Because good research needs good data

Case studies on Open Science in the context of ERC projects - Set 5

TitleCase studies on Open Science in the context of ERC projects - Set 5
Publication TypeReport
Year of Publication2019
AuthorsWhyte A, Banelytė V
Date Published01/2019
Report NumberVersion 1.0

This document presents the fifth of five sets of case studies that have been produced in the framework of the ‘Study on open access to publications and research data management and sharing within ERC projects’. This study has been procured by the ERC Executive Agency under contract number ERCEA/A1/2016/06.

The following three case studies are included in this set:

- Repression and the Escalation of Conflict (RATE)

The RATE project, led by Professor Sabine Carey at the University of Mannheim, sheds light on the relationship between killings of journalists and political repression. This data-rich and empirically based political science research builds on a variety of existing data sources. Some are the product of the research team’s previous research, and some are gathered from media sources. The project is generating fresh data from these and from newly collected surveys and interviews. Professor Carey’s team has produced online resources based on these, and deposited datasets and code in open repositories. Open sharing of their novel reference datasets has spawned new lines of enquiry for the research team, and for the broader political science community, into pro-government militias and their influence on levels of political violence.

- Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID)

The TransMID project is consolidating recent work in infectious disease modelling that employs social contact data to analyse patterns in disease transmission. By extensively collecting and reusing social contact data from previous studies, Professor Niel Hens at the University of Hasselt is finding the key parameters for modelling across these datasets. This should better equip epidemiologists to assist public health agencies in responding to epidemics. Researchers need to share their data more often for that to happen. Hens and his collaborators offer their community an example by sharing datasets, including their own results, as publicly and quickly as possible. In doing so the team gains impact for TransMID outputs and, by collaborating in data analysis tool development, Hens and his colleagues are laying the ground for others in the field to benefit. The potential is threefold; firstly, data sharers can more readily enhance the reusability of their datasets by describing the data collection context using common parameters that TransMID has found through systematic analysis of previous studies. Secondly, the datasets described by these parameters are used by TransMID as raw material for the development of software tools that enable new systematic analyses. Thirdly, researchers can more readily deal with ethical questions by learning how TransMID addresses them.

- Evolutionary reconstruction of viral spread in time and space (VIRALPHYLOGEOGRAPHY)

A detailed characterisation of pathogen spread in space and time is crucial for epidemiologists to identify the causal mechanisms leading to disease emergence, epidemic expansion and endemic maintenance. The project VIRALPHYLOGEOGRAPHY, led by Associate Professor Philippe Lemey at KU Leuven aimed to reconstruct the way viruses spread through time and space. While investigating how genetic variation within viral pathogens, such as influenza, Ebola and HIV, emerges and persists in various different hosts and environments, Lemey and his team developed a comprehensive statistical framework for uncovering the spatial and temporal dynamics of pathogen genomes. For their research, the team adopted an approach that promotes openness and transparency. As the project’s results can directly impact epidemic emergency responses, they favoured open-source research tools as well as open sharing of research methods and outputs.