mAkE Data Management Report

mAkE was an innovation action that aimed to promote cooperation and strategic partnerships between Digital Innovation Hubs (DIHs) in Africa and Europe. The DIHs in mAkE were makerspaces, which have been growing to become important actors in the local digital innovation ecosystems in both Europe and Africa. Makerspaces support digital, local manufacturing, and innovation in product design and development.

The mAkE project contributed to strengthening the EU-Africa innovation and start-up ecosystem by creating infrastructure for decentralised production and collaboration as well as shared policy frameworks and educational opportunities. The infrastructure allows for fast and efficient collaboration among the actors in the ecosystem in terms of knowledge-sharing, skills, use of machines and contracting processes in support of distributed manufacturing. The mAkE capacity-building activities equipped makerspaces and their attached local small and medium-sized enterprises (SMEs) and digital start-ups with the necessary skills to engage in hardware-based innovation and small-scale manufacturing. We offered learning resources, targeted trainings, and incubation, mentoring and matching activities for makers and makerspaces in Africa and Europe.

During the duration of the mAkE project, all work packages were managing data, guided by the Data Management Plan (DMP, D8.2) as well as the Project Handbook (D8.1). Personal data was primarily collected during events (for registration purposes) and when setting up interviews, and this data was then either deleted or anonymised. Non-personal data, such as the geographical location of machines and tools, was made publicly available online in compliance with the principles of open and public sharing of data. As stated in the Grant Agreement, mAkE was part of the Open Research Data Pilot of the EU, and has thus been committed to providing access not only to project results and processes, but also to data collected during those processes, such as the open dataset for the project’s map of machinery (Deliverable D4.3).