Data management

Date: 16.06.2023, 23.06.2023, 30.06.2023, 07.07.2023  

Learning model: online lectures and exercises 

This short course is designed to help RI managers enhance their skills and knowledge in defining and implementing key data management policies across the research lifecycle. Key topics include creating comprehensive data policies, establishing and respecting FAIR principles for data, and developing effective data management plans.

The course is divided into four Sessions:

  • – Introduction to data management and data policy for RI managers
  • – Operational oversight of data management and policy in an RI
  • – FAIR principles and their application
  • – Data management plans

Target Audience

The short course is aimed at managers, operators and other professionals in Research Infrastructures or Core Facilities.

Learning outcomes

Learning outcomes

This course will provide a comprehensive overview of the key issues and concepts around the management of data and data policy in Research Infrastructures. It will cover topics such as the role of data policy, data typologies, metadata, operational considerations for managers, data lifecycle, workflows, user groups, open data, data sharing and access restrictions, certification mechanisms, and FAIR principles. After completing the course, participants will be able to develop relevant data management policies and guidelines, determine resources, technologies, and staff competencies needed to implement data management and policy, and implement FAIR principles in their research infrastructure.

Session 1 – Introduction to data management and data policy for RI managers

The introduction will provide a framework for the course and present the key concepts relevant to managing data and data policy within RIs, including definitions of data and typologies of RIs, the role of metadata, and operational considerations for managers.

After completing this Session, the participant will be able to: 

  • understand the key issues and concepts around the management of data and data policy within an operational RI; 
  • situate his or her own RI within a typology of research infrastructures, and appreciate how this influences the treatment of data management and policy;
  • determine how different drivers affect how data management and data policy are implemented in an RI; and
  • assess the different relevant factors in play when implementing data management and policy in real-time settings, such as resources, technologies, and staff competencies.
Session 2 – Operational oversight of data management and policy in an RI

This Session will cover the role of data policy and data management in RIs, including how data policy for different data management domains should be crafted and formulated for different audiences and purposes, and aligned with internal and external drivers and implemented in RI workflows. It will also address how policy can be converted into practical guidelines for different user groups.

After completing this Session, the participant will be able to:

  • identify and develop relevant data management policies for research infrastructure throughout the data lifecycle;
  • define appropriate workflows, roles, and responsibilities among research infrastructure staff for data management and policy implementation;
  • understand, catalogue, and manage different types of data (datasets, software, workflows, etc.) handled and generated in the research infrastructure and by its users;
  • decide what is needed to make data and metadata accessible for long-term preservation;
  • understand data sharing and access (open data vs closed data) and restrictions/control in an Open Science context; and
  • assess certification mechanisms available for data management in different research infrastructures/scientific communities and determine whether they are needed for the research infrastructure.
Session 3 – FAIR principles and their application

This Session focuses on deepening the participants’ understanding of the FAIR principles and empowering them to adapt and extend the principles of findability, accessibility, interoperability, and reusability in their RI. By the end of this Session, the participants will be able to set up the guidelines for FAIRness in their Research Infrastructure, and plan the development and/or integration of the protocols, techniques and tools required to achieve such FAIRness.

After completing this Session , the participants will be able to:

  • understand the FAIR principles in general and the main concepts and vocabulary used;
  • make data findable, understanding the most common metadata schemas and the importance of generating persistent identifiers;
  • make data accessible, describing the different protocols to access data, both for humans and for machines;
  • make data interoperable, using ontologies and other semantic artifacts;
  • make data reusable, selecting the appropriate license and providing rich metadata to facilitate its reuse and provenance; and
  • implement FAIR principles in the setting of a real research infrastructure.
Session 4 – Data management plans for Research Infrastructures

Developing a reliable and specific data management plan is a core business of each research infrastructure. A data management plan ensures that the RI’s data will be adequately described and made available to a broader public. This enables a more thorough perspective for the re-use of data and the formulation of innovative data-centric research questions. This Session turns the theoretical knowledge of data management policies and plans into practice.

