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1.
F1000Res ; 102021.
Artigo em Inglês | MEDLINE | ID: mdl-34249331

RESUMO

Background: Many types of data from genomic analyses can be represented as genomic tracks, i.e. features linked to the genomic coordinates of a reference genome. Examples of such data are epigenetic DNA methylation data, ChIP-seq peaks, germline or somatic DNA variants, as well as RNA-seq expression levels. Researchers often face difficulties in locating, accessing and combining relevant tracks from external sources, as well as locating the raw data, reducing the value of the generated information. Description of work: We propose to advance the application of FAIR data principles (Findable, Accessible, Interoperable, and Reusable) to produce searchable metadata for genomic tracks. Findability and Accessibility of metadata can then be ensured by a track search service that integrates globally identifiable metadata from various track hubs in the Track Hub Registry and other relevant repositories. Interoperability and Reusability need to be ensured by the specification and implementation of a basic set of recommendations for metadata. We have tested this concept by developing such a specification in a JSON Schema, called FAIRtracks, and have integrated it into a novel track search service, called TrackFind. We demonstrate practical usage by importing datasets through TrackFind into existing examples of relevant analytical tools for genomic tracks: EPICO and the GSuite HyperBrowser. Conclusion: We here provide a first iteration of a draft standard for genomic track metadata, as well as the accompanying software ecosystem. It can easily be adapted or extended to future needs of the research community regarding data, methods and tools, balancing the requirements of both data submitters and analytical end-users.


Assuntos
Ecossistema , Metadados , Genoma , Genômica , Software
2.
Int J Mol Sci ; 22(10)2021 May 18.
Artigo em Inglês | MEDLINE | ID: mdl-34069990

RESUMO

The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as 'Amplicon Sequence Variants' (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.


Assuntos
Código de Barras de DNA Taxonômico/estatística & dados numéricos , Metagenômica/estatística & dados numéricos , Microbiota/genética , Software , Algoritmos , Análise por Conglomerados , Biologia Computacional/métodos , Interpretação Estatística de Dados , Sequenciamento de Nucleotídeos em Larga Escala , Metadados , RNA Ribossômico 16S/genética , Análise de Sequência de DNA
3.
Environ Sci Technol ; 55(13): 9352-9361, 2021 07 06.
Artigo em Inglês | MEDLINE | ID: mdl-34133145

RESUMO

Adsorption of uranium onto goethite is an important partitioning process that controls uranium mobility in subsurface environments, for which many different surface complexation models (SCMs) have been developed. While individual models can fit the data for which they are parameterized, many perform poorly when compared with experimental data covering a broader range of conditions. There is an imperative need to quantitatively evaluate the variations in the models and to develop a more robust model that can be used with more confidence across the wide range of conditions. We conducted an intercomparison and refinement of the SCMs based on a metadata analysis. By seeking the globally best fit to a composite dataset with wide ranges of pH, solid/sorbate ratios, and carbonate concentrations, we developed a series of models with different levels of complexity following a systematic roadmap. The goethite-uranyl-carbonate ternary surface complexes were required in every model. For the spectroscopically informed models, a triple-plane model was found to provide the best fit, but the performance of the double-layer model with bidentate goethite-uranyl and goethite-uranyl-carbonate complexes was also comparable. Nevertheless, the models that ignore the bidentate feature of uranyl surface complexation consistently performed poorly. The goodness of fitting for the models that ignore adsorption of carbonate and the charge distributions was not significantly compromised compared with that of their counterparts that considered those. This approach of model development for a large and varied dataset improved our understanding of U(VI)-goethite surface reactions and can lead to a path for generating a single set of reactions and equilibrium constants for including U(VI) adsorption onto goethite in reactive transport models.


