The information environment of scientific research requires fundamental changes. Decisionmaking and research assessment cannot be based on opaque and non-inclusive information anymore. The... Show moreThe information environment of scientific research requires fundamental changes. Decisionmaking and research assessment cannot be based on opaque and non-inclusive information anymore. The signatories of the Barcelona Declaration on Open Research Information have taken responsibility for transforming how research information is created and used. Openness of information should become a new standard in science. This introduction aims to provide a brief overview of the Barcelona Declaration, including its context, aims, motivations, and potential challenges for implementation. Show less
Background The COVID-19 pandemic has challenged healthcare systems and research worldwide. Data is collected all over the world and needs to be integrated and made available to other researchers... Show moreBackground The COVID-19 pandemic has challenged healthcare systems and research worldwide. Data is collected all over the world and needs to be integrated and made available to other researchers quickly. However, the various heterogeneous information systems that are used in hospitals can result in fragmentation of health data over multiple data 'silos' that are not interoperable for analysis. Consequently, clinical observations in hospitalised patients are not prepared to be reused efficiently and timely. There is a need to adapt the research data management in hospitals to make COVID-19 observational patient data machine actionable, i.e. more Findable, Accessible, Interoperable and Reusable (FAIR) for humans and machines. We therefore applied the FAIR principles in the hospital to make patient data more FAIR. Results In this paper, we present our FAIR approach to transform COVID-19 observational patient data collected in the hospital into machine actionable digital objects to answer medical doctors' research questions. With this objective, we conducted a coordinated FAIRification among stakeholders based on ontological models for data and metadata, and a FAIR based architecture that complements the existing data management. We applied FAIR Data Points for metadata exposure, turning investigational parameters into a FAIR dataset. We demonstrated that this dataset is machine actionable by means of three different computational activities: federated query of patient data along open existing knowledge sources across the world through the Semantic Web, implementing Web APIs for data query interoperability, and building applications on top of these FAIR patient data for FAIR data analytics in the hospital. Conclusions Our work demonstrates that a FAIR research data management plan based on ontological models for data and metadata, open Science, Semantic Web technologies, and FAIR Data Points is providing data infrastructure in the hospital for machine actionable FAIR Digital Objects. This FAIR data is prepared to be reused for federated analysis, linkable to other FAIR data such as Linked Open Data, and reusable to develop software applications on top of them for hypothesis generation and knowledge discovery. Show less
Schumann, S.; Vegt, I. van der; Gill, P.; Schuurman, B. 2019
In recent years, the use of primary data in terrorism research has increased. In order to maximise the benefits of this trend, we want to encourage terrorism scholars to implement open science... Show moreIn recent years, the use of primary data in terrorism research has increased. In order to maximise the benefits of this trend, we want to encourage terrorism scholars to implement open science practices more systematically. This article therefore presents different avenues towards open and reproducible terrorism studies. After introducing the open science movement and advantages of open science, we report an online survey study (N = 75) that shows that terrorism researchers have favourable attitudes towards and are keen to engage in open science activities. Findings, however, also point to key challenges that might prevent the implementation of open science in terrorism studies. Survey respondents were particularly concerned about sharing sensitive data, the risk of malicious practices, publishing in low-impact open access outlets, and indicated that open science seemed mainly targeted at quantitative research. To illustrate how researchers from different backgrounds and with potential resource restrictions can adopt open science practices, we propose practical solutions to address and reflect on these barriers. Show less
