Open science and reproducible Research


We try to make and promote reproducible research, with the objective that publications are available including software and data online. You can check also the innovation program launched to promote open science knowledge transfer.

Recent publications:

Beardsley M, Hernández‐Leo D, Ramirez‐Melendez R. Seeking reproducibility: Assessing a multimodal study of the testing effect. Journal of Computer Assisted Learning

CompMusic, a selected use case in the study on open access to publications and research data management and sharing within ERC projects

Other actions to promote it:

  • Open Science Workshop for PhD students by the ORION project. Registration 

  • June 7th, 15:30h. Reflecting on the PELARS project and Multimodal Learning Analytics. Daniel Spikol, Malmö University. 15:30h, room 55.309.

The talk presents key results and lessons learnt from the Practice-based Experiential Learning Analytics Research and Support (PELARS) project. PELARS was a three-year project that developed a learning analytics system to investigate small group learning for open-ended engineering tasks. The aim is to share the results and challenges of the project to further the dialogue about how to increase progress for multimodal learning analytics (MMLA). The theories and different methods of the project will be discussed that include the different sensors used to capture, record, and analyse students physical interactions and how we used this data to create models to understand aspects of collaboration. To investigate the multimodal data, we started with a simple grading of the student's final products and progressed to a richer framework for assessing student non-verbal collaboration with different machine learning strategies. Some of the results illustrate that body location and movement are strong features for further investigating collaboration. However, challenges remain across the sustainability and ethics of how this data can be used to support the learners and teachers in creative, open-ended activities.

Software Licencing and Open Source tooling workshops

Malcolm Bain, idLaw partners

  • April 5th, 2018 15:30h - 17:30h introduction to software licensing (room 52.219, Roc Boronat 138, open seminar - no registration required)

When using and developing open source software, there are a number of considerations to take into account that go beyond the pure technical aspects. Malcolm Bain will introduce and review the legal aspects of using and developing open source software, with a focus on licensing, license choice and license compliance obligations with distributing products that are or embed open source components. 

Malcolm Bain is an English solicitor and Spanish lawyer, specialising in Information Technology and Intellectual Property law, and co-founder of id law partners (now part of BGMA, a Barcelona based law firm). He has a wide experience representing clients on both sides of IT transactions, and advises on licensing, software contracts, technology transfer, copyright, privacy and trademark issues. He has participated in various R+D projects and written and lectured on many aspects of IT law, e-commerce and internet regulation.


  • 25 January 2018. Sharing your data and software on Zenodo. Lars Holm Nielsen. Zenodo project leader, CERN. 15:30h. 55.410. Slides 

Abstract: To fully understand and reproduce research performed by others, it is necessary to have all the details. In the digital age, that means all the digital artefacts, which are all welcomed in Zenodo. To be an effective catch-all repository, that eliminates barriers to adopting data sharing practices, Zenodo does not impose any requirements on format, size, access restrictions or licence. Quite literally we wish there to be no reason for researchers not to share! Data, software and other artefacts in support of publications may be the core, but equally welcome are the materials associated with the conferences, projects or the institutions themselves, all of which are necessary to understand the scholarly process.

  • 26 October 2017. DKPro Core - With Reusable and Interoperable Components Towards Reproducible Experiments. Richard Eckart de Castilho. TU Darmstadt. PhD Seminars. 15:30h, room 55.410.


  • 14 September 2017. Data management and sharing in Large Research Infrastructures: how synchrotrons handle the big data challenge. Anne Bonnin, Paul Sherrer Institute. Room 55.309


  • 16 March 2017. PhD seminars. Software development best practices for research reproduceability. Alastair Porter, MTG.

Abstract: In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.


  • How many times have you got frustrated, because your code from last month refuses to run and your past self didn’t bother to leave you any guidelines?
  • Are you scared that one day a colleague will ask you the data/results of a paper, and you will have to excavate them out of a folder named ‘allDataResultsVersion8bFinalizedRecheckedPleaseEnd’?
  • Are you concerned that your contributions will not have much impact, because people may not be able to access them properly?

If yes, you are in the same shoes with me, when I started my PhD! In this talk, I will present how I embraced reproducibility to avoid some of these common mistakes. I will explain some best practices, simple tricks and habits I have learned throughout my doctoral research, which improved the quality of my research, made it reusable by others (and myself), and hence improved the accessibility and visibility of my work. I will give practical examples in where I failed (and then gradually improved) on organizing, developing, versioning, documenting, licensing and publishing the research material (data, code, experimental setups and results etc.). I will also introduce some of the available software tools and services, which would help you to achieve these goals. I hope that this talk will convince you to consider reproducibility as a major criteria in academic research, and give you a head start on achieving this objective.

Title: Imaging biomarkers: algorithms, open data and infrastructure for neurological disorders


Abstract: One of the major challenges in clinical neuroimaging is to detect quantitative signs of pathological evolution as early as possible in order to prevent disease progression, evaluate therapeutic protocols or even better understand and model the normal history of a given neurological pathology.

A particular challenge is to find correlations between brain structures at the morphometric, structural, metabolic or functional level through a large set of multimodal images. MRI is the premier means to study the human brain through various acquisition protocols. This presentation will illustrate this challenge through the use of novel cellular or structural MRI protocols able to provide relevant information at the cellular or micro-structural level.

Technological perspectives will be also provided about general issues of Medical Imaging as a Service in the context of the emerging open data services and digital infrastructures. After introducing the general context, some examples will be provided of how these new services can be implemented, and applied to neurological diseases, and especially Multiple Sclerosis.

Title: Scientific Dissemination, Online Repositories, and Author's Rights.

Title: Reproducibility in research.

Abstract: An objective of the María de Maeztu Strategic Research Program is “to increase the impact of our research by increasing the impact of the publications, datasets and software tools, and take advantage of this impact to establish and consolidate partnerships”. It includes actions to promote that the research results, datasets and tools are discoverable, interpretable and reusable, including the publication of the data and software together with the publications. During this session, we will discuss some of the topics linked to "reproducible research", including the increasing requirements in making datasets and computer code available by funding agencies, publishers and potential mechanisms to promote it in our organisation being elaborated in the context of the Maria de Maeztu program.

Ongoing draft document within MdM for good practices for discussion in this link


Video of the 2016 award ceremony

  • Data management: The UPF Library supports you in several aspects linked to Data Management, including the possibility to use the UPF repository to preserve your data. Check here for more details.