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Background: studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure.Objective: our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization.Methods: we used harmonized data from 77,434 mother-child dyads from 9 birth cohorts in the European Union Child Cohort Network when the child was 5 to 11 years old. Associations were examined through the DataSHIELD platform by using adjusted logistic regression models, which were fitted separately for each cohort and combined by using random effects meta-analysis.Results: the prevalence of early-life cat and dog ownership ranged from 12% to 45% and 7% to 47%, respectively, and the prevalence of asthma ranged from 2% to 20%. There was no overall association between either cat or dog ownership and asthma (odds ratio [OR] = 0.97 [95% CI = 0.87-1.09] and 0.92 [95% CI = 0.85-1.01], respectively). Timing and degree of ownership did not strongly influence associations. Cat and dog ownership were also not associated with cat- and dog-specific allergic sensitization (OR = 0.92 [95% CI = 0.75-1.13] and 0.93 [95% CI = 0.57-1.54], respectively). However, cat- and dog-specific allergic sensitization was strongly associated with school-age asthma (OR = 6.69 [95% CI = 4.91-9.10] and 5.98 [95% CI = 3.14-11.36], respectively). There was also some indication of an interaction between ownership and sensitization, suggesting that ownership may exacerbate the risks associated with pet-specific sensitization but offer some protection against asthma in the absence of sensitization.Conclusion: our findings do not support early-life cat and dog ownership in themselves increasing the risk of school-age asthma, but they do suggest that ownership may potentially exacerbate the risks associated with cat- and dog-specific allergic sensitization.

The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community. The LifeCycle project received funding from the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 733206 LifeCycle). All study specific acknowledgements and funding are presented in the supplementary material. This manuscript reflects only the author’s view and the Commission is not responsible for any use that may be made of the information it contains.

The Database of the Southern Dutch Dialects (DSDD) aims to aggregate and standardise three existing comprehensive lexicographic dialect databases of the Flemish, Brabantic and Limburgian dialects into one integrated dataset (Van Keymeulen, et al., 2019; Van Hout, et al., 2018, De Vriend, et al., 2006). In 2016, the Research Foundation Flanders funded a medium-scale research infrastructure project, the Database of Southern Dutch Dialects (DSDD)[1], which ran from 2017 until 2020 and resulted in a harmonised dataset of concepts (Van den Heuvel, et al., 2016), a user-friendly search engine and a geo-visualisation tool. The application backend provides an Application Programming Interface (API) which will be further developed and made available to researchers to export subsets of the data for analysis using existing digital research tools. At the previous DH Benelux conferences the project team introduced the project (2017), explored the cartographic tools (2018) and demonstrated the prototype (2019). Following the launch of the DSDD platform in 2020, the team will now present the importance of the interdisciplinary approach, the final results of the project, as well as future directions beyond the project lifetime.

The known challenge of underutilization of data and biological material from biorepositories as potential resources formedical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability—entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)—are likely to address only parts of the problem. In this article,we argue that biologicalmaterial and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks.Wepropose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently., peer-reviewed

Digital cultural heritage collections in libraries, archives, and museums are increasingly being used for digital humanities research. However, traditional ways of providing access to such collections, for example through digital library interfaces, are less than ideal for researchers who are looking to build datasets around specific research questions. Inspired by the ‘Collections as Data’ movement as an approach for cultural heritage institutions to prepare their digital 1 collections for analysis using digital methods, KBR, the Royal Library of Belgium, has embarked on a 24 month project called DATA-KBR-BE (2020-2022) to facilitate data-level access to its 2 digitised and born-digital collections for digital humanities research. This paper will: a) introduce the concept of ‘Collections as Data’ while exploring the opportunities and challenges for cultural heritage institutions; b) outline the DATA-KBR-BE project and the methodology for piloting ‘Collections as Data’ at KBR; and c) present the preliminary results of initial experiments to extract thematic datasets in support of digital humanities research scenarios as a first step towards designing a sustainable data extraction workflow for KBR.