Abstract
Objectives: Healthcare professionals' high risk of infection and burnout in the first months of the COVID19 pandemic probably hindered their much-needed preparedness to respond. We aimed to inform how individual and institutional factors contributed for the preparedness to respond during the first months of a public health emergency. Study design: Cross-sectional study. Methods: We surveyed healthcare workers from a Local Health Unit in Portugal, which comprises primary health care centers and hospital services, including public health units and intensive care units, in the second and third months of the COVID-19 epidemic in Portugal. The 460 answers, completed by 252 participants (about 10% of the healthcare workers), were analyzed using descriptive statistics and multiple logistic regressions. We estimated adjusted odds ratios for the readiness and willingness to respond. Results: Readiness to respond was associated with the perception of adequate infrastructures (aOR = 4.04, P < 0.005), lack of access to personal protective equipment (aOR = 0.26, P < 0.05) and organization (aOR = 0.31, P < 0.05). The willingness to act was associated with the perception of not being able to make a difference (aOR = 0.05, P < 0.005), risk of work-related burnout (aOR = 21.21, P < 0.01) and experiencing colleagues or patients' deaths due to COVID-19 (aOR = 0.24, P < 0.05). Conclusions: Adequate organization, infrastructures, and access to personal protective equipment may be crucial for workers' preparedness in a new public health emergency, as well workers' understanding of their roles and expected impact. These factors, together with the risk of work-related burnout, shall be taken into account in the planning of the response of healthcare institutions in future public health emergencies.

Abstract
OBJECTIVES: Existing individual-level human data cover large populations on many dimensions such as lifestyle, demography, laboratory measures, clinical parameters, etc. Recent years have seen large investments in data catalogues to FAIRify data descriptions to capitalise on this great promise, i.e. make catalogue contents more Findable, Accessible, Interoperable and Reusable. However, their valuable diversity also created heterogeneity, which poses challenges to optimally exploit their richness. METHODS: In this opinion review, we analyse catalogues for human subject research ranging from cohort studies to surveillance, administrative and healthcare records. RESULTS: We observe that while these catalogues are heterogeneous, have various scopes, and use different terminologies, still the underlying concepts seem potentially harmonizable. We propose a unified framework to enable catalogue data sharing, with catalogues of multi-center cohorts nested as a special case in catalogues of real-world data sources. Moreover, we list recommendations to create an integrated community of metadata catalogues and an open catalogue ecosystem to sustain these efforts and maximise impact. CONCLUSIONS: We propose to embrace the autonomy of motivated catalogue teams and invest in their collaboration via minimal standardisation efforts such as clear data licensing, persistent identifiers for linking same records between catalogues, minimal metadata 'common data elements' using shared ontologies, symmetric architectures for data sharing (push/pull) with clear provenance tracks to process updates and acknowledge original contributors. And most importantly, we encourage the creation of environments for collaboration and resource sharing between catalogue developers, building on international networks such as OpenAIRE and research data alliance, as well as domain specific ESFRIs such as BBMRI and ELIXIR. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.

Abstract
In this paper, we report on new findings about the results of an empirical study which aims to investigate how the COVID-19 pandemic has been shaping nomadic work practices and also challenging the lifestyles of digital nomads (DN). To do this, we collected textual data from posts in a Reddit community. We argue that, in order to understand how to design technical solutions for the so-called 'new normal' working conditions, one way to approach this is to understand how digital nomads are being impacted in their work practices and routines, and also how they are seeing the future of their technology-mediated work-life space. Finally, we show how evidence collected from DNs about their experiences and difficulties perceived during the pandemic period can inform CSCW researchers worldwide about future design-oriented strands.

Abstract
The purpose of this paper is to reveal a set of new results obtained from an ongoing investigation focused on the way that the particular characteristics which are inherent to 'wannabe' digital nomads' activities contribute to the sustainability of the whole digital nomad ecosystem. In line with the premise of this research, we assume the importance of understanding the impacts that are being felt in the personal knowledge management ecology practices and routines of digital nomads as experienced by a specific online population (i.e., Reddit user base), together with a deep and wide examination of their preferences and expectations regarding the technology-mediated work-life issues that exert a direct influence on the digital nomad community. To this end, we gathered and further processed text posts and comments from users in the '/r/digitalnomad' subreddit. From a sociotechnical standpoint, the empirical data extracted from this sample population about the wannabe/how to be digital nomad symbiotic ecosystem can provide insightful information for researchers worldwide about future design-level interventions. © 2022 IEEE.

Abstract
In this paper we present findings from a bibliometric evaluation of scientific publications on human-AI systems, indexed in the Dimensions database over the past five years (2018 to 2022). The study maps the research landscape in this burgeoning area, as it relates to the topic of collaboration. To this end, we assessed publication and citation counts over time, authorship-level indicators, and keyword occurrence frequency. We also examined funding information as an indicator of research priorities, alongside usage-based statistics and alternative metrics such as social media mentions, recommendations, and reads. Our preliminary findings highlight a significant focus on aspects like trust, explainability, transparency, and autonomy in highly complex scenarios through the use of generative models and hybrid interaction techniques. The results also reveal a growth in the number of publications and funding grants, although a certain lack of maturity is observable in terms of citation patterns and coherence of thematic clusters. © 2022 IEEE.

Abstract
Refactoring code manually can be complex. Several refactoring tools were developed to mitigate the effort needed to create more readable, adaptable, and maintainable code. However, most of them continue to provide late feedback, assistance, and support on how developers should improve their software. That's where the concept of Live Refactoring comes in. We believe the immediate and continuous suggestion of refactoring candidates to the code will help reduce this problem. Therefore, we prototyped a Live Refactoring Environment that identifies, recommends, and applies Extract Method refactorings. We carried out an empirical experiment that showed us that our approach helped developers reach better code, with more quality, improving their refactoring experience.