Thoughts on Starting the CODATA Data Science Journal

This essay discusses some of the considerations that led to the founding of the [CODATA] Data Science Journal. Three factors were most relevant to the founding. First, there was a need to have a more formal publication mechanism for the papers given at the biennial CODATA International Conferences. Second, there was a pressing need for data science advancements made in one area of scientific data work to be shared with other scientific disciplines. Lastly the increasing number of scientists interested in data, throughout science, and throughout the world, required a more convenient publication outlet. Thus arose the Data Science Journal

Funeral practices and grief

Does restricting the ceremonial/ritual arrangements around a cremation to a minimum have a negative association with grief over time? This question has increasingly concerned professionals in the funeral industry as well as those in healthcare capacities working with bereaved persons. We examined the relationship between cremation arrangements and levels of grief. Bereaved people in the UK completed questionnaires 2 to 5 months post-loss and a year later (N=233 with complete data). Complexity of the cremation service was not significantly related to grief; neither was satisfaction with arrangements (which was typically high). Results suggested that it makes no difference to grief whether a more minimalistic or elaborate funeral ceremony is chosen under conditions where the bereaved feel free to make choices that best suit their situation. We concluded that the funeral industry seems to be offering bereaved people an appropriate range of cremation arrangement choices to meet their needs. Important limits to generalizability are discussed. That funeral services serve multiple functions for bereaved persons is emphasized.</p

Comparative effects of verapamil and nitroprusside on left ventricular function in patients with hypertension

AbstractThe effects of verapamil were compared with those of nitroprusside at matched mean arterial pressures and heart rates in 10 symptomatic hypertensive patients during cardiac catheterization. Simultaneous radionuclide angiography and micromanometer pressure measurements were obtained to assess left ventricular pressure-volume relations. Compared with control conditions, verapamil increased left ventricular end-diastolic volume index from 57 ± 16 to 70 ± 28 ml/m2 (p = 0.05) without a significant increase in left ventricular end-diastolic pressure (from 10 ± 4 to 13 ± 6 mm Hg). Despite a downward and rightward shift in the end-systolic pressure-volume relation indicating negative inotropic effects, ejection fraction did not decrease significantly (from 52 ± 9% to 46 ± 9%); cardiac index and stroke volume index remained unchanged. The change in stroke volume index with verapamil was directly related to the magnitude of change in end-diastolic volume index (r = 0.82, p < 0.005), suggesting that the increase in enddiastolic volume did not arise purely from negative inotropic effects. Systemic vascular resistance index decreased from 42 ± 8 to 34 ± 7 mm Hg-min-m2/liter (p < 0.05).In contrast, nitroprusside decreased left ventricular end-diastolic volume index from 57 ± 16 to 41 ± 10 ml/m2 (p < 0.05), cardiac index from 3.2 ± 0.7 to 2.8 ± 0.6 liters/min per m2 (p < 0.05) and stroke volume index from 28 ± 6 to 24 ± 5 ml/m2 (p < 0.01), with no change in systemic vascular resistance index (40 ± 10 mm Hg·min·m2). The end-systolic pressure-volume relation shifted downward and leftward in all patients, stemming from altered left ventricular loading.Thus, in equihypotensive doses, verapamil and nitroprusside have markedly different effects on left ventricular function. The peripheral vasodilation and apparent improvement in left ventricular filling during verapamil balanced the negative inotropic effects, resulting in maintenance of stroke volume and cardiac index. The primary hypotensive effect of verapamil was a decrease in systemic vascular resistance, whereas that of nitroprusside was a decrease in cardiac index stemming from reduced left ventricular preload

Chemical data evaluation: General considerations and approaches for IUPAC projects and the chemistry community (IUPAC Technical Report)

The International Union of Pure and Applied Chemistry has a long tradition of supporting the compilation of chemical data and their evaluation through direct projects, nomenclature and terminology work, and partnerships with international scientific bodies, government agencies, and other organizations. The IUPAC Interdivisional Subcommittee on Critical Evaluation of Data has been established to provide guidance on issues related to the evaluation of chemical data. In this first report, we define the general principles of the evaluation of scientific data and describe best practices and approaches to data evaluation in chemistryinfo:eu-repo/semantics/publishedVersio

