Periodic Reporting for period 2 - DIAMOND (Revealing fair and actionable knowledge from data to support women’s inclusion in transport systems) Período documentado: 2020-05-01 hasta 2022-01-31 Resumen del contexto y de los objetivos generales del proyecto The DIAMOND project’s main goal is to turn data into actionable knowledge with notions of fairness, in order to progress towards an inclusive and efficient transport system. The duration of the project was from 1st November 2018 till 31st January 2022, 39 months in total. The project focuses on four real-world scenarios (use-cases), where inclusiveness is currently a central issue, with a defined goal per each one: · Railways and public multimodal transport, which goal was to increase the % of women using the railways and public transport in peak and off-peak hours. · Autonomous vehicles, which goal was to increase the acceptance level of autonomous driving by women · Vehicle (bike) sharing, with the aim at increasing the % of women using the bike-sharing system. · Corporate social responsibility and employment, aiming at increasing the % of women employees in on-site and off-site job positions in the transport sector. This project was born out of the conviction that 80% of factors influencing on fairness in transport are hidden and not evident (iceberg theory), and this was exactly the reason because an interdisciplinary team with gender, psychology and social experts, jointly with transport engineers, was built to work together in the DIAMOND project. Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha To achieve this objective, the next technical roadmap was followed:• Definition of what is understood as fairness by the project.• Generate knowledge about fairness in transport: Needs and barriers, and recommendations.• Develop methods to make this knowledge actionable: Toolbox and Guidelines.• Assess the potential impact of this actionable knowledge on a specific goal.This technical roadmap was applied to 4 use cases, for which inequalities regarding fairness are well documented; a goal was also defined per each use case:• In the Use case 1, the project addressed the railways and public transport, with the goal to increase the number of women travelling on-peak and off-peak hours.• In the Use case 2, the project addressed the design of Autonomous Vehicles with the goal to increase the acceptance level by women.• In the Use case 3, bike sharing systems were addressed with the goal to increase the number of women using this scheme.• And finally in the Use case 4, the project addressed the employment in the transport sector with the goal to increase the % of women employees in on-site and off-site job positions. As a first step, the concept of fairness for the project was defined, as a state in which people are treated similarly, and not impeded by prejudices or unnecessary distinctions or barriers, except they can be explicitly justified.Needs and barriers of women per each use case were identified, clustered and hierarchized in 3 levels of detail, being actionable knowledge those in the level 3. Then, a list of recommendations was created for all needs and barriers through workshops with external experts, the interdisciplinary Diamond’s team and experts from related associations. These recommendations were validated by at least 5 experts with 80% of positive answers about the validity of each recommendation to address a specific need or barrier.The project created, per each use case, quantitative databases through preferences and satisfaction surveys, observations, simulations in a laboratory and structured datasets; and qualitative datasets through Focus Groups, interviews, social media analysis and workshops. A user engagement strategy was outlined per each data collection campaign, for which, as part of the ethics and responsible research followed during the whole project, an Ethics approval process managed by an Ethics board was carried out per each one.After a data analysis through the Analytical Hierarchy process (AHP), Bayesian Networks and other statistical tests, DIAMOND got the next fundamental results:• A hierarchy of needs and barriers, and recommendations for different profiles of women.• Correlations among these needs and barriers.• Factors and profiles with significant differences regarding satisfaction.All these fundamental results were the support of other outputs of the DIAMOND project, such as:• A Toolbox (https://toolkit4fairness.eu/) where an Entity can first, choose a profile of traveller and employee, and then fill a self-assessment questionnaire. After this, the Entity will get a fairness score for this specific profile, a list of recommendations to improve the fairness of this profile, and factors worthy to focus on and what other factors are drastically affecting them. With this information, the Entity has sufficient information to outline a roadmap for improving its fairness.• An Impact assessment method to assess the effectiveness of recommendations regarding the goal of each use case.• A White paper (Link) addressing gender-specific needs in Europe’s current and future transport systems• Educational Curriculum design guidelines• New Corporate Social Responsibility Protocols for transport companies, and • Guidelines about Autonomous Vehicles through the gender perspective glasses Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha) Going further, the DIAMOND project has estimated, based on the increase of the satisfaction level of some critical needs and barriers, which would be the impact regarding the fairness of implementing some feasible recommendations suggested by the Toolbox by a transport service provider or an employer :These estimations concluded that a railways or public transport service provider will increase around a 5% the number of women travelling during off-peak hours, if it implements some recommendations such as «Display the next services in the station», «Adapted connections paths to all kind of users» or «Provide more staff for real-time assistance». The «Provision of education about sportive driving when it is activated» in Autonomous Vehicles would increase their acceptance level for women in a 20%. «Offer electrical bikes to customers» would increase 50% the number of women using the bike-sharing, and «Gender neutral employment advertisement» or «Ensure secure and a rapid police support» would have a high impact on women working off-site in the transport sector, although in this case the estimation model is not able to quantify this impact.