After completing this Session , the participant will be able to:

  • understand the importance of dedicated data management plans for increased data quality of the research infrastructures’ main assets;
  • support compliance with the research Infrastructure’s data management policies;
  • contribute to knowledge exchange with regard to data management by the research infrastructure’s gateway function;
  • increase the quality of service in their RI by improving the essential cornerstones of research data management plans; 
  • develop an individual and personalised template for a data management plan for the participants’ research infrastructure; and 
  • ensure improved quality of the draft template by expert-level feedback after assessment of the provided data management plan template.
The programme

The programme

16 June 2023 Introduction to data management and data policy for RI managers
9:00-10:00 Setting the stage for the course, background, definitions, framework, learning objectives and course goals, including first exercise
10:00-10:30 Break 
10:30-12:00 Practical aspects, with exercise

After the Session: written assignment, to be delivered by June 21st, assessed, and discussed on Jun 23, 2023, with opt-in session at 8:30
23 June 2023 Operational oversight of data management and policy in an RI
9:00-10:00 Definitions and model for policy development, with exercise
10:00-10:30 Break
10:30-12:00 Moving from principles to practice with data policy
12:00-13:00 Lunch break
13:00-14:30 Exercises 

After the Session: written assignment, to be delivered by June 28th, assessed, and discussed on June 30, with opt-in session at 8:30
30 June 2023 FAIR principles and their application
9:00 – 09:15 Introduction to FAIR principles
9:15 – 10:00 Make your data findable 
10:00 – 10:45 Make your data accessible
10:45 – 11:00 Break
11:00 – 11:45 Make your data interoperable
11:45 – 12:30 Make your data reusable
12:30 – 13:30 Lunch
13:30 – 15:00 FAIR principles implementations & exercise  
7 July 2023 Data management plans for Research Infrastructures
9:00 – 10:00 Data management plans: its main parts and usefulness for RI and researchers of the RI 
10:00 -10:30 Break
10:30 – 13:00 Data management plans: setting up DMP templates for your Research Infrastructure

After the course: written assignment: Data management plans: Bring your own facility and propose a template with feedback moment early September (date: tbd)
The Faculty

The Faculty

NameShort Bio
Marialuisa LavitranoMarialuisa Lavitrano Marialuisa Lavitrano is professor of Pathology, director of Molecular Medicine Lab, and director of the School of Oncology at the University of Milano-Bicocca where she was pro-rector for International Affairs for 8 years (2006–2013). She is the Director of EMMRI – the Executive Masters in Management of Research Infrastructures.
Prof. Marialuisa Lavitrano is among the most outstanding scientists currently working at UNIMIB. Enrolled at UNIMIB in 2001, a few years after the creation of the University, she played a key role in the development and establishment of UNIMIB as one of the most promising universities in Italy.
She is the Director of BBMRI Italy and she is part of the Board of Directors of the EOSC Association.
Enrico GuariniEnrico Guarini, PhD, is Associate Professor of Business Administration and Management at the Department of Business and Law, University of Milano-Bicocca, Italy. MSc and PhD in Business Administration and Management both from Bocconi University. He has taught at the University of Modena and Reggio Emilia and at Bocconi University. Visiting Professor at the University of Malta, Bethlehem University, Polytechnic Institute of Càvado and Ave, and Honorary Visiting Fellow at the University of Technology Sydney. He has a long-standing experience in executive education at SDA Bocconi School of Management where he has been a member of the Board and served as the Director of custom programs for public administration, healthcare, and nonprofit organizations. In his research he adopts a public interest perspective to examine primarily financial management and governance in the public sector. His research explores the interaction of financial governance and accounting rules with decisions and behaviors applied at the operational management level of government tiers, departments and agencies, and how this facilitates or impedes policy outcomes. He has published articles in Financial Accountability & Management, International Review of Administrative Sciences, Public Money & Management, Accounting History, Accounting History Review, Qualitative Research in Accounting & Management, Accounting, Auditing & Accountability Journal, among others. He is a member of the Scientific Committee of Azienda Pubblica (the Italian journal for public management) and of the Editorial Board of Public Sector Financial Management Book Series at Palgrave. He serves as Co-Chair of the Special Interest Group on Local Governance at the International Research Society for Public Management (IRSPM). 
Brian KleinerBrian Kleiner is head of Data Services at FORS, Swiss Centre of Expertise in the Social Sciences, where he oversees a national digital data archive, including the acquisition, curation, and dissemination of social science data from research projects conducted in Switzerland. His professional interests focus on the development of research infrastructures and their operation in real settings, as well as different aspects of data management and policy design. 
Esteban GonzálezEsteban González is Research Software Engineer at the Ontology Engineering Group – Universidad Politecnica de Madrid. He is facilitator of the Open Science Community at the same university and co-coordinator of the EELISA Open Science Community. His  career has been focused in Research Data Management and Citizen Science. Recently, he has started his PhD on Natural Language Processing and publication of research objects.
Alexander BotzkiAlexander Botzki holds a Master in Chemistry and completed his PhD in Computational Medicinal Chemistry at Regensburg University, Germany. Following a PostDoc at Sanofi Synthelabo in Strasbourg, France, he moved to Belgium working at DevGen (now Syngenta) for 3 years as Computational Medicinal Chemist. After a subsequent position at Algonomics as Computational Scientist, Alexander started at VIB where he is currently heading the Technology Training unit. In the period at VIB, in prior positions, he was Head of the Bioinformatics Core as well as Laboratory Informatics Specialist responsible for the roll-out of an electronic laboratory notebook system and the implementation of lab informatics solutions. One important aspect of his current service role within TEchnology Training and as ELIXIR Belgium Training Coordinator is the deployment of a comprehensive offering in short-term hands-on training courses in bioinformatics open to life scientists in Belgium and beyond.  
Korbinian BöslKorbinian Bösl is a senior engineer at the Computational Biology Unit (CBU) at the University of Bergen. He is the Data Management Coordinator of ELIXIR-NO and part of the operational management team of the Centre for Digital Life Norway. He is coordinating data management efforts between the Life Science Research Infrastructures in Norway. Korbinian has a research background on systems host-pathogen interactions and holds a PhD in Molecular Medicine from the Norwegian University of Science and  Technology. He has developed and implemented a research data management training program for life scientists across Norway.
Daniel FariaDaniel Faria is an assistant professor of computer science and engineering at Instituto Superior Técnico, and an integrated researcher at INESC-ID, where he carries out research on topics spanning Bioinformatics, Artificial Intelligence and the Semantic Web.
He is also a member of ELIXIR, where he serves as an editorial board member of the RDM-kit and co-leads the data and interoperability platform at the national level (BioData.pt), as well as being the scientific coordinator of the national training program “Ready for BioData Management?”
Keith Jeffery Keith Jeffery is an independent consultant and currently working for UKRI/BGS (British Geological Survey) on EPOS-SP and ENVRIFAIR and for EPOS-ERIC on EPOS and EOSC-Future as well as for others on advanced topics.  He is past Director IT at STFC Rutherford Appleton Laboratory with 360,000 users, a large computing centre and department. Keith holds 3 honorary visiting professorships, is an elected Fellow of the Geological Society of London and the British Computer Society, a member of the BCS academy, is a Chartered Engineer and Chartered IT Professional and an Honorary Fellow of the Irish Computer Society.  Keith is past-President of ERCIM and past President of euroCRIS, and serves on international expert groups, conference boards and assessment panels.  He has advised government on IT.  He chaired the EC Expert Groups on GRIDs and on CLOUD Computing.
How to apply

