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Data governance capability is fundamental to coal mine intelligence construction. It could accelerate the intelligent construction of coal mines and promote the digital transformation of the coal industry so as to building a modern energy system in digital China. This paper therefore discusses the theory and methods of improving data governance capability for intelligent coal mines. Specifically, this study analyzes its strategic demands of intelligent coal mine construction on data governance and offers a working definition for data governance capability for intelligent coal mines. Then an evaluative system is proposed for the evaluation of data governance capability for intelligent coal mines. Further, by drawing on capability maturity theory, this study establishes a maturity model that specifies the improvement path of data governance capability for intelligent coal mines. Finally, based on the PDCA cycle theory, this paper puts forward strategies for improving data governance capability for intelligent coal mines, in order to 1)supplement existing theories of data governance capability enhancement, and 2)provide references for future practices of data governance.

Copyright of Records Management: Journal of the Records Management Society of Japan is the property of Records Management Society of Japan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Intelligent coal mine data governance is the key bottleneck to achieving the high-level development goal of coal mine intelligent construction. It is of great significance to ensure data operation compliance, ensure data quality, prevent and control data risks, and improve data value. However, there is a lack of perfect methodology to guide the theoretical research and technical practice of intelligent coal mine data governance. In order to solve this problem, an intelligent coal mine data governance element-mechanism-hierarchy-process reference model is constructed from four dimensions of data governance elements, governance mechanism, governance hierarchy and governance process. It provides a multi-dimensional fusion methodology perspective and theoretical analysis logic to achieve an understanding of key issues. It is concluded that complex system theory, data strategic management theory, collaborative innovation theory, digital continuity theory, public governance theory, information life cycle theory, and PDCA cycle theory are the important theoretical basis of intelligent coal mine data governance. Under the guidance of the reference model of intelligent coal mine data governance, and based on the relevant theoretical basis, an intelligent coal mine data governance system framework is constructed. It includes five major components: data governance environment, driving and supporting factors, top-level design, data governance domain, and data governance process and capability. Benchmarking the framework of intelligent coal mine data governance system, it is concluded that intelligent coal mine data governance still needs to further break through the five key issues. The issues are data value movement law disclosure, metadata and data dictionary construction, data quality and data security system management rule design, complex giant system data coupling model development and digital intelligence generation law modeling.

Copyright of Railway Standard Design is the property of Railway Standard Design Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper compares and discusses the data standards of materials that form the basis of MLA collaboration, i.e., the collaboration between Museums, Libraries, and Archives, and mentions the possibilities and issues of MLA collaboration from the viewpoint of the data standards of materials and Linked Open Data (LOD) [ABSTRACT FROM AUTHOR]

This paper examines the concept of open-source data interoperability in the United States' K-12 education domain, specifically addressing the implications of interoperability for data justice. The term 'data justice' is a relatively recent coinage; the framing and meaning of this term are still evolving, and it has not yet been applied in the educational domain. Building on the nascent research and theorizing in the fields of both data justice and interoperability in educational contexts, this paper provides an overview of the current state of this intersection. Additionally, the authors draw on their direct experiences implementing interoperability initiatives in several U.S. states in order to build a foundational understanding of the risks and opportunities for data justice in the realm of interoperability and data standards in education. The paper concludes with a call for more research to be completed on this complex sociotechnical topic. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Tunnel Construction / Suidao Jianshe (Zhong-Yingwen Ban) is the property of Tunnel Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Data is the core resource to promote the development of intelligent coal mine technology, innovation of application mode and improvement of market competitiveness. Data governance is the key bottleneck for the development of smart mine from primary stage to advanced stage. However, at present, there is no consensus on the concept connotation, development goal and key technologies of data governance for smart mine. In order to solve the above problems, this paper analyzes the important position of data governance in the construction of smart mines, and defines the concept and connotation of data governance for smart mine. Data governance for smart mine is guided by the governance concept of 'precipitation, reuse, sharing and collaboration'. All departments within the coal enterprise work together with industry and government regulatory departments to formulate data standards and management specifications. The data structure and data transmission link of coal enterprises are reshaped to break through the data barriers of smart mines and ensure data quality and data security. The smart mine technology linkage and business collaboration mechanism are built to realize the process of digital-driven decision-making and flexible production. This paper discusses the development goal of data governance for smart mine from three aspects, including overall goal, development strategy and phased tasks. It is pointed out that the key point of data governance for smart mine is to solve the problem of information isolated island in the process of smart mine construction. Therefore, the data sharing and business collaboration are realized so as to make smart mine become an organic whole to promote the value enhancement of coal enterprises. Smart mine data governance needs to properly handle the five aspects relationships, including local coordination and overall coordination, physical integration and logical integration, intelligent business system and data governance platform, group-level data governance platform and mine-level data governance platform, and local processing and cloud processing. It is proposed that smart mine data governance needs to break through six key technologies, including data standard, global data modeling, data aggregation, data development, data management and data center architecture.

