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Data Science ◽  
2022 ◽  
pp. 1-42
Author(s):  
Stian Soiland-Reyes ◽  
Peter Sefton ◽  
Mercè Crosas ◽  
Leyla Jael Castro ◽  
Frederik Coppens ◽  
...  

An increasing number of researchers support reproducibility by including pointers to and descriptions of datasets, software and methods in their publications. However, scientific articles may be ambiguous, incomplete and difficult to process by automated systems. In this paper we introduce RO-Crate, an open, community-driven, and lightweight approach to packaging research artefacts along with their metadata in a machine readable manner. RO-Crate is based on Schema.org annotations in JSON-LD, aiming to establish best practices to formally describe metadata in an accessible and practical way for their use in a wide variety of situations. An RO-Crate is a structured archive of all the items that contributed to a research outcome, including their identifiers, provenance, relations and annotations. As a general purpose packaging approach for data and their metadata, RO-Crate is used across multiple areas, including bioinformatics, digital humanities and regulatory sciences. By applying “just enough” Linked Data standards, RO-Crate simplifies the process of making research outputs FAIR while also enhancing research reproducibility. An RO-Crate for this article11 https://w3id.org/ro/doi/10.5281/zenodo.5146227 is archived at https://doi.org/10.5281/zenodo.5146227.


2021 ◽  
pp. 2100047
Author(s):  
Amel Karaa ◽  
Laura E. MacMullen ◽  
John C. Campbell ◽  
John Christodoulou ◽  
Bruce H. Cohen ◽  
...  

Author(s):  
Brinda Vallat ◽  
Benjamin Webb ◽  
Maryam Fayazi ◽  
Serban Voinea ◽  
Hongsuda Tangmunarunkit ◽  
...  

Structures of many complex biological assemblies are increasingly determined using integrative approaches, in which data from multiple experimental methods are combined. A standalone system, called PDB-Dev, has been developed for archiving integrative structures and making them publicly available. Here, the data standards and software tools that support PDB-Dev are described along with the new and updated components of the PDB-Dev data-collection, processing and archiving infrastructure. Following the FAIR (Findable, Accessible, Interoperable and Reusable) principles, PDB-Dev ensures that the results of integrative structure determinations are freely accessible to everyone.


2021 ◽  
pp. 193229682110581
Author(s):  
Juan Espinoza ◽  
Nicole Y. Xu ◽  
Kevin T. Nguyen ◽  
David C. Klonoff

The current lack of continuous glucose monitor (CGM) data integration into the electronic health record (EHR) is holding back the use of this wearable technology for patient-generated health data (PGHD). This failure to integrate with other healthcare data inside the EHR disrupts workflows, removes the data from critical patient context, and overall makes the CGM data less useful than it might otherwise be. Many healthcare organizations (HCOs) are either struggling with or delaying designing and implementing CGM data integrations. In this article, the current status of CGM integration is reviewed, goals for integration are proposed, and a consensus plan to engage key stakeholders to facilitate integration is presented.


2021 ◽  
Author(s):  
Shawn Zheng Kai Tan ◽  
Huseyin Kir ◽  
Brian Aevermann ◽  
Tom Gillespie ◽  
Michael Hawrylycz ◽  
...  

Large scale single cell omics profiling is revolutionising our understanding of cell types, especially in complex organs like the brain. This presents both an opportunity and a challenge for cell ontologies. Annotation of cell types in single cell 'omics data typically uses unstructured free text, making comparison and mapping of annotation between datasets challenging. Annotation with cell ontologies is key to overcoming this challenge, but this will require meeting the challenge of extending cell ontologies representing classically defined cell types by defining and classifying cell types directly from data. Here we present the Brain Data Standards Ontology (BDSO), a data driven ontology that is built as an extension to the Cell Ontology (CL). It supports two major use cases: cell type annotation, and navigation, search, and organisation of a web application integrating single cell omics datasets for the mammalian primary motor cortex. The ontology is built using a semi-automated pipeline that interlinks cell type taxonomies and necessary and sufficient marker genes, and imports relevant ontology modules derived from external ontologies. Overall, the BDS ontology provides an underlying structure that supports these use cases, while remaining sustainable and extensible through automation as our knowledge of brain cell type expands.


