Data Curation in the Era of Research Infrastructures

Governments and funding bodies enact policies to set up Research Infrastructures (RIs) to integrate data from different environmental monitoring research sites. The goal of such policies is to publicly open access to research data to support research and innovation and to develop policies for sustaining RIs and the environment at large. However, little is known about the data curation practices of environmental monitoring research scientists at the origins of data. Informed by practice theories on the constitutive entanglement of the social and the material in everyday organisational work, the study zooms-in on the data curationpractices utilised by environmental monitoring research scientists to create data that is of good quality and reliable for sharing. Early findings are based on observations and semi-structured interviews of participants in environmental research sites, who collaborate on taking samples of animal and plant species in marine and terrestrial environments. We find that data curation at the origins of data are rife with challenges and opportunities in: data competence, data management and data quality practices. This poster submission concludes with implications of such practices for data governance of large-scale RIs

Data Sharing Frames: How Scientists Understand the Work of Sharing Scientific Data

The curation of data is fundamental to their wider dissemination and use. This paper investigates the frames of workers who perform data curation in scientific contexts. We view data curation as a sense-making practice, where workers collaborate to disseminate meaningful data to a broad set of prospective users. Previous Information Systems investigations have suggested that data-related activities are dependent on workers’ understanding of their local work context. We expand this with an evolving and long-term view. We use a stepwise-deductive induction method to examine how scientists understand the work involved in curating scientific data for public sharing. We draw on frames as the theoretical lens of the study that enables us to identify three data sharing frames – the object, curation, and aligning frames – as important frames that shape how scientists curate data for public sharing. Our analysis provides a deeper understanding of the nuances of managing scientific data for public access. Our main contribution is the articulation of an evolving and long-term view of how workers approach their tasks in getting data ready for long-term public use

Making Data Work: A Systematic Mapping of Collaborative Data Curation Practices

A growing body of literature in Information Systems focuses on the collaborative data curation practices that support the use of novel technologies in the ongoing datafication of work and organizing. In this study, we map the practices and processes that help make data useful and meaningful so that organizations can take advantage of these technologies. We examine 54 empirical studies and focus on the individuals and groups that collaborate to make data useful and meaningful. We identify the following collaborative data curation practices: (i) engaging multiple users in cooperation, (ii) involving higher-level stakeholders, and (iii) using shared resources. We contribute to the IS literature by broadening the view of data curation as an organizational practice that requires the collective, situated, and ongoing engagement of multiple actors making flexible and interpretive decisions to identify and resolve challenges related to working with data