The digital twin concept describes a comprehensive model used to monitor and simulate an existing asset in nearly realtime. In a maritime context, digital twins do not yet have a wide selection of standards to support interoperability among systems, undermining users' ability to create a cohesive digital twin that combines multiple sources of data. This study proposes an open framework for modelling and organizing ship, sensor, and operating context data in digital twins. The framework is web-driven, allowing digital twin content and simulations to be accessed by distributed users. Two case studies based on the framework are presented. The first one explains how to manage ship and sensor data using taxonomies suitable across different stages of the lifecycle. A dashboard for browsing a digital model of the research vessel Gunnerus according to taxonomies for early design and operation is developed as a proof of concept. The second case study illustrates how the proposed data standards can be used to develop simulations accounting for some aspects of the vessel's operating context. The digital Gunnerus model is used to develop a navigational simulator including surrounding terrain and nearby vessels. The challenges anticipated in scaling the framework toward industrial applications are discussed in terms of standards' capabilities, compatibility, and of data governance. Plans of integrating the case studies with sensor streams to obtain true digital twins are outlined. [ABSTRACT FROM AUTHOR]

[Display omitted] • Data standard for macromolecular structures from integrative and hybrid modeling (IHM). • Infrastructure for deposition, archiving, and public dissemination of integrative structures. • Representation and tools to enable interoperation of structural biology resources. • Community-driven effort that is extensible to handle novel methods. • Supports FAIR data delivery and accelerates scientific discovery. IHMCIF (github.com/ihmwg/IHMCIF) is a data information framework that supports archiving and disseminating macromolecular structures determined by integrative or hybrid modeling (IHM), and making them Findable, Accessible, Interoperable, and Reusable (FAIR). IHMCIF is an extension of the Protein Data Bank Exchange/macromolecular Crystallographic Information Framework (PDBx/mmCIF) that serves as the framework for the Protein Data Bank (PDB) to archive experimentally determined atomic structures of biological macromolecules and their complexes with one another and small molecule ligands (e.g., enzyme cofactors and drugs). IHMCIF serves as the foundational data standard for the PDB-Dev prototype system, developed for archiving and disseminating integrative structures. It utilizes a flexible data representation to describe integrative structures that span multiple spatiotemporal scales and structural states with definitions for restraints from a variety of experimental methods contributing to integrative structural biology. The IHMCIF extension was created with the benefit of considerable community input and recommendations gathered by the Worldwide Protein Data Bank (wwPDB) Task Force for Integrative or Hybrid Methods (wwpdb.org/task/hybrid). Herein, we describe the development of IHMCIF to support evolving methodologies and ongoing advancements in integrative structural biology. Ultimately, IHMCIF will facilitate the unification of PDB-Dev data and tools with the PDB archive so that integrative structures can be archived and disseminated through PDB. [ABSTRACT FROM AUTHOR]

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB’s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

Objective The global COVID pandemic has highlighted the need for the reporting of enhanced serology data from laboratory testing data. Qualitative results alone do not provide detailed data to understand levels of SARS-CoV-2 seroprevalence within a populace. To enable this, a minimum data set is required to support standardised data reporting. Approach The CO-CONNECT project is concerned with the response to COVID within the UK and how datasets can be made Findable, Accessible, Interoperable and Reusable (FAIR). One aspect of this is a focus upon improving granular levels of COVID serology testing data being reported by national laboratories to the National Pathology Exchange (NPEx). A study was conducted to ascertain the essential data elements that could formulate a COVID Serology Data Standard (CSDS). Three NHS laboratories acting as pilot studies and NPEx have been actively involved with the development of the CSDS, together with clinicians and academics from the CO-CONNECT project. Results Feedback from clinicians, academics and NPEx has been collected, together with NHS laboratory feasibility analysis to derive a minimum set of data elements that form a proposed data standard to standardise the reporting of laboratory COVID serology data for the UK. The proposed CSDS comprises twelve data elements in total, grouped into four main areas, (1) subject identifier and test date and time, (2) analyser types, test kits and samples, (3) qualitative results and (4) quantitative results. To further support the standardisation effort, a proposed Health Level Seven (HL7) message structure has been created to enable the reporting of the CSDS data elements to NPEx. Conclusion The CSDS has been created to help augment levels of reported granular data for laboratory COVID serology testing. If adopted, this could enable healthcare professionals to better understand the calibration of assays across multiple analyser types and thus antibody response levels.

