Rezultaty
A report on big data governance and institutional issues.
Big Data and emerging transportation challengesA report describing the research challenges related to big data technologies and methods for the transport sector.
Exploitation PlanThis deliverable will report the activities for exploiting the research results of the project after the project’s life time.
Big Data implementation context in transportA report describing the review and analysis of the Big Data investments and services
Data Benefit Analysis and Impact Assessment Methodologies (IAM) for appraising big data solution in transportThis deliverable will consist of the Data Benefit Analysis and the Impact Assessment Methodology for the evaluation of investments in big data to improve management and optimization of transport systems and networks.
Policy briefsFour targeted (4) policy briefs by the end of the project
Big Data in Transport LibraryA report with all the use cases identified in NOESIS
Dissemination , communication and exploitation planA report on planned dissemination, communication and exploitation activities.
Suitability of business and organizational models for the successful implementation of big data in transport solutionsThis deliverable will provide a set of recommendations for the right implementation of successful business models for using of big data for transport. The analysis will make recommendations depending on the freight vs. passenger transport and the specific characteristic of each transport mode, or the interconnection of different transport modes.
Handbook on Key Lessons Learnt and Transferable PracticesA report on the key lessons learns and best practices derived from the use cases analysis.
Learning Framework methodology and architectureA report describing the Learning Framework methodology and architecture of NOESIS.
Technological and policy roadmapsThis deliverable will produce two coordinated roadmaps: one for the implementation of technological solutions and the other one for policy measures aimed at facilitating the use of big data to public agencies and transport companies.
Development and validation of the NOESIS Decision Support tool (DST)A report describing the development and validation of the NOESIS Decision Support tool (DST)
Summary to Practitioners on Laws, Regulations, and Directives on Data Privacy, Security and OpennessA Report summarizing all Big Data related Laws, Regulations, and Directives related to transport.
Publikacje
Autorzy:
Janković, S., S. Mladenović, S. Zdravković, S. Vesković, and A. Uzelac,
Opublikowane w:
"Second International Conference ""Transport for Today's Society""", 2019, ISBN 9789-989786778
Wydawca:
Faculty of Technical Sciences Bitola
DOI:
10.20544/tts2018.p02
Autorzy:
Nandor Verba, Kuo-Ming Chao, Soizic Linford, Eleni Anoyrkati
Opublikowane w:
Proceedings of the Fourth International Conference on Traffic and Transport Engineering, Numer Belgrade 2018, 2018, Strona(/y) 232-238, ISBN 978-86-916153-4-5
Wydawca:
City Net Scientific Research Center Ltd. Belgrade
Autorzy:
Katrakazas C., Antoniou C., Yannis G.
Opublikowane w:
Transportation Research Board (TRB), Numer Proceedings of the Transportation Research Board (TRB) 98th Annual Meeting,, 2019
Wydawca:
TRB
Autorzy:
Soizic Linford, Benjamin Bogdanovic, Kuo-Ming Chao, Sladana Jankovic, Vladislav Maras, Mirjana Bugarinovic, Ilias Trochidis
Opublikowane w:
2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2019, Strona(/y) 146-151, ISBN 978-1-7281-0350-1
Wydawca:
IEEE
DOI:
10.1109/cscwd.2019.8791927
Autorzy:
Slađana Janković, Snežana Mladenović, Dušan Mladenović, Slavko Vesković, Draženko Glavić
Opublikowane w:
Enterprise Information Systems, Numer 12/8-9, 2018, Strona(/y) 1180-1201, ISSN 1751-7575
Wydawca:
Taylor & Francis
DOI:
10.1080/17517575.2018.1462404
Autorzy:
Xiang Fei, Nazaraf Shah, Nandor Verba, Kuo-Ming Chao, Victor Sanchez-Anguix, Jacek Lewandowski, Anne James, Zahid Usman
Opublikowane w:
Future Generation Computer Systems, Numer 90, 2019, Strona(/y) 435-450, ISSN 0167-739X
Wydawca:
Elsevier BV
DOI:
10.1016/j.future.2018.06.042
Autorzy:
Szu-Yin Lin, Chi-Chun Chiang, Jung-Bin Li, Zih-Siang Hung, Kuo-Ming Chao
Opublikowane w:
Future Generation Computer Systems, Numer 89, 2018, Strona(/y) 446-454, ISSN 0167-739X
Wydawca:
Elsevier BV
DOI:
10.1016/j.future.2018.06.052
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