Periodic Reporting for period 2 - LeMO (Leveraging Big Data to Manage Transport Operations)
Reporting period: 2019-05-01 to 2020-10-31
Transport researchers and policy makers today face several challenges as they work to build efficient, safe and sustainable transportation systems. From rising congestion to growing demand for public transit, the travel behaviour and transportation preferences of city dwellers are changing fast. Leveraging Big Data to Manage Transport Operations (LeMO) project addresses these issues by investigating the implications of the utilisation of such Big Data to enhance the economic sustainability and competitiveness of European transport sector. The project examined and analysed Big Data in the European transport domain in particular with respect to five transport dimensions: mode, sector, technology, policy and evaluation. LeMO accomplishes this by conducting a series of case studies. LeMO supplemented seven case studies with a trend analysis that finds the barriers and limitations of the transportation system to exploit Big Data opportunities. LeMO devised research and policy roadmap that provides incremental steps necessary towards data openness and sharing to make transport safer, more efficient and more sustainable. Notably, LeMO brought crucial issues linked to privacy, data security and other legal aspects to the forefront, paving the way for future legal framework for the collection and exploitation of Big Data in transport.
The specific objectives of the project are given below. Completed work (Deliverables) to achieve these objectives is shown in brackets:
• To map the current context in which Big Data is being utilised in transport (D1.1)
• To review policies and initiatives relevant to Big Data in transport in the public and private sector (D1.2)
• To understand the technological and infrastructural tools relevant to Big Data in transport (D1.3)
• To understand the economic, legal, social, ethical, environmental and political issues relevant to Big Data in transport currently and in the future (D2.1 D2.2 D2.3 D2.4)
• To understand the relationship between Big Data and open access to data (D2.2)
• To outline a methodology for undertaking case studies in Big Data (D3.1)
• To undertake a series of case studies on Big Data in different sectors (Task 3.2)
• To conduct interviews with case study representatives (Task 3.2)
• To find on the prerequisites of successful big data implementation in the transport sector (D3.2)
• To provide knowledge of these barriers, and with the basis in this knowledge, provide recommendations for exploiting big data within the limitations that the barriers are creating (Task 4.1 and D4.1)
• To undertake a horizontal analysis of case studies to identify constructive findings and suggestions that can be traced across contexts (Task 4.2 and D4.2)
• To design research and policy roadmap for efficient utilisation of big data in the transport field (D4.3 and D4.4 from Task 4.3 and 4.4)
• To gain stakeholder consensus on the LeMO roadmap via a workshop (Task 4.5)
• To create shared value and promote the exchange of knowledge among project partners, Advisory & Reference Group (ARG) and other relevant stakeholders (D5.4 from Task 5.1 and Task 5.4)
• To ensure adequate and wide dissemination for each specific target audiences (Task 5.2)
• To facilitate the validation of the project outcomes (Task 5.5)
Conclusions:
The LeMO roadmap for Big Data in transport in Europe focuses on ensuring the crucial conditions for the development of a European Big Data in the transport ecosystem based on the research outcomes of the project. The LeMO roadmap culminates with a suggestion for the implementation of the actions. LeMO’s goals can be achieved more quickly if research and policy focus on actions that are more of a priority than others, have a higher impact or are easier to implement.
The specific objectives of the project are given below. Completed work (Deliverables) to achieve these objectives is shown in brackets:
• To map the current context in which Big Data is being utilised in transport (D1.1)
• To review policies and initiatives relevant to Big Data in transport in the public and private sector (D1.2)
• To understand the technological and infrastructural tools relevant to Big Data in transport (D1.3)
• To understand the economic, legal, social, ethical, environmental and political issues relevant to Big Data in transport currently and in the future (D2.1 D2.2 D2.3 D2.4)
• To understand the relationship between Big Data and open access to data (D2.2)
• To outline a methodology for undertaking case studies in Big Data (D3.1)
• To undertake a series of case studies on Big Data in different sectors (Task 3.2)
• To conduct interviews with case study representatives (Task 3.2)
• To find on the prerequisites of successful big data implementation in the transport sector (D3.2)
• To provide knowledge of these barriers, and with the basis in this knowledge, provide recommendations for exploiting big data within the limitations that the barriers are creating (Task 4.1 and D4.1)
• To undertake a horizontal analysis of case studies to identify constructive findings and suggestions that can be traced across contexts (Task 4.2 and D4.2)
• To design research and policy roadmap for efficient utilisation of big data in the transport field (D4.3 and D4.4 from Task 4.3 and 4.4)
• To gain stakeholder consensus on the LeMO roadmap via a workshop (Task 4.5)
• To create shared value and promote the exchange of knowledge among project partners, Advisory & Reference Group (ARG) and other relevant stakeholders (D5.4 from Task 5.1 and Task 5.4)
• To ensure adequate and wide dissemination for each specific target audiences (Task 5.2)
• To facilitate the validation of the project outcomes (Task 5.5)
Conclusions:
The LeMO roadmap for Big Data in transport in Europe focuses on ensuring the crucial conditions for the development of a European Big Data in the transport ecosystem based on the research outcomes of the project. The LeMO roadmap culminates with a suggestion for the implementation of the actions. LeMO’s goals can be achieved more quickly if research and policy focus on actions that are more of a priority than others, have a higher impact or are easier to implement.