2021 ◽  
Vol 5 (S2) ◽  
Author(s):  
Michael Terner ◽  
Krista Louie ◽  
Candy Chow ◽  
Greg Webster

AbstractPROMs are essential to delivering patient-centred health care, and when applied routinely they can enhance communication between patients and providers, inform decisions for value-based health system improvements and improve overall patient care experiences and outcomes. The use of patient-reported outcome measures (PROMs) across Canada varies across provinces and territories, partly because of differences in health care delivery models across these jurisdictions. A national program that coordinates uses of PROMs is needed to ensure that this information is comparable across jurisdictions. This commentary provides a summary look at the development of national PROMs data standards and reporting for hip and knee replacement surgery, including the selection of survey tools, building consensus, developing and promoting standards, and reporting on the results nationally and internationally as well as outlining recent learnings from regional implementation of data standards. In 2017, the Canadian Institute for Health Information published national PROMs data collection standards for hip and knee arthroplasty that included guidelines for survey time points, the minimum data set and PROMs instruments. This broad-scale PROMs collection initiative had stakeholder engagement and support from multiple levels within the health system, including administrators, clinic managers, patients, and health system decision-makers. Learnings from regional implementation of the standards demonstrated the importance of assessing existing infrastructure and information technology requirements, mapping clinical workflows, planning for human and information technology resources, navigating local legislation and hospital policies and ensuring data linkage capabilities. This initiative showed the need for a common regional approach for PROMs collection to be efficient and effective. The learnings from implementation of the national Canadian PROMs program for hip and knee arthroplasty can be used as an example for other jurisdictions and clinical areas such as renal care and mental health. Common data standards allow for secondary use of this data that is valuable for reporting and informing policy and guidelines as well as meeting care delivery goals to further the shift in health care systems becoming more patient-centred to improve the quality-of-life of patients.


Author(s):  
Abigail Benson ◽  
Diana LaScala-Gruenewald ◽  
Robert McGuinn ◽  
Erin Satterthwaite

While a bevy of standards exist for managers of biological data to use, biological science departments or projects could benefit from an easy to digest primer about biological data standards and the value they confer. Moreover, a quick visual breakdown comparing standards could help data managers choose those that best serve their needs. The Earth Science Information Partners (ESIP) is a nonprofit that enables and supports high quality virtual and in-person collaborations between cross-domain data professionals on common data challenges and opportunities, and is supported by the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS). The ESIP Biological Data Standards Cluster has been developing a primer on existing biological data standards for managers of biological data who may be unaware of existing standards but need to improve management, analysis, and use of the biological observation data. The goal of this primer is to spread awareness about existing standards in a simple, aesthetically pleasing way. Our hope is that this primer, shared online and at conferences, will help increase the adoption of existing biological standards and help make data more Findable, Accessible, Interoperable, and Reusable (FAIR).