Assuntos
Compostos de Ferro , Urânio , Adsorção , Concentração de Íons de Hidrogênio , Metadados , Minerais
4.
BMC Res Notes ; 14(1): 189, 2021 May 17.
Artigo em Inglês | MEDLINE | ID: mdl-34001211

RESUMO

OBJECTIVE: The SARS-CoV-2 pandemic has prompted one of the most extensive and expeditious genomic sequencing efforts in history. Each viral genome is accompanied by a set of metadata which supplies important information such as the geographic origin of the sample, age of the host, and the lab at which the sample was sequenced, and is integral to epidemiological efforts and public health direction. Here, we interrogate some shortcomings of metadata within the GISAID database to raise awareness of common errors and inconsistencies that may affect data-driven analyses and provide possible avenues for resolutions. RESULTS: Our analysis reveals a startling prevalence of spelling errors and inconsistent naming conventions, which together occur in an estimated ~ 9.8% and ~ 11.6% of "originating lab" and "submitting lab" GISAID metadata entries respectively. We also find numerous ambiguous entries which provide very little information about the actual source of a sample and could easily associate with multiple sources worldwide. Importantly, all of these issues can impair the ability and accuracy of association studies by deceptively causing a group of samples to identify with multiple sources when they truly all identify with one source, or vice versa.


Assuntos
COVID-19 , SARS-CoV-2 , Genoma Viral/genética , Genômica , Humanos , Metadados , Filogenia
5.
Stud Health Technol Inform ; 281: 488-489, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042614

RESUMO

The Portal of Medical Data Models has been developed since 2011 by the University of Münster. Its main goals are transparency, standardization and secondary use of medical metadata. Via two online surveys feedback from stakeholders of German health research was collected regarding the portal's contents. The surveys confirmed great interest in secondary use of medical forms.


Assuntos
Metadados , Retroalimentação , Inquéritos e Questionários
6.
Stud Health Technol Inform ; 281: 779-783, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042684

RESUMO

The data produced during a research project are too often collected for the sole purpose of the study, therefore hindering profitable reuse in similar contexts. The growing need to counteract this trend has recently led to the formalization of the FAIR principles that aim to make (meta)data Findable, Accessible, Interoperable and Reusable, for humans and machines. Since their introduction, efforts are ongoing to encourage FAIR principles adoption and to implement solutions based on them. This paper reports on the FAIR-compliant registry we developed to collect and serve metadata describing clinical trials. The design of the registry is based on the FAIR Data Point (FDP) specifications, the state-of-the-art reference for FAIRified metadata sharing. To map the metadata relevant to our use case, we have extended the DCAT-based semantic model of the FDP adopting well-established ontologies in the biomedical and clinical domain, like the Semanticscience Integrated Ontology (SIO). Current implementation is based on the Molgenis software and provides both a user interface and a REST API for metadata discovering. At present the registry is being loaded with the metadata of the 18 clinical studies included in the 'I FAIR Program', a project finalised to the dissemination of FAIR best practices among the clinical researchers in Sardinia (Italy). After a testing phase, the registry will be publicly available, while the new model and the source code will be released open source.


Assuntos
Pesquisa Biomédica , Metadados , Humanos , Itália , Sistema de Registros , Software
7.
Stud Health Technol Inform ; 281: 794-798, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042687

RESUMO

COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.


Assuntos
COVID-19 , Estudos Epidemiológicos , Humanos , Metadados , Sistema de Registros , SARS-CoV-2
8.
Stud Health Technol Inform ; 281: 18-22, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042697

RESUMO

Metadata management is an essential condition to follow the FAIR principles. Therefore, metadata management was one asset of an accompanying project within a funding scheme for registries in health services research. The metadata of the funded projects were acquired, combined in a database compatible with the metamodel of ISO/IEC 11179 "Information technology - Metadata registries" third edition (ISO/IEC 11179-3), and analyzed in order to support the development and the operation of the registries. In the second phase of the funding scheme, six registries delivered a complete update of their metadata. The mean number of data elements increased from 245.7 to 473.5 and the mean number of values from 569.5 to 1,306.0. The conceptual core of the database had to be extended by one third to cover the new elements. The reason for this increase remained unclear. Constraints from the grant might be causal, a deviation from an evidence-based development process as well. It is questionable, whether the revealed quality of the metadata is sufficient to fulfill the FAIR principles. The extension of the metamodel of ISO/IEC 11179-3 is in agreement with the literature. However, further research is needed to find workable solutions for metadata management.