How should the completeness and quality of curated nanomaterial data be evaluated

Nanotechnology is of increasing significance. Curation of nanomaterial data into electronic databases offers opportunities to better understand and predict nanomaterials’ behaviour. This supports innovation in, and regulation of, nanotechnology. It is commonly understood that curated data need to be sufficiently complete and of sufficient quality to serve their intended purpose. However, assessing data completeness and quality is non-trivial in general and is arguably especially difficult in the nanoscience area, given its highly multidisciplinary nature. The current article, part of the Nanomaterial Data Curation Initiative series, addresses how to assess the completeness and quality of (curated) nanomaterial data. In order to address this key challenge, a variety of related issues are discussed: the meaning and importance of data completeness and quality, existing approaches to their assessment and the key challenges associated with evaluating the completeness and quality of curated nanomaterial data. Considerations which are specific to the nanoscience area and lessons which can be learned from other relevant scientific disciplines are considered. Hence, the scope of this discussion ranges from physicochemical characterisation requirements for nanomaterials and interference of nanomaterials with nanotoxicology assays to broader issues such as minimum information checklists, toxicology data quality schemes and computational approaches that facilitate evaluation of the completeness and quality of (curated) data. This discussion is informed by a literature review and a survey of key nanomaterial data curation stakeholders. Finally, drawing upon this discussion, recommendations are presented concerning the central question: how should the completeness and quality of curated nanomaterial data be evaluated

Metadata stewardship in nanosafety research: learning from the past, preparing for an "on-the-fly" FAIR future

Introduction: Significant progress has been made in terms of best practice in research data management for nanosafety. Some of the underlying approaches to date are, however, overly focussed on the needs of specific research projects or aligned to a single data repository, and this “silo” approach is hampering their general adoption by the broader research community and individual labs. Methods: State-of-the-art data/knowledge collection, curation management FAIRification, and sharing solutions applied in the nanosafety field are reviewed focusing on unique features, which should be generalised and integrated into a functional FAIRification ecosystem that addresses the needs of both data generators and data (re)users. Results: The development of data capture templates has focussed on standardised single-endpoint Test Guidelines, which does not reflect the complexity of real laboratory processes, where multiple assays are interlinked into an overall study, and where non-standardised assays are developed to address novel research questions and probe mechanistic processes to generate the basis for read-across from one nanomaterial to another. By focussing on the needs of data providers and data users, we identify how existing tools and approaches can be re-framed to enable “on-the-fly” (meta) data definition, data capture, curation and FAIRification, that are sufficiently flexible to address the complexity in nanosafety research, yet harmonised enough to facilitate integration of datasets from different sources generated for different research purposes. By mapping the available tools for nanomaterials safety research (including nanomaterials characterisation, non-standard (mechanistic-focussed) methods, measurement principles and experimental setup, environmental fate and requirements from new research foci such as safe and sustainable by design), a strategy for integration and bridging between silos is presented. The NanoCommons KnowledgeBase has shown how data from different sources can be integrated into a one-stop shop for searching, browsing and accessing data (without copying), and thus how to break the boundaries between data silos. Discussion: The next steps are to generalise the approach by defining a process to build consensus (meta)data standards, develop solutions to make (meta)data more machine actionable (on the fly ontology development) and establish a distributed FAIR data ecosystem maintained by the community beyond specific projects. Since other multidisciplinary domains might also struggle with data silofication, the learnings presented here may be transferable to facilitate data sharing within other communities and support harmonization of approaches across disciplines to prepare the ground for cross-domain interoperability. Visit WorldFAIR online at http://worldfair-project.eu. WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393

Metadata stewardship in nanosafety research: learning from the past, preparing for an "on-the-fly" FAIR future

