get This Book
×
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

The amount of data surrounding the application of emerging technologies is expanding, producing “big data” at magnitudes not previously seen. While a few agencies have found some success with individual projects, most are uncertain on how to handle this level of big data at an organizational level.

The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 282: Framework for Managing Data from Emerging Transportation Technologies to Support Decision-Making is designed to walk an agency through the process of developing the knowledge, environment, projects, and buy-in to move incrementally and iteratively from a traditional data management approach to establishing data management policies, procedures, technologies, and practices that fully meet the modern data management needs of an agency.

This document is supplemental material to NCHRP Research Report 952: Guidebook for Managing Data from Emerging Technologies for Transportation.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!