Keywords: Analytical chemistry; cheminformatics: data and standards; data standard; file format; mass spectrometry; NMR EN Analytical chemistry cheminformatics: data and standards data standard file format mass spectrometry NMR 725 736 12 08/09/22 20220601 NES 220601 Introduction The amount of research data is growing in all disciplines, and chemistry is no exception. The NMR record in NMReDATA format includes the instrument (raw) data, a SDFile and, since version 2, also spectral data in JCAMP format in a folder, which can be compressed in the zip format for data exchange. Data standards for NMR spectroscopy NMR is an indispensable analytical technique providing rich information on bonding and structure as well as molecule interaction and abundance of molecules in samples. Data formats for analytical data When developing infrastructures for chemistry, one of the major tasks is to adopt or define data models and formats for exchange, storage and archival of analytical data. [Extracted from the article]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NEF and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB restraint violation report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints. [Display omitted] • The wwPDB validation report has been expanded to include restraint analysis • NMR-STAR and NEF serve as the standardized format for NMR data at wwPDB • Standardized restraint format facilitates model versus data assessment • More comprehensive and better assessment of biomolecular NMR structures Baskaran et al. outlined the rationale for model-versus-data assessment of NMR structures by wwPDB, along with a summary of validation tools for NMR distance and dihedral-angle restraints implemented in the wwPDB validation pipeline. These tools enhance the assessment of biomolecular NMR structure quality, benefiting users of the wwPDB archive. [ABSTRACT FROM AUTHOR]

• Allotrope Data Model ensures data integrity through validation. • Allotrope Framework's foundation is built upon the versatile HDF5. • Multiple tools enable easy access to Allotrope Data Format datasets. • Advances in AF technologies made it easy for users to adopt the standard. Recent Allotrope Foundation (AF) Connect Workshops (2021–2023) showcased some of the latest advancements in data standardization for analytical data in the pharmaceutical industry. These workshops demonstrated the adaption of two key technologies, the Allotrope Data Format (ADF) and the Allotrope Simple Model (ASM), which streamline instrument data representation and terminology to enhance interoperability across systems. Notably, ASM has facilitated broader adoption of the standard. The increasing significance of data-driven decision-making in the life sciences is underscored by the evolving landscape of open-source solutions and commercial implementations, as demonstrated by industry leaders adopting these standards. Here, we highlight selected examples that illustrate the collective efforts of the community in advancing data standards and data management in the life sciences. [ABSTRACT FROM AUTHOR]

To be computationally reproducible and efficient, integration of disparate data depends on shared entities whose matching meaning (semantics) can be computationally assessed. For biodiversity data one of the most prevalent shared entities for linking data records is the associated taxon concept. Unlike Linnaean taxon names, the traditional way in which taxon concepts are provided, phylogenetic definitions are native to phylogenetic trees and offer well-defined semantics that can be transformed into formal, computationally evaluable logic expressions. These attributes make them highly suitable for phylogeny-driven comparative biology by allowing computationally verifiable and reproducible integration of taxon-linked data against Tree of Life-scale phylogenies. To achieve this, the first step is transforming phylogenetic definitions from the natural language text in which they are published to a structured interoperable data format that maintains strong ties to semantics and lends itself well to sharing, reuse, and long-term archival. To this end, we developed the Phyloreference Exchange Format (Phyx), a JSON-LD-based text format encompassing rich metadata for all elements of a phylogenetic definition, and we created a supporting software library, phyx.js, to streamline computational management of such files. Together they form a foundation layer for digitizing and computing with phylogenetic definitions of clades. [ABSTRACT FROM AUTHOR]

To be computationally reproducible and efficient, integration of disparate data depends on shared entities whose matching meaning (semantics) can be computationally assessed. For biodiversity data one of the most prevalent shared entities for linking data records is the associated taxon concept. Unlike Linnaean taxon names, the traditional way in which taxon concepts are provided, phylogenetic definitions are native to phylogenetic trees and offer well-defined semantics that can be transformed into formal, computationally evaluable logic expressions. These attributes make them highly suitable for phylogeny-driven comparative biology by allowing computationally verifiable and reproducible integration of taxon-linked data against Tree of Life-scale phylogenies. To achieve this, the first step is transforming phylogenetic definitions from the natural language text in which they are published to a structured interoperable data format that maintains strong ties to semantics and lends itself well to sharing, reuse, and long-term archival. To this end, we developed the Phyloreference Exchange Format (Phyx), a JSON-LD-based text format encompassing rich metadata for all elements of a phylogenetic definition, and we created a supporting software library, phyx.js, to streamline computational management of such files. Together they form a foundation layer for digitizing and computing with phylogenetic definitions of clades.

The nuclear magnetic resonance extracted data (NMReDATA) format has been proposed as a way to store, exchange, and disseminate nuclear magnetic resonance (NMR) data and physical and chemical metadata of chemical compounds. In this paper, we report on analytical workflows that take advantage of the uniform and standardized NMReDATA format. We also give access to a repository of sample data, which can serve for validating software packages that encode or decode files in NMReDATA format. [ABSTRACT FROM AUTHOR]

The global movement of people and goods has increased the risk of biosecurity threats and their potential to induce large economic, social, and environmental harm. Integration of biosafety monitoring networks has become a top priority for addressing biosafety issues. In order to resolve the data standards and integration problems in the field of biosafety in China, the Biosafety Surveillance Conceptual Data Model (BSCDM), which is an object-oriented, hierarchically designed, flexible and scalable biosafety surveillance concept data model, is proposed in this article. This model is based on the integration of business process management and data resources of disease surveillance, animal disease surveillance and potential invasive biological monitoring. In reference to the Public Health Conceptual Data Model (PHCDM) and Federal Enterprise Architecture (FEA), BSCDM conducts a thorough analysis of biosafety monitoring activities, records basic information requirements of biosafety monitoring and provides data set standards for biosafety-related activities. It is developed with the Unified Modeling Language (UML) and could be applied as an open standard for accelerating data analysis and promoting collaboration. This study attempts to integrate biosafety monitoring data and the presented model has been tested in the detection of dengue fever in China and will be applied to other biosafety fields.

