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Big Data Opportunities and Challenges in Asset Management
| 题名： | Big Data Opportunities and Challenges in Asset Management |
| 作者： | Gong, J.; Heaslip, K.; McNeil, S.; Farzan, F.; Brink, S. |
| 关键词： | Big data##Transportation Asset Management (TAM)##Data analytics##Big data demands##Performance##Opportunities analysis##Challenges##Transportation industry##Statistics##Workshops## |
| 摘要： | State Departments of Transportation and other transportation agencies collect vast quantities of data but man-aging, accessing and sharing data has been problematic and well documented. This project reviewed the similar challenges faced by other industries and investigated what approaches have been taken by these industries to address those challenges. In the project, we also explored what kinds of data sets in the transportation industry are posing big data challenges, and reviewed relevant studies on emerging applications of these data sets. It is reasonable to conclude that the rise of big data demands more efficient and effective and scalable data analysis methods that must transcend traditional analysis methods in the field of statistics, data mining and machine learning. Therefore, a detailed literature survey was also conducted on what kind of tools and data analytic have been proposed and used for big data analytics. Many use cases are highlighted in the report to demonstrate the opportunities with big data. At the end of the project, a half-day workshop was conducted to disseminate the findings of this research and solicity inputs from leading industry and academic researcher in the field of engineering informatics, cloud computing, and big data analytics. Many presentations in the workshop have echoed the findings of this project. |
| 总页数： | 92 |
| 报告类型： | 科技报告 |
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