Assuntos
Pesquisa sobre Serviços de Saúde , Metadados , Bases de Dados Factuais , Tecnologia da Informação , Sistema de Registros
9.
Stud Health Technol Inform ; 281: 372-376, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042768

RESUMO

Registries of clinical studies such as ClinicalTrials.gov are an important source of information. However, the process of manually entering metadata is prone to errors which impedes their use and thereby the overall usefulness of the registry. In this work, we propose a generic approach towards detection of errors in the metadata by using the Shapes Constraint Language for defining rule templates covering constraints regarding value type and cardinality. We developed a Python 3 algorithm for the automatic validation of 15 rule instances applied to the whole ClinicalTrials.gov database (355,862 studies; 27th October 2020) resulting in more than 5 million metadata verifications. Our results show a large number of errors in different metadata fields, such as i) missing values, ii) values not coming from a predefined set or iii) wrong cardinalities, can be detected using this approach. Since 2015 approximately 5% of all studies contain one or more errors. In the future, we will apply this technique to other registries and develop more complex rules by focusing on the semantics of the metadata. This could render the possibility of automatically correcting entries, increasing the value of registries of clinical studies.


Assuntos
Idioma , Metadados , Bases de Dados Factuais , Sistema de Registros , Semântica
10.
Stud Health Technol Inform ; 281: 387-391, 2021 May 27.
Artigo em Inglês | MEDLINE | ID: mdl-34042771

RESUMO

Advancements in regenerative medicine have highlighted the need for increased standardization and sharing of stem cell products to help drive these innovative interventions toward public availability and to increase collaboration in the scientific community. Although numerous attempts and numerous databases have been made to store this data, there is still a lack of a platform that incorporates heterogeneous stem cell information into a harmonized project-based framework. The aim of the platform described in this study, ReMeDy, is to provide an intelligent informatics solution which integrates diverse stem cell product characteristics with study subject and omics information. In the resulting platform, heterogeneous data is validated using predefined ontologies and stored in a relational database. In this initial feasibility study, testing of the ReMeDy functionality was performed using published, publically-available induced pluripotent stem cell projects conducted in in vitro, preclinical and intervention evaluations. It demonstrated the robustness of ReMeDy for storing diverse iPSC data, by seamlessly harmonizing diverse common data elements, and the potential utility of this platform for driving knowledge generation from the aggregation of this shared data. Next steps include increasing the number of curated projects by developing a crowdsourcing framework for data upload and an automated pipeline for metadata abstraction. The database is publically accessible at https://remedy.mssm.edu/.


Assuntos
Crowdsourcing , Pesquisa com Células-Tronco , Bases de Dados Factuais , Metadados
11.
Stud Health Technol Inform ; 278: 35-40, 2021 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-34042873

RESUMO

The Operational Data Model (ODM) is a data standard for interchanging clinical trial data. ODM contains the metadata definition of a study, i.e., case report forms, as well as the clinical data, i.e., the answers of the participants. The portal of medical data models is an infrastructure for creation, exchange, and analysis of medical metadata models. There, over 23000 metadata definitions can be downloaded in ODM format. Due to data protection law and privacy issues, clinical data is not contained in these files. Access to exemplary clinical test data in the desired metadata definition is necessary in order to evaluate systems claiming to support ODM or to evaluate if a planned statistical analysis can be performed with the defined data types. In this work, we present a web application, which generates syntactically correct clinical data in ODM format based on an uploaded ODM metadata definition. Data types and range constraints are taken into account. Data for up to one million participants can be generated in a reasonable amount of time. Thus, in combination with the portal of medical data models, a large number of ODM files including metadata definition and clinical data can be provided for testing of any ODM supporting system. The current version of the application can be tested at https://cdgen.uni-muenster.de and source code is available, under MIT license, at https://imigitlab.uni-muenster.de/published/odm-clinical-data-generator.


