Research data management has become an inevitable part of research, and both funding agencies and publishers nowadays require open and reusable data. This article focuses on one of the most prominent initiatives promoting reusability of research data - the FAIR guiding principles - nowadays widely accepted as the new standard for research data management. Through semi-structured interviews, we investigated researchers' experiences of practicing FAIR research data management within the context of a multi-stakeholder project within the field of health research funded by the European Commission. Our analysis showed that the informants' experiences of practicing FAIR research data management differed largely depending on which scientific tradition they belonged to; something that previous studies have attributed to shortcomings in the current infrastructure, lack of resources and persistent cultures around data sharing in the wider scientific community. Drawing on previous work presented within the field of Critical Data Studies (CDS), we argue that our findings point to a more fundamental problem; namely the failure to recognize that the FAIR framework is built on a positivist conceptualization of data. We argue that if FAIR is to have any chance of succeeding in its ambitions to be as inclusive and all-encompassing as it wants to be, these insights need to be taken more into account and provide some potential pathways.

Background: The implementation of a data-driven approach within the health care system happens in a rapid pace; including in the eldercare sector. Within Swedish eldercare, data-driven health approach is not yet widely implemented. In the specific context of long-term care for older adults, quality of care is as much determined by how social care is being performed as it is by what kind medical care that is provided. In particular, relational aspects have been proven to have a crucial influence on the experience of quality of care for the actors involved. Drawing on ethnographic material collected at a Swedish nursing home, this paper explores in what way the relational aspects of care could potentially become affected by the increased use of a data-driven health approach. Methods: An ethnographic approach was adopted in order to investigate the daily care work at a long-term care facility as it unfolded. Fieldwork was conducted at a somatic ward in a Swedish long-term care facility over 4 months (86 h in total), utilizing the methods of participant observation, informal interviews and document analysis. The material was analyzed iteratively throughout the entire research process adopting thematic analysis. Results: Viewing our ethnographic material through an observational lense problematising the policy discourse around data-driven health approach, two propositions were developed. First, we propose that relational knowledge risk becoming less influential in shaping everyday care, when moving to a data-driven health approach. Second, we propose that quality of care risk becoming more directed on quality of medical care at the expense of quality of life. Conclusion: While the implementation of data-driven health approach within long-term care for older adults is not yet widespread, the general development within health care points towards a situation in which this will become reality. Our study highlights the importance of taking the relational aspects of care into consideration, both during the planning and implementation phase of this process. By doing this, the introduction of a data-driven health approach could serve to heighten the quality of care in a way which supports both quality of medical care and quality of life.

Conversational agents (CA) are increasingly used to manage and coordinate household chores and everyday activities at home. However, these technologies should be adaptive to age-specific characteristics in order to be considered beneficial for the ageing population. This study presents a participatory design of a conversational agent to provide cognitive support in recipe following and nutrition advice for adults aged 65 and over. Through a qualitative thematic analysis, the study explores older adults’ expectations, interactions and experiences with the agent in order to identify age-specific challenges of interacting with CAs. Data consists of a participatory design workshop with eight older adults (aged 65 and over), followed by a Wizard of Oz study with ten older adults interacting with the agent in the kitchen environment in a laboratory setting. Results demonstrate that older adults consider conversational agents as beneficial for providing personalised recipe recommendations, advising the user to choose appropriate ingredients and reminding them of their dietary intake. When interacting with the agent older adults displayed challenges with confirmation and repetition, questioning and correcting, the lack of conversational responses, and difficulties in hearing and understanding the multi-modal interaction. Older adults experience agents as collaborators, but not as conversational partners. The study concludes that the accessibility and inclusiveness of conversational agents regarding voice interaction could be improved by further developing participatory methods with older adults.