Natural history collections are invaluable tools for various questions regarding biodiversity, environmental, and cultural studies. All object metadata thus need to be findable, reachable and interoperable for the scientific community and beyond. This requires a good structuration of data, appropriate exchange formats, and web sites or portals making all necessary information accessible. Collection managers, curators, and scientist from various institutions and nationalities were surveyed in order to understand the importance of open geoscientific collections for the respective holding institution and their daily work. In addition, particular requirements for the publication of geoscientific collection object metadata were gathered in a two-day workshop with international experts working with paleontological, mineralogical, petrological and meteorite collections. The survey and workshop revealed that common data standards are of crucial importance though insufficiently used by most institutions. The extent and type of information necessary for the publication and discussed during the workshop will be considered for domain specific application schema facilitating the publication and exchange of geoscientific object metadata. There is a high demand for comprehensive data portals covering all geoscientific disciplines. Gathered portal requirements will be taken into account when improving the already running GeoCASe aggregator platform.

Although plot or monitoring data are quite often associated with objects collected in the plot and stored in specific collections, controlled vocabularies currently available do not cover both disciplines. This situation limits the possibility to publish common data sets and consequently brings a loss of significant information by combining plot-based research with collection object associated data. To facilitate the exchange and publication of these important data sets, experts in natural history collection data, ecological research, and environmental science met for a one-day workshop in Berlin. The participants discussed data standards and ontologies relevant for each discipline and collected requirements for a first application schema covering terms important for both, collection object related data and plot-based research.

Abstract Background To truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice. Methods We developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD. Results Along with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data. Conclusions We expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice.

This paper explores the data challenges of a major collection method in the field of ecology: using infrared-activated cameras to detect wildlife. One such solution, eMammal, is now available to address these struggles. We delineate the key reason behind its success: a data curator who manages an established data standard and communicates with eMammal’s users and stakeholders. We outline the tasks of this data curator, mention how they can work with data librarians, and demonstrate that the data curator position is already applicable in several biological science fields with a few examples. We end by emphasizing the growth of such a position and how it contributes to the research field. The substance of this article is based upon a lightning talk presentation at RDAP Summit 2018.

In 2010, the Conference of the Parties of the Convention on Biological Diversity agreed on the Strategic Plan for Biodiversity 2011–2020 in Aichi Prefecture, Japan. As this plan approaches its end, we discussed whether marine biodiversity and prediction studies were nearing the Aichi Targets during the 4th World Conference on Marine Biodiversity held in Montreal, Canada in June 2018. This article summarises the outcome of a five-day group discussion on how global marine biodiversity studies should be focused further to better understand the patterns of biodiversity. We discussed and reviewed seven fundamental biodiversity priorities related to nine Aichi Targets focusing on global biodiversity discovery and predictions to improve and enhance biodiversity data standards (quantity and quality), tools and techniques, spatial and temporal scale framing, and stewardship and dissemination. We discuss how identifying biodiversity knowledge gaps and promoting efforts have and will reduce such gaps, including via the use of new databases, tools and technology, and how these resources could be improved in the future. The group recognised significant progress toward Target 19 in relation to scientific knowledge, but negligible progress with regard to Targets 6 to 13 which aimed to safeguard and reduce human impacts on biodiversity. [ABSTRACT FROM AUTHOR]

Background: Atrial fibrillation (AF) affects an estimated 33 million people worldwide, leading to increased mortality and an increased risk of heart failure and stroke. Many AF patient registries exist, but the ability to link and compare data across registries is hindered by differences in the outcome measures collected by each registry and a lack of harmonization.Objectives: The purpose of this project was to develop a minimum set of standardized outcome measures that could be collected in AF patient registries and clinical practice.Methods: AF patient registries were identified through multiple sources and invited to join the workgroup and submit outcome measures. Additional measures were identified through literature searches and reviews of consensus statements. Outcome measures were categorized using the Agency for Healthcare Research and Quality's supported Outcome Measures Framework (OMF). A minimum set of broadly relevant measures was identified. Measure definitions were harmonized through in-person and virtual meetings.Results: One hundred twelve outcome measures, including those from thirteen registries, were curated according to the OMF and then harmonized into a minimum set of measures in the OMF categories of survival (3 measures), clinical response (3 measures), events of interest (9 measures), patient-reported outcomes (2 measures), and resource utilization (3 measures). The harmonized definitions build on existing consensus statements.Conclusions: The harmonized measures represent a minimum set of outcomes that are relevant in AF research and clinical practice. Routine and consistent collection of these measures in registries and in other systems would support creation of a research infrastructure to efficiently address new questions and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Although plot or monitoring data are quite often associated with objects collected in the plot and stored in specific collections, controlled vocabularies currently available do not cover both disciplines. This situation limits the possibility to publish common data sets and consequently brings a loss of significant information by combining plot-based research with collection object associated data. To facilitate the exchange and publication of these important data sets, experts in natural history collection data, ecological research, and environmental science met for a one-day workshop in Berlin. The participants discussed data standards and ontologies relevant for each discipline and collected requirements for a first application schema covering terms important for both, collection object related data and plot-based research. [ABSTRACT FROM AUTHOR]