 How to apply

Application period starts 3 April 2023 and ends 5 May 2023. Selected participants are informed via email by 15 May 2023. If the participant wishes to cancel their participation, they are required to inform the organisers at least 2 weeks prior to the course. 

Apply by filling in the form below and upload your CV (max 3 pages)


The pilot short course is offered free-of-charge and requires the participant’s full commitment during lectures, group work and written assignments.


Info & Contact

To pass the course the participant must attend at least 80% of the lectures.

For any doubt or information, please see the FAQs below or send an email to ritrainplus[at]unimib.it


Why should I take this programme?

The programme is aimed at managers, operators and other professionals at Research Infrastructures and Core Facilities.

Who is behind this programme?

The pilot programme is designed by academic and educational experts in the RItrainPlus project who have a long experience working or leading Research Infrastructures or other scientific institutions.

How is the programme organized?

The programme  is divided into seven short courses, each containing sessions.  The short courses take up 16–32 hours each, plus individual work.

How do I take part?

The participants can take up either the whole programme and progress from one short course to the next, or take an individual short course that best fits their needs. For those interested in taking up the whole programme, it should be noted that some activities will be overlapping. Participants are advised to check the course schedules for more information.

What’s expected of me?

The participant is expected to participate in at least 80% of the scheduled activities. The courses are assessed in various ways. 

Do I have to take all the sessions in a short course? Can I just choose what I like?

The participant needs to participate in all the modules in the short course. 

What does it cost?

The pilot courses are offered free of charge

How are the courses taught?

Most of the short courses are offered as online intensive courses that take up 2-6 consecutive days. The courses are taught by experienced academics at RItrainPlus partner universities and institutions with  invited international experts.The courses will be delivered in the period June-September 2023.

How do I apply?

The application period is 03.04.2023 – 05.05.2023. Apply to the short course by submitting a short motivation letter and your CV. The chosen applicants will be informed via email by 15. 05. 2023.

When will I know if my application has been accepted?

Selected participants are informed by May 15th.

What if I realize that I cannot participate anymore after I’ve been admitted to participation?

If the participant wishes to cancel their participation, they are required to inform the organizers at least two weeks prior to the starting of the course

Data management