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Data Management Plan – Version I (D1.4)

Methodology

Training

Intervention

Tool

Data

Study

Use case

Vangelis Angelakis, Linköping University

Overview

Deliverable D1.4 establishes the first Data Management Plan for ELABORATOR and sets the principles for collecting, storing, processing, sharing and preserving project data. It combines compliance with the General Data Protection Regulation with the FAIR principles of making research data Findable, Accessible, Interoperable and Reusable. The plan is particularly relevant because the project gathers information from sensors, tools, workshops, questionnaires and evaluations across 12 cities. For readers, it provides a clear baseline for handling mobility data while protecting the rights of participants.


Highlights

• GDPR foundations: The plan defines key concepts, legal principles, consent requirements, data-subject rights and the responsibilities of controllers and processors.

• Three data classes: Class 1 covers information collected from citizens and local stakeholders during co-creation and evaluation activities. Class 2 describes data used to characterise intervention sites. Class 3 covers pre-intervention and post-intervention evaluation data, including monitoring and survey data.

• Data minimisation: Personal data should be collected only where necessary. Identity data must not be shared, and pseudonymisation is required for scientific analysis and exchange between partners.

• Protection of vulnerable groups: The plan requires additional care when research involves vulnerable road users or people vulnerable to exclusion, including clear information and meaningful consent.

• Governance and security: Partners must define joint-controller responsibilities, use data-sharing agreements and keep records of processing activities. Access controls, secure storage and partner procedures protect personal data.

• FAIR and Open Access: Publications and public deliverables should be indexed with appropriate metadata and persistent identifiers. Scientific publications and supporting research data should be openly accessible where possible, while restrictions must be explained.


Conclusion

D1.4 gives city and project teams a common set of rules before large-scale intervention and evaluation data collection begins. It helps them plan consent, storage, access, sharing and publication consistently across different national and organisational contexts. The document establishes the baseline approach and does not yet present city-level implementation results.

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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

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ELABORATOR is part of the CIVITAS Initiative and contributes to the goals of the EU Mission: Climate-Neutral and Smart Cities

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UKRI supports UK participants with grant numbers 10078745 (iRAP ) and 10069203 (UBRIS)

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