The LeMO project has progressed well in meeting its objectives.
Work package 1, Setting the stage on big data is complete. This extensive research revealed a number of meaningful insights to assist transport stakeholders in better understanding the European Big Data ecosystem. Aspects of this research were validated in a workshop in Sogndal, Norway in June 2018.
Work package 2, outlining Institutional and governmental issues and barriers was completed and partners identified practical examples impacting different stakeholders. Analyses of this information confirmed that a number of economic, legal, environmental, social and ethical and political issues are present in the Big Data landscape in Europe and they impact a number of key transport areas, and potentially the Big Data industry as a whole. These findings were validated at a workshop that was held in Vienna, Austria in November 2018.
Work package 3, LeMO Case studies were complete at the close of the first reporting period. Partners conducted case studies, which involved transport organisations actively using big data for specific purposes, to enable LeMO to understand strategies, actions and changes in behaviour associated with big data and identify their resultant merits and demerits.
Work package 4, we uncovered different barriers to the utilisation of Big Data in the transport sector and their characterisation. We extracted a total of 129 barriers from the various aspects and identified 54 from the LeMO project case studies and other relevant projects. Finally, the LeMO roadmap is devised.
Work package 5 on creating shared value commenced with the start of the LeMO project and remained live throughout the duration of the project. LeMO partners established and continued to maintain a user-friendly website to keep stakeholders engaged. Other dissemination activities also conducted. Further clustering activities were intensified under the present reporting period.
Main exploitable findings and outputs include: LeMO research roadmap, LeMO policy roadmap, and LeMO findings about legal, regulatory, ethical, social, economic, and political aspects
Significant dissemination activities:
1. Simultaneous and sustainable value creation for shareholders and the society.
2. Organization of Collaborative Symposium.
3. Organization of the LeMO webinar, within the framework of Transport Research Arena TRA 2020.
4. Organization of 2 surveys with stakeholders
5. Publication of newsletters and research papers/articles
6. Successful collaboration with different projects funded under Horizon 2020
7. Production of 3 LeMO videos and 1 LeMO quiz game
8. Participation in Research and Innovation Days 2020 event organized by EU
9. Continuing engagement with stakeholders on social media
10. Development of graphically enhanced version of D.4.4
11. Organization of the LeMO final event
Work package 1, Setting the stage on big data is complete. This extensive research revealed a number of meaningful insights to assist transport stakeholders in better understanding the European Big Data ecosystem. Aspects of this research were validated in a workshop in Sogndal, Norway in June 2018.
Work package 2, outlining Institutional and governmental issues and barriers was completed and partners identified practical examples impacting different stakeholders. Analyses of this information confirmed that a number of economic, legal, environmental, social and ethical and political issues are present in the Big Data landscape in Europe and they impact a number of key transport areas, and potentially the Big Data industry as a whole. These findings were validated at a workshop that was held in Vienna, Austria in November 2018.
Work package 3, LeMO Case studies were complete at the close of the first reporting period. Partners conducted case studies, which involved transport organisations actively using big data for specific purposes, to enable LeMO to understand strategies, actions and changes in behaviour associated with big data and identify their resultant merits and demerits.
Work package 4, we uncovered different barriers to the utilisation of Big Data in the transport sector and their characterisation. We extracted a total of 129 barriers from the various aspects and identified 54 from the LeMO project case studies and other relevant projects. Finally, the LeMO roadmap is devised.
Work package 5 on creating shared value commenced with the start of the LeMO project and remained live throughout the duration of the project. LeMO partners established and continued to maintain a user-friendly website to keep stakeholders engaged. Other dissemination activities also conducted. Further clustering activities were intensified under the present reporting period.
Main exploitable findings and outputs include: LeMO research roadmap, LeMO policy roadmap, and LeMO findings about legal, regulatory, ethical, social, economic, and political aspects
Significant dissemination activities:
1. Simultaneous and sustainable value creation for shareholders and the society.
2. Organization of Collaborative Symposium.
3. Organization of the LeMO webinar, within the framework of Transport Research Arena TRA 2020.
4. Organization of 2 surveys with stakeholders
5. Publication of newsletters and research papers/articles
6. Successful collaboration with different projects funded under Horizon 2020
7. Production of 3 LeMO videos and 1 LeMO quiz game
8. Participation in Research and Innovation Days 2020 event organized by EU
9. Continuing engagement with stakeholders on social media
10. Development of graphically enhanced version of D.4.4
11. Organization of the LeMO final event
The expected impact of the LeMO project will be on transport stakeholders and the broader society by developing the research and policy roadmap that will assist stakeholders to diminish the barriers and limitations, and amplify the opportunities associated with Big Data in European Transport sector. The LeMO project collects evidence of barriers, limitations and opportunities across a number of vital transport modes to support these key impacts.
Strategic impacts – Provide research and policy recommendations to assist stakeholders.
Economic impacts – Assist European stakeholders in gaining a greater share of the Big Data market.
Social impacts – Provide recommendations that will assist stakeholders to diminish the negative social impacts associated with Big Data in transportation.
Strategic impacts – Provide research and policy recommendations to assist stakeholders.
Economic impacts – Assist European stakeholders in gaining a greater share of the Big Data market.
Social impacts – Provide recommendations that will assist stakeholders to diminish the negative social impacts associated with Big Data in transportation.