Assuntos
Pesquisa Biomédica , Metadados , Humanos , Software
12.
Stud Health Technol Inform ; 278: 41-48, 2021 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-34042874

RESUMO

Rare lung diseases affect 1.5-3 million people in Europe while causing bad prognosis or early deaths for patients. The European Reference Network for Respiratory Diseases (ERN-Lung) is a patient centric network, funded by the European Union (EU). The aims of ERN-LUNG is to increase healthcare and research regarding rare respiratory diseases. An initial need for cross-border healthcare and research is the use of registries and databases. A typical problem in registries for RDs is the data exchange, since the registries use different kind of data with different types or descriptions. Therefore, ERN-Lung decided to create a new Registry Data-Warehouse (RDW) where different existing registries are connected to enable cross-border healthcare within ERN-Lung. This work facilitates the aims, conception and implementation for the RDW, while considering a semantic interoperability approach. We created a common dataset (CDS) to have a common descriptions of respiratory diseases patients within the ERN registries. We further developed the RDW based on Open Source Registry System for Rare Diseases (OSSE), which includes a Metadata Repository with the Samply.MDR to unique describe data for the minimal dataset. Within the RDW, data from existing registries is not stored in a central database. The RDW uses the approach of the "Decentral Search" and can send requests to the connected registries, whereas only aggregated data is returned about how many patients with specific characteristics are available. However, further work is needed to connect the different existing registries to the RDW and to perform first studies.


Assuntos
Data Warehousing , Doenças Raras , Europa (Continente)/epidemiologia , Humanos , Metadados , Doenças Raras/epidemiologia , Sistema de Registros
13.
Stud Health Technol Inform ; 278: 66-74, 2021 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-34042877

RESUMO

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.


Assuntos
Metadados , Software , Arquivos , Fenótipo , Reprodutibilidade dos Testes
14.
Stud Health Technol Inform ; 278: 94-100, 2021 May 24.
Artigo em Inglês | MEDLINE | ID: mdl-34042881

RESUMO

Metadata repositories are an indispensable component of data integration infrastructures and support semantic interoperability between knowledge organization systems. Standards for metadata representation like the ISO/IEC 11179 as well as the Resource Description Framework (RDF) and the Simple Knowledge Organization System (SKOS) by the World Wide Web Consortium were published to ensure metadata interoperability, maintainability and sustainability. The FAIR guidelines were composed to explicate those aspects in four principles divided in fifteen sub-principles. The ISO/IEC 21526 standard extends the 11179 standard for the domain of health care and mandates that SKOS be used for certain scenarios. In medical informatics, the composition of health care SKOS classification schemes is often managed by documentalists and data scientists. They use editors, which support them in producing comprehensive and valid metadata. Current metadata editors either do not properly support the SKOS resource annotations, require server applications or make use of additional databases for metadata storage. These characteristics are contrary to the application independency and versatility of raw Unicode SKOS files, e.g. the custom text arrangement, extensibility or copy & paste editing. We provide an application that adds navigation, auto completion and validity check capabilities on top of a regular Unicode text editor.