Author(s):  
Holly Little ◽  
Talia Karim ◽  
Erica Krimmel

As we atomize and expand the digital representation of specimen information through data standards, it is critical to evaluate the implementation of these developments, including how well they serve discipline-specific needs. In particular, fossil specimens often present challenges because they require information to be captured that is seemingly parallel to, but not entirely aligned with, that of their extant counterparts. Previous work to evaluate data sharing practices of paleontology collections has shown an imbalance in the use of Darwin Core (DwC) (Wieczorek et al. 2012) terms and many instances of underutilized terms (Little 2018). To expand upon that broad assessment and encourage better adoption of evolving standards and data practices by fossil collections, a more in-depth review of term usage is necessary. Here we review specific DwC terms that are underutilized or that present challenges for fossil occurrence records, and we examine the subsequent impact on data discovery of paleo specimens. We conclude by sharing options for improving standards implementation within a paleo context. We see key patterns and challenges in current implementation of DwC in paleo collections, as evidenced by evaluations of the typical mappings found in occurrence records for fossil specimens, data flags applied by aggregators, and discussions within the paleo collections community. These can be organized into three broad groupings. Group 1: Some DwC terms (or classes of terms) are clear to implement, but are underutilized due to issues that are also found within the neontological community. Example: Location. In the case of terms related to the Location class, paleontology has a need for a way to deal with sensitive locality information. The sensitivity here typically relates to laws restricting the sharing of locality information to protect fossil sites versus neontological requirements to protect threatened, rare, or endangered species. The end goal of needing to fuzz locality information without completely making the specimen record undiscoverable or unusable is the same. There is a need for better education at the paleo data provider-level related to standards for recording and sharing information in this category, which could be based on existing neontological community standards. Group 2: A second group of DwC terms often seem clear to implement, but the terminology used to describe and define them might be unfamiliar to paleontologists or read as unnecessary for fossil occurrences. This uncertainty about the applicability of a term to paleo data can often result in data not being mapped or fully shared. Example: recordedBy (= collector). In these cases, a simple translation of what the definition means in verbiage that is familiar to paleontologists, or the inclusion of paleo-oriented examples in the DwC documentation, can make implementation clear. Group 3: A third group of issues relates to DwC terms, classes, and/or extensions that are more complicated in the context of fossil vs. neontological data. In some cases use of these terms is complicated for neontological data as well, but perhaps for different reasons. The terms impacted by these challenges can sometimes have the same general use, but due to the nature of fossil preservation, or because a term has a different meaning within the discipline of paleontology, additional layers of uncertainty or ambiguity are present. Examples: Resource Relationship/Interactions, Individual count, Preparations, Taxon. Review of these terms and their related classes and/or the extensions they are part of has revealed that they might require qualification, further explanation, additional vocabulary terms, or even the need for special handling instructions when data are ingested and normalized at the aggregator level. This group of issues is more complicated to resolve, but the problems are not intractable and can progress toward solutions through further discussion within the community, active participation in the standards development and review process, and development of clear guidelines. Strategically assessing these terms and generating discipline-specific guidelines to be used by the paleo community can improve the mobilization and discovery of fossil occurrence data. Documenting these paleo data practices not only helps data providers, it also increases the utility of these data within the broader research community by clearly outlining how the terms were used. Overall, this discipline-focused approach to understanding the implementation of data standards like DwC at the term level, helps to increase knowledge sharing across the paleo community, improves data quality and standards adoption, and moves these datasets towards alignment with best practices like the FAIR (Findable, Accessible, Interoperable, Reusable) data principles.


2021 ◽  
pp. tobaccocontrol-2021-056704
Author(s):  
Sam N Cwalina ◽  
Ugonna Ihenacho ◽  
Joshua Barker ◽  
Sabrina L Smiley ◽  
Mary Ann Pentz ◽  
...  

The US Food and Drug Administration (FDA) applies the Population Health Standard in tobacco product review processes by weighing anticipated health benefits against risks associated with a given commercial tobacco product at the population level. However, systemic racism (ie, discriminatory policies and practices) contributes to an inequitable distribution of tobacco-related health benefits and risks between white and Black/African Americans at the population level. Therefore, Black-centered, antiracist data standards for tobacco product review processes are needed to achieve racial equity and social justice in US tobacco control policy. Regardless of whether FDA implements such data standards, non-industry tobacco scientists should prioritise producing and disseminating Black-centred data relevant to FDA’s regulatory authority. We describe how systemic racism contributes to disparities in tobacco-related outcomes and why these disparities are relevant for population-level risk assessments, then discuss four possible options for Black-centred data standards relevant to tobacco product review processes.


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