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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.

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.

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.

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.

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.

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.)

Field observations of the soil-to-atmosphere CO2 flux—soil respiration, RS—are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g., FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. With input from the research community, we have also developed research data and metadata templates to support data collection adhering to the reporting format. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. This proposed RS reporting format is openly available online and is intended to be a dynamic document, subject to further community feedback and/or change.

Field observations of the soil-to-atmosphere CO2 flux—soil respiration, RS—are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the earth and ecological sciences as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g., FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. With input from the research community, we have also developed research data and metadata templates to support data collection adhering to the reporting format. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. This proposed RS reporting format is openly available online and is intended to be a dynamic document, subject to further community feedback and/or change.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

Leaf-level gas exchange data support the mechanistic understanding of plant fluxes of carbon and water. These fluxes inform our understanding of ecosystem function, are an important constraint on parameterization of terrestrial biosphere models, are necessary to understand the response of plants to global environmental change, and are integral to efforts to improve crop production. Collection of these data using gas analyzers can be both technically challenging and time consuming, and individual studies generally focus on a small range of species, restricted time periods, or limited geographic regions. The high value of these data is exemplified by the many publications that reuse and synthesize gas exchange data, however the lack of metadata and data reporting conventions make full and efficient use of these data difficult. Here we propose a reporting format for leaf-level gas exchange data and metadata to provide guidance to data contributors on how to store data in repositories to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format specifies data table variable naming and unit conventions, as well as metadata characterizing experimental conditions and protocols. For common data types that were the focus of this initial version of the reporting format, i.e., survey measurements, dark respiration, carbon dioxide and light response curves, and parameters derived from those measurements, we took a further step of defining required additional data and metadata that would maximize the potential reuse of those data types. To aid data contributors and the development of data ingest tools by data repositories we provided a translation table comparing the outputs of common gas exchange instruments. Extensive consultation with data collectors, data users, instrument manufacturers, and data scientists was undertaken in order to ensure that the reporting format met community needs. The reporting format presented here is intended to form a foundation for future development that will incorporate additional data types and variables as gas exchange systems and measurement approaches advance in the future. The reporting format is published in the U.S. Department of Energy's ESS-DIVE data repository, with documentation and future development efforts being maintained in a version control system.

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]

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.

The flow cytometry data file standard provides the specifications needed to completely describe flow cytometry data sets within the confines of the file containing the experimental data. In 1984, the first Flow Cytometry Standard format for data files was adopted as FCS 1.0. This standard was modified in 1990 as FCS 2.0 and again in 1997 as FCS 3.0. We report here on the next generation flow cytometry standard data file format. FCS 3.1 is a minor revision based on suggested improvements from the community. 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 FCS 3.1 standard retains the basic FCS file structure and most features of previous versions of the standard. Changes included in FCS 3.1 address potential ambiguities in the previous versions and provide a more robust standard. The major changes include simplified support for international characters and improved support for storing compensation. The major additions are support for preferred display scale, a standardized way of capturing the sample volume, information about originality of the data file, and support for plate and well identification in high throughput, plate based experiments. Please see the normative version of the FCS 3.1 specification in Supporting Information for this manuscript (or at http://www.isac-net.org/ in the Current standards section) for a complete list of changes.

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]

Integration of insulin dosing data into the electronic health record (EHR), combined with other patient-generated health care data, would facilitate the use of wirelessly connected insulin delivery systems, including smart insulin pens, insulin pumps, and advanced hybrid closed-loop systems. In 2022, Diabetes Technology Society developed the Integration of Continuous Glucose Monitoring Data into the EHR (iCoDE) Project, which is the first consensus standard for integrating data from a wearable device into the EHR. The iCoDE Standard is a comprehensive guide for any health care delivery organization or hospital for automatically integrating continuous glucose monitoring data into the EHR. Diabetes Technology Society is following iCoDE with the Integration of Connected Diabetes Device Data into the EHR (iCoDE-2) Project, to similarly provide guidance for integrating insulin delivery data into the EHR alongside continuous glucose monitoring data.

Background: The anonymization of Common Data Model (CDM)-converted EHR data is essential to ensure the data privacy in the use of harmonized health care data. However, applying data anonymization techniques can significantly affect many properties of the resulting data sets and thus biases research results. Few studies have reviewed these applications with a reflection of approaches to manage data utility and quality concerns in the context of CDM-formatted health care data., Objective: Our intended scoping review aims to identify and describe (1) how formal anonymization methods are carried out with CDM-converted health care data, (2) how data quality and utility concerns are considered, and (3) how the various CDMs differ in terms of their suitability for recording anonymized data., Methods: The planned scoping review is based on the framework of Arksey and O'Malley. By using this, only articles published in English will be included. The retrieval of literature items should be based on a literature search string combining keywords related to data anonymization, CDM standards, and data quality assessment. The proposed literature search query should be validated by a librarian, accompanied by manual searches to include further informal sources. Eligible articles will first undergo a deduplication step, followed by the screening of titles. Second, a full-text reading will allow the 2 reviewers involved to reach the final decision about article selection, while a domain expert will support the resolution of citation selection conflicts. Additionally, key information will be extracted, categorized, summarized, and analyzed by using a proposed template into an iterative process. Tabular and graphical analyses should be addressed in alignment with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. We also performed some tentative searches on Web of Science for estimating the feasibility of reaching eligible articles., Results: Tentative searches on Web of Science resulted in 507 nonduplicated matches, suggesting the availability of (potential) relevant articles. Further analysis and selection steps will allow us to derive a final literature set. Furthermore, the completion of this scoping review study is expected by the end of the fourth quarter of 2023., Conclusions: Outlining the approaches of applying formal anonymization methods on CDM-formatted health care data while taking into account data quality and utility concerns should provide useful insights to understand the existing approaches and future research direction based on identified gaps. This protocol describes a schedule to perform a scoping review, which should support the conduction of follow-up investigations., International Registered Report Identifier (irrid): PRR1-10.2196/46471., (©Gaetan Kamdje Wabo, Fabian Prasser, Kerstin Gierend, Fabian Siegel, Thomas Ganslandt. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 11.08.2023.)