Natural history collections are invaluable tools for various questions regarding biodiversity, environmental, and cultural studies. All object metadata thus need to be findable, reachable and interoperable for the scientific community and beyond. This requires a good structuration of data, appropriate exchange formats, and web sites or portals making all necessary information accessible. Collection managers, curators, and scientist from various institutions and nationalities were surveyed in order to understand the importance of open geoscientific collections for the respective holding institution and their daily work. In addition, particular requirements for the publication of geoscientific collection object metadata were gathered in a two-day workshop with international experts working with paleontological, mineralogical, petrological and meteorite collections. The survey and workshop revealed that common data standards are of crucial importance though insufficiently used by most institutions. The extent and type of information necessary for the publication and discussed during the workshop will be considered for domain specific application schema facilitating the publication and exchange of geoscientific object metadata. There is a high demand for comprehensive data portals covering all geoscientific disciplines. Gathered portal requirements will be taken into account when improving the already running GeoCASe aggregator platform. [ABSTRACT FROM AUTHOR]

FCS 3.2 is a revision of the flow cytometry data standard based on a decade of suggested improvements from the community as well as industry needs to capture instrument conditions and measurement features more precisely. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type. The standard retains the overall FCS file structure and most features of previous versions, but also contains a few changes that were required to support new types of data and use cases efficiently. These changes are incompatible with existing FCS file readers. Notably, FCS 3.2 supports mixed data types to, for example, allow FCS measurements that are intrinsically integers (e.g., indices or class assignments) or measurements that are commonly captured as integers (e.g., time ticks) to be more represented as integer values, while capturing other measurements as floating‐point values in the same FCS data set. In addition, keywords explicitly specifying dyes, detectors, and analytes were added to avoid having to extract those heuristically and unreliably from measurement names. Types of measurements were formalized, several keywords added, others removed, or deprecated, and various aspects of the specification were clarified. A reference implementation of the cyclic redundancy check (CRC) calculation is provided in two programming languages since a correct CRC implementation was problematic for many vendors. © 2020 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Abstract: The Flow Cytometry Standard (FCS) format is a widely accepted norm for storing Flow Cytometry (FCM) data. Its goal as a standard is to allow FCM data sharing and re‐analysis. Over more than three decades of its existence FCS has evolved into a well‐defined, flexible file format reflecting technical changes in the FCM field. Its flexibility as well as rising numbers of instrument vendors leads to suboptimal implementations of FCS in some cases. Such situations compromise the primary goal of the standard and hinder the ability to reproduce FCM analyses. It is further underlined by rapid rise of advanced FCM analyses, often carried out outside traditional software tools and heavily relying on standard data storage and presentation. We have developed flowIO, an R package which tests FCS file conformance with the standard as defined by International Society for Advancement of Cytometry (ISAC) normative. Along with the package we provide a web based application (also at http://bioinformin.cesnet.cz/flowIO/) allowing user friendly access to the conformance testing as well as FCS file editing and export for further analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • Community-driven data representation for computed structure models (CSMs) of biological macromolecules. • Provides common data representation and tools that enable interoperation of structural biology data resources. • Provides data and software infrastructure for deposition, archiving, and public dissemination of CSMs. • Provides data infrastructure that supports FAIR (Findable, Accessible, Interoperable, Reusable) data delivery and accelerates scientific discovery. ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery of Findable , Accessible , Interoperable , and Reusable (FAIR) data to users worldwide. ModelCIF describes the specific set of attributes and metadata associated with macromolecular structures modeled by solely computational methods and provides an extensible data representation for deposition, archiving, and public dissemination of predicted three-dimensional (3D) models of macromolecules. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined 3D structures of macromolecules and associated metadata. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described. [ABSTRACT FROM AUTHOR]

Characterized by their low prevalence, rare diseases are often chronically debilitating or life threatening. Despite their low prevalence, the aggregate number of individuals suffering from a rare disease is estimated to be nearly 400 million worldwide. Over the past decades, efforts from researchers, clinicians, and pharmaceutical industries have been focused on both the diagnosis and therapy of rare diseases. However, because of the lack of data and medical records for individual rare diseases and the high cost of orphan drug development, only limited progress has been achieved. In recent years, the rapid development of next-generation sequencing (NGS)-based technologies, as well as the popularity of precision medicine has facilitated a better understanding of rare diseases and their molecular etiology. As a result, molecular subclassification can be identified within each disease more clearly, significantly improving diagnostic accuracy. However, providing appropriate care for patients with rare diseases is still an enormous challenge. In this review, we provide a brief introduction to the challenges of rare disease research and make suggestions on where and how our efforts should be focused. [ABSTRACT FROM AUTHOR]