Assuntos
Informática Médica , Metadados , Bases de Dados Factuais , Atenção à Saúde , Vocabulário Controlado
15.
BMC Med Inform Decis Mak ; 21(1): 160, 2021 05 17.
Artigo em Inglês | MEDLINE | ID: mdl-34001121

RESUMO

BACKGROUND: The variety of medical documentation often leads to incompatible data elements that impede data integration between institutions. A common approach to standardize and distribute metadata definitions are ISO/IEC 11179 norm-compliant metadata repositories with top-down standardization. To the best of our knowledge, however, it is not yet common practice to reuse the content of publicly accessible metadata repositories for creation of case report forms or routine documentation. We suggest an alternative concept called pragmatic metadata repository, which enables a community-driven bottom-up approach for agreeing on data collection models. A pragmatic metadata repository collects real-world documentation and considers frequent metadata definitions as high quality with potential for reuse. METHODS: We implemented a pragmatic metadata repository proof of concept application and filled it with medical forms from the Portal of Medical Data Models. We applied this prototype in two use cases to demonstrate its capabilities for reusing metadata: first, integration into a study editor for the suggestion of data elements and, second, metadata synchronization between two institutions. Moreover, we evaluated the emergence of bottom-up standards in the prototype and two medical data managers assessed their quality for 24 medical concepts. RESULTS: The resulting prototype contained 466,569 unique metadata definitions. Integration into the study editor led to a reuse of 1836 items and item groups. During the metadata synchronization, semantic codes of 4608 data elements were transferred. Our evaluation revealed that for less complex medical concepts weak bottom-up standards could be established. However, more diverse disease-related concepts showed no convergence of data elements due to an enormous heterogeneity of metadata. The survey showed fair agreement (Kalpha = 0.50, 95% CI 0.43-0.56) for good item quality of bottom-up standards. CONCLUSIONS: We demonstrated the feasibility of the pragmatic metadata repository concept for medical documentation. Applications of the prototype in two use cases suggest that it facilitates the reuse of data elements. Our evaluation showed that bottom-up standardization based on a large collection of real-world metadata can yield useful results. The proposed concept shall not replace existing top-down approaches, rather it complements them by showing what is commonly used in the community to guide other researchers.


Assuntos
Documentação , Metadados , Humanos , Padrões de Referência , Semântica
16.
Stud Health Technol Inform ; 279: 144-146, 2021 May 07.
Artigo em Inglês | MEDLINE | ID: mdl-33965931

RESUMO

BACKGROUND: Integration of heterogenous resources is key for Rare Disease research. Within the EJP RD, common Application Programming Interface specifications are proposed for discovery of resources and data records. This is not sufficient for automated processing between RD resources and meeting the FAIR principles. OBJECTIVE: To design a solution to improve FAIR for machines for the EJP RD API specification. METHODS: A FAIR Data Point is used to expose machine-actionable metadata of digital resources and it is configured to store its content to a semantic database to be FAIR at the source. RESULTS: A solution was designed based on grlc server as middleware to implement the EJP RD API specification on top of the FDP. CONCLUSION: grlc reduces potential API implementation overhead faced by maintainers who use FAIR at the source.


Assuntos
Doenças Raras , Software , Bases de Dados Factuais , Humanos , Internet , Metadados , Semântica
17.
Clin Nucl Med ; 46(8): 635-640, 2021 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-33883488

RESUMO

PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata. METHODS: A total of 359 patients with a lung mass or nodule who underwent noncontrast chest CT and FDG PET/CT prior to treatment were enrolled retrospectively. All pulmonary lesions were classified by pathology (257 malignant, 102 benign). Deep learning classification models based on ResNet-18 were developed using the pretrained weights obtained from ImageNet data set. We propose a deep TL model for differential diagnosis of lung cancer using CT imaging data and metadata with SUVmax and lesion size derived from PET/CT. The area under the receiver operating characteristic curve (AUC) of the deep learning model was measured as a performance metric and verified by 5-fold cross-validation. RESULTS: The performance metrics of the conventional CT model were generally better than those of the CT of PET/CT model. Introducing metadata with SUVmax and lesion size derived from PET/CT into baseline CT models improved the diagnostic performance of the CT of PET/CT model (AUC = 0.837 vs 0.762) and the conventional CT model (AUC = 0.877 vs 0.817). CONCLUSIONS: Deep TL models with CT imaging data provide