Introduction: Significant progress has been made in terms of best practice in research data management for nanosafety. Some of the underlying approaches to date are, however, overly focussed on the needs of specific research projects or aligned to a single data repository, and this "silo" approach is hampering their general adoption by the broader research community and individual labs.Methods: State-of-the-art data/knowledge collection, curation management FAIrification, and sharing solutions applied in the nanosafety field are reviewed focusing on unique features, which should be generalised and integrated into a functional FAIRification ecosystem that addresses the needs of both data generators and data (re)users.Results: The development of data capture templates has focussed on standardised single-endpoint Test Guidelines, which does not reflect the complexity of real laboratory processes, where multiple assays are interlinked into an overall study, and where non-standardised assays are developed to address novel research questions and probe mechanistic processes to generate the basis for read-across from one nanomaterial to another. By focussing on the needs of data providers and data users, we identify how existing tools and approaches can be re-framed to enable "on-the-fly" (meta) data definition, data capture, curation and FAIRification, that are sufficiently flexible to address the complexity in nanosafety research, yet harmonised enough to facilitate integration of datasets from different sources generated for different research purposes. By mapping the available tools for nanomaterials safety research (including nanomaterials characterisation, nonstandard (mechanistic-focussed) methods, measurement principles and experimental setup, environmental fate and requirements from new research foci such as safe and sustainable by design), a strategy for integration and bridging between silos is presented. The NanoCommons KnowledgeBase has shown how data from different sources can be integrated into a one-stop shop for searching, browsing and accessing data (without copying), and thus how to break the boundaries between data silos.Discussion: The next steps are to generalise the approach by defining a process to build consensus (meta)data standards, develop solutions to make (meta)data more machine actionable (on the fly ontology development) and establish a distributed FAIR data ecosystem maintained by the community beyond specific projects. Since other multidisciplinary domains might also struggle with data silofication, the learnings presented here may be transferrable to facilitate data sharing within other communities and support harmonization of approaches across disciplines to prepare the ground for cross-domain interoperability

Leukocyte surface biomarkers implicate deficits of innate immunity in sporadic Alzheimer\u27s disease

Introduction: Blood-based diagnostics and prognostics in sporadic Alzheimer\u27s disease (AD) are important for identifying at-risk individuals for therapeutic interventions. Methods: In three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses. Results: We identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aβ clearance. A proposed panel including four leukocyte markers – CD11c, CD59, CD91, and CD163 – predicts patients’ PET Aβ status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts. Conclusion: Our finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis

Metadata stewardship in nanosafety research: learning from the past, preparing for an “on-the-fly” FAIR future

Introduction: Significant progress has been made in terms of best practice in research data management for nanosafety. Some of the underlying approaches to date are, however, overly focussed on the needs of specific research projects or aligned to a single data repository, and this “silo” approach is hampering their general adoption by the broader research community and individual labs.Methods: State-of-the-art data/knowledge collection, curation management FAIrification, and sharing solutions applied in the nanosafety field are reviewed focusing on unique features, which should be generalised and integrated into a functional FAIRification ecosystem that addresses the needs of both data generators and data (re)users.Results: The development of data capture templates has focussed on standardised single-endpoint Test Guidelines, which does not reflect the complexity of real laboratory processes, where multiple assays are interlinked into an overall study, and where non-standardised assays are developed to address novel research questions and probe mechanistic processes to generate the basis for read-across from one nanomaterial to another. By focussing on the needs of data providers and data users, we identify how existing tools and approaches can be re-framed to enable “on-the-fly” (meta) data definition, data capture, curation and FAIRification, that are sufficiently flexible to address the complexity in nanosafety research, yet harmonised enough to facilitate integration of datasets from different sources generated for different research purposes. By mapping the available tools for nanomaterials safety research (including nanomaterials characterisation, nonstandard (mechanistic-focussed) methods, measurement principles and experimental setup, environmental fate and requirements from new research foci such as safe and sustainable by design), a strategy for integration and bridging between silos is presented. The NanoCommons KnowledgeBase has shown how data from different sources can be integrated into a one-stop shop for searching, browsing and accessing data (without copying), and thus how to break the boundaries between data silos.Discussion: The next steps are to generalise the approach by defining a process to build consensus (meta)data standards, develop solutions to make (meta)data more machine actionable (on the fly ontology development) and establish a distributed FAIR data ecosystem maintained by the community beyond specific projects. Since other multidisciplinary domains might also struggle with data silofication, the learnings presented here may be transferrable to facilitate data sharing within other communities and support harmonization of approaches across disciplines to prepare the ground for cross-domain interoperability