We have relevant datasets, repositories, frameworks and tools of relevance for research and technology transfer initiatives related to knowledge extraction. This section provides an overview on a selection of them and links to download or contact details.

The MdM Strategic Research Program has its own community in Zenodo for material available in this repository  as well as at the UPF e-repository  . Below a non-exhaustive list of datasets representative of the research in the Department.

As part of the promotion of the availability of resources, the creation of specific communities in Zenodo has also been promoted, at level of research communities (for instance, MIR and Educational Data Analytics) or MSc programs (for instance, the Master in Sound and Music Computing)



Back [EDUCATIONAL DATA] Understanding collective behavior of learning design communities

[EDUCATIONAL DATA] Understanding collective behavior of learning design communities


The following dataset has been used for the paper entitled "Understanding Collective Behavior of Learning Design Communities".

Michos, K., & Hernández-Leo, D. (2016). Understanding collective behavior of learning design communities. In Proceedings of the 11t European Conference on Technology Enhanced Learning, 614-617. https://doi.org/10.1007/978-3-319-45153-4_75


Social computing enables collective actions and social interaction with rich exchange of information. In the context of educators’ networks where they create and share learning design artifacts, little is known about their collective behavior. Learning design tooling focuses on supporting educators (learning designers) in making explicit their design ideas and encourages the development of “learning design communities”. Building on social elements, this paper aims to identify the level of engagement and interactions in three communities using an Integrated Learning Design Environment (ILDE). The results show a relationship between the exploration of different artifacts and creation of content in all the three communities confirming that browsing influence the community's outcomes. Different patterns of interaction suggest specific impact of language and length of support for users.