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]

The Brazilian Plant-Pollinator Interactions Network*1 (REBIPP) aims to develop scientific and teaching activities in plant-pollinator interaction. The main goals of the network are to: 1. generate a diagnosis of plant-pollinator interactions in Brazil; 2. integrate knowledge in pollination of natural, agricultural, urban and restored areas; 3. identify knowledge gaps; 4. support public policy guidelines aimed at the conservation of biodiversity and ecosystem services for pollination and food production; 5. and encourage collaborative studies among REBIPP participants. To achieve these goals the group has resumed and built on previous works in data standard definition done under the auspices of the IABIN-PTN (Etienne Américo et al. 2007) and FAO (Saraiva et al. 2010) projects (Saraiva et al. 2017). The ultimate goal is to standardize the ways data on plant-pollinator interactions are digitized, to facilitate data sharing and aggregation. A database will be built with standardized data from Brazilian researchers members of the network to be used by the national community, and to allow sharing data with data aggregators. To achieve those goals three task groups of specialists with similar interests and background (e.g botanists, zoologists, pollination biologists) have been created. Each group is working on the definition of the terms to describe plants, pollinators and their interactions. The glossary created explains their meaning, trying to map the suggested terms into Darwin Core (DwC) terms, and following the TDWG Standards Documentation Standard*2 in definition. Reaching a consensus on terms and their meaning among members of each group is challenging, since researchers have different views and concerns about which data are important to be included into a standard. That reflects the variety of research questions that underlie different projects and the data they collect. Thus, we ended up having a long list of terms, many of them useful only in very specialized research protocols and experiments, sometimes rarely collected or measured. Nevertheless we opted to maintain a very comprehensive set of terms, so that a large number of researchers feel that the standard meets their needs and that the databases based on it are a suitable place to store their data, thus encouraging the adoption of the data standard. An update of the work will soon be available at REBIPP website and will be open for comments and contributions. This proposal of a data standard is also being discussed within the TDWG Biological Interaction Data Interest Group*3 in order to propose an international standard for species interaction data. The importance of interaction data for guiding conservation practices and ecosystem services provision management has led to the proposal of defining Essential Biodiversity Variables (EBVs) related to biological interactions. Essential Biodiversity Variables (Pereira et al. 2013) were developed to identify key measurements that are required to monitoring biodiversity change. EBVs act as intermediate abstract layer between primary observations (raw data) and indicators (Niemeijer 2002). Five EBV classes have been defined in an initial stage: genetic composition, species populations, species traits, community composition, ecosystem function and ecosystem structure. Each EBV class defines a list of candidate EBVs for biodiversity change monitoring (Fig. 1). Consequently, digitalization of such data and making them available online are essential. Differences in sampling protocols may affect data scalability across space and time, hence imposing barriers to the full use of primary data and EBVs calculation (Henry et al. 2008). Thus, common protocols and methods should be adopted as the most straightforward approach to promote integration of collected data and to allow calculation of EBVs (Jürgens et al. 2011). Recently a Workshop was held by GLOBIS B*4 (GLOBal Infrastructures for Supporting Biodiversity research) to discuss Species Interactions EBVs (February, 26-28, Bari, Italy). Plant-pollinator interactions deserved a lot of attention and REBIPP's work was presented there. As an outcome we expect to define specific EBVs for interactions, and use plant- pollinators as an example, considering pairwise interactions as well as interaction network related variables. The terms in the plant-pollinator data standard under discussion at REBIPP will provide information not only on EBV related with interactions, but also on other four EBV classes: species populations, species traits, community composition, ecosystem function and ecosystem structure. As we said, some EBVs for specific ecosystem functions (e.g. pollination) lay beyond interactions network structures. The EBV 'Species interactions' (EBV class 'Community composition') should incorporate other aspects such as frequency (Vázquez et al. 2005), duration and empirical estimates of interaction strengths (Berlow et al. 2004). Overall, we think the proposed plant-pollinator interaction data standard which is currently being developed by REBIPP will contribute to data aggregation, filling many data gaps and can also provide indicators for long-term monitoring, being an essential source of data for EBVs. [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]