Pollination is considered one of the most important processes for biodiversity conservation (Kremen 2005). Recently, the global community, by means of the Intergovernmental Platform of Biodiversity and Ecosystems Services (IPBES 2016), and also, the Convention on Biological Diversity (CBD 2002) recognized the importance of plant-pollinator interactions for ecosystems functioning and sustainable agriculture. The conservation of pollination depends of information about plant-pollinator interactions covering a great diversity of functional and taxonomic groups. Studies show that successful pollination can improve the amount and the quality of plant fecundation and fruit production (Kevan and Imperatriz-Fonseca 2002). However, the success of these actions depends on the knowledge on pollinators, their conservation and interactions with plants and the environment. In order to conserve and manage it, more information needs to be captured about plant-pollinator interactions. Primary data about pollinators is becoming increasingly available online and can be accessed at a number of websites and portals. Many initiatives have also been created to facilitate and to stimulate the dissemination of pollination data, and examples are the Inter- American Biodiversity Information Network - Pollinators Thematic Network - IABIN-PTN (w ww.biocomp.org.br/iabinptn) and the WebBee (www.webbee.org.br) (Saraiva et al. 2003). One important aspect of this trend is the strong reliance on standardized data schemas and protocols (e.g. Darwin Core - DwC and TDWG Access Protocol for Information Retrieval - TAPIR, respectively) that allow us to share and aggregate biological data, among which pollinator data are included. Although plant-pollinator interaction data are critically important to our understanding of the role, importance and effectiveness of (potential) pollinators, they cannot be adequately represented by the current standards for occurrence data (such as DwC). The ways that interaction data are recorded and stored worldwide, as well as their intended use are very diverse. They lack of a common protocol and data schema, that will allow us to aggregate them in web portals and eventually use them to build decision support systems for conservation and sustainable use in agriculture, needs to be addressed. The IABIN-PTN adopted a simple solution to characterize and digitalize plant-pollinator interaction data based on DwC (Cartolano Júnior et al. 2007), allowing the digitalization of many Latin-american collections. Following that work, the Food and Agriculture Organization of the United Nations (FAO) produced a detailed survey of potential descriptors of plant-pollinators interactions. Although the ultimate goal of that work was to propose a data standard, that did not evolve (Cavalheiro et al. 2016). The FAO Global pollination project, adopted in Brazil the same simplified model used by IABIN to digitize plant-pollinator interaction data (Saraiva et al. 2010). Recently many Brazilian scientists gathered around the Brazilian Plant-Pollinator Interactions Network (REBIPP - www.rebipp.org.br) with the aim of developing scientific and teaching activities in the field. The main goals of the network are: generate a diagnosis of plant-pollinator interactions in Brazil; integrate knowledge in pollination of natural, agricultural, urban and restored areas; identify knowledge gaps; support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed those previous works done under the auspices of the IABIN and FAO projects, and a data standard is being discussed. The ultimate goal is to adopt a standard and develop a database of plant-pollinator data in Brazil to be used by the national community. This proposal of a data standard (depicted in Fig. 1) can serve as a starting point for the definition of a global data standard for plantpollinator interactions under the TDWG umbrella. [ABSTRACT FROM AUTHOR]

The complexities of the intricate geospatial resources and formats make preservation and distribution of GIS data difficult even among experts. The proliferation of, for instance, KML, Internet map services, etc, reflects the need for sharing geodata but a comprehensive solution when having to deal with data and metadata of a certain complexity is not currently provided. Original geospatial data is usually divided into several parts to record its different aspects (spatial and thematic features, etc), plus additional files containing, metadata, symbolization specifications and tables, etc; these parts are encoded in different formats, both standard and proprietary. To simplify data access, software providers encourage the use of an additional element that we call generically “map project”, and this contains links to other parts (local or remote). Consequently, in order to distribute the data and metadata refereed by the map in a complete way, or to apply the Open Archival Information System (OAIS) standard to preserve it for the future, we need to face the multipart problem. This paper proposes a package allowing the distribution of real (comprehensive although diverse and complex) GIS data over the Internet and for data preservation. This proposal, complemented with the right tools, hides but keeps the multipart structure, so providing a simpler but professional user experience. Several packaging strategies are reviewed in the paper, and a solution based on ISO 29500-2 standard is chosen. The solution also considers the adoption of the recent Open Geospatial Consortium Web Services common standard (OGC OWS) context document as map part, and as a way for also combining data files with geospatial services. Finally, and by using adequate strategies, different GIS implementations can use several parts of the package and ignore the rest: a philosophy that has proven useful (e.g. in TIFF). [ABSTRACT FROM AUTHOR]

Background: To truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice. Methods: We developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD. Results: Along with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data. Conclusions: We expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice. [ABSTRACT FROM AUTHOR]

The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)2) research initiative. The project data archive is quality managed, easy to use, and is now open for other atmospheric research data. The archive's creation was already taken into account during the HD(CP)2 project planning phase and the necessary resources were granted. The funding enabled the HD(CP)2 project to build a sound archive structure, which guarantees that the collected data are accessible for all researchers in the project and beyond. [ABSTRACT FROM AUTHOR]

As a country with 11 properties included on the World Heritage List and approximately 12,000 important cultural properties, Korea has been continuously carrying out the inventory and documentation of cultural properties to conserve and manage them since the 1960s. The inventory of cultural properties had been carried out by making and managing a register which recorded basic information mainly on state-designated cultural properties such as their size, quantity, and location. The documentation of cultural properties was also carried out by making measured drawings. However, the inventory and documentation done under the previous analog method had a limit to the information it could provide for the effective conservation and management of cultural properties. Moreover, in recent times important cultural properties have frequently been damaged by man-made and natural disasters such as arson, forest fires, and floods, so an alternative was required. Accordingly, Korea actively introduced digital techniques led by the government for the inventory and documentation of important cultural properties. In this process, the government established the concept of a digital set, built a more efficie nt integrated data management system, and created standardized guidelines to maximize the effectiveness of data acquisition, management, and utilization that greatly increased the level of digital inventory, documentation, and archiving. [ABSTRACT FROM AUTHOR]

The lack of software interoperability with respect to gating has traditionally been a bottleneck preventing the use of multiple analytical tools and reproducibility of flow cytometry data analysis by independent parties. To address this issue, ISAC developed Gating-ML, a computer file format to encode and interchange gates. Gating-ML 1.5 was adopted and published as an ISAC Candidate Recommendation in 2008. Feedback during the probationary period from implementors, including major commercial software companies, instrument vendors, and the wider community, has led to a streamlined Gating-ML 2.0. Gating-ML has been significantly simplified and therefore easier to support by software tools. To aid developers, free, open source reference implementations, compliance tests, and detailed examples are provided to stimulate further commercial adoption. ISAC has approved Gating-ML as a standard ready for deployment in the public domain and encourages its support within the community as it is at a mature stage of development having undergone extensive review and testing, under both theoretical and practical conditions. © 2015 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Background and objective The importance of data standards when integrating clinical research data has been recognized. The common data element (CDE) is a consensus-based data element for data harmonization and sharing between clinical researchers, it can support data standards adoption and mapping. However, the lack of a suitable methodology has become a barrier to data standard adoption. Our aim was to demonstrate an approach that allowed clinical researchers to design electronic case report forms (eCRFs) that complied with the data standard. Methods We used a multi-technique approach, including information retrieval, natural language processing and an ontology-based knowledgebase to facilitate data standard adoption using the eCRF design. The approach took research questions as query texts with the aim of retrieving and associating relevant CDEs with the research questions. Results The approach was implemented using a CDE-based eCRF builder, which was evaluated using CDE- related questions from CRFs used in the Parkinson Disease Biomarker Program, as well as CDE-unrelated questions from a technique support website. Our approach had a precision of 0.84, a recall of 0.80, a F -measure of 0.82 and an error of 0.31. Using the 303 testing CDE-related questions, our approach responded and provided suggested CDEs for 88.8% (269/303) of the study questions with a 90.3% accuracy (243/269). The reason for any missed and failed responses was also analyzed. Conclusion This study demonstrates an approach that helps to cross the barrier that inhibits data standard adoption in eCRF building and our evaluation reveals the approach has satisfactory performance. Our CDE-based form builder provides an alternative perspective regarding data standard compliant eCRF design. [ABSTRACT FROM AUTHOR]

[Display omitted] • Community Driven Data Representation for structural biology data. • Provides common data representation and tools that accelerates scientific discovery. • Provides data and software infrastructure for the Protein Data Bank (PDB) Core Archive. • Provides essential data infrastructure supporting FAIR data delivery. PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide. [ABSTRACT FROM AUTHOR]

The archiving of scientific data is a sophisticated mission in nearly all research projects. In this paper, we introduce a new online archive of atmospheric measurement data from the "High definition clouds and precipitation for advancing climate prediction" (HD(CP)2) research initiative. The project data archive is quality managed, easy to use, and is now open for other atmospheric research data. The archive’s creation was already taken into account during the HD(CP)2 project planning phase and the necessary resources were granted. The funding enabled the HD(CP)2 project to build a sound archive structure, which guarantees that the collected data are accessible for all researchers in the project and beyond.

The paper compares hydrographic and terrain categories in the geospatial data standards of the United States, Taiwan, and Russian Federation where the dominant languages used are from different language families. It aims to identify structural and semantic differences between similar categories across three geospatial data standards. By formalizing the data standard structures and identifying the properties that differentiate sibling categories in each geospatial data standard using well-known formal relations and quality universals, we develop a common basis on which hydrographic and terrain categories in the three data standards can be compared. The result suggests that all the three data standards structure categories with a mixture of relations even though most of them are well-known relations in top-level ontologies. Similar categories can be found across all the three standards. Cases of categories from different standards carrying identical meaning are rare. Partial overlaps in the meaning of the similar categories can be a direct result of different quality universals at work in defining and distinguishing these categories, or in the case of these categories being ordered by size, the threshold values for distinguishing the categories are ambiguous and language-dependent. Understanding these differences avoids incorrect mappings of categories in multilingual applications. More importantly, it provides a starting point for more effective mapping between hydrographic and terrain categories between English, Mandarin, and Russian. [ABSTRACT FROM AUTHOR]

Vertebrate fossil tracks have been studied through 3D modelling techniques during the last two decades to improve tracking procedures. Different laser scanners and software have been used during field investigation and this differentiation caused incompatibility between many analysis programs. Post processing procedures are not standardized among scientists and file precision give different results in additionally constrain comparison. The starting point to find a solution to the problem is to point out the main technologies used to collect data in the field. The resulting protocol does not oblige to uniform hardware but it does suggest combining different laser scanners with a minimum post processing to optimize the result. Important inkling would be to use 2D relief as a reference to organize 3D tracking procedures. Saving formats during post processing are improved by setting fixed landmarks integrated in the 3D model in a multitask file. The D.I.C.O.M. medical standard (*.cdm format) and the 3D printing international standard (*.stl format) when combined, may be a good solution for uniform the format. This approach might be the first step for the standardization of source and derived files and the creation of a worldwide 3D ichnological catalogue. This will allow creating a scientific improvement in terms of reproducibility and comparison of the experience.

We propose the use of existing data standards and web technologies to modeling and development of digital twin ships. Our research provides an open framework that can be linked to services such as visualizations, simulations and remote control. The case study applies the standards-based framework to an experiment that involved a scale model ship equipped with a dynamic positioning system under artificial waves. The digital twin prototype illustrated the capability of mirroring and controlling the model's position in real-time, and predicting motion responses across wave conditions via a web application. Thus, it closes the loop between test and design in the life cycle by allowing validation of results in comparison to empirical data during operation. The results from these experiments are used to discuss an expanded version of the digital twin for validation and optimization of motion response, as well as its implications to the system's (ship) taxonomy and data management. The conclusion summarizes lessons when using the adopted standards, as well as challenges when scaling the approach to real life operations. Future research is proposed toward extending the standardization to more complex cases. • Open and standards-based development of a digital twin for a dynamic positioning experiment in a wave basin. • The digital twin monitors wave motion response and controls dynamic positioning in real-time. • The data organization follows a function-oriented taxonomy based on the Vessel Information System, created by DNV. • Among the standards used are JSON for metadata, glTF for visualization and ISO 19848 for data logs. • Simulation interface is developed as a Web-app for wider compatibility across devices and remote access over the internet. [ABSTRACT FROM AUTHOR]

CitSci.org is a global citizen science software platform and support organization housed at Colorado State University. The mission of CitSci is to help people do high quality citizen science by amplifying impacts and outcomes. This platform hosts over one thousand projects and a diverse volunteer base that has amassed over one million observations of the natural world, focused on biodiversity and ecosystem sustainability. It is a custom platform built using open source components including: PostgreSQL, Symfony, Vue.js, with React Native for the mobile apps. CitSci sets itself apart from other Citizen Science platforms through the flexibility in the types of projects it supports rather than having a singular focus. This flexibility allows projects to define their own datasheets and methodologies. The diversity of programs we host motivated us to take a founding role in the design of the PPSR Core, a set of global, transdisciplinary data and metadata standards for use in Public Participation in Scientific Research (Citizen Science) projects. Through an international partnership between the Citizen Science Association, European Citizen Science Association, and Australian Citizen Science Association, the PPSR team and associated standards enable interoperability of citizen science projects, datasets, and observations. Here we share our experience over the past 10+ years of supporting biodiversity research both as developers of the CitSci.org platform and as stewards of, and contributors to, the PPSR Core standard. Specifically, we share details about: 1. the origin, development, and informatics infrastructure for CitSci 2. our support for biodiversity projects such as population and community surveys 3. our experiences in platform interoperability through PPSR Core working with the Zo oniverse, SciStarter, and CyberTracker 4. data quality 5. data sharing goals and use cases. We conclude by sharing overall successes, limitations, and recommendations as they pertain to trust and rigor in citizen science data sharing and interoperability. As the scientific community moves forward, we show that Citizen Science is a key tool to enabling a systems-based approach to ecosystem problems. [ABSTRACT FROM AUTHOR]

The Flow Cytometry Standard (FCS) format was developed back in 1984. Since then, FCS became the standard file format supported by all flow cytometry software and hardware vendors. Over the years, updates were incorporated to adapt to technological advancements in both flow cytometry and computing technologies. However, flexibility in how data may be stored in FCS has led to implementation difficulties for instrument vendors and third party software developers. In this technical note, we are providing implementation guidance and examples related to FCS 3.1, the latest version of the standard. By publishing this text, we intend to prevent potential compatibility issues that could be faced when implementing the FCS spillover and preferred display keywords that have arisen during discussions among some implementers. © 2012 International Society for Advancement of Cytometry. [ABSTRACT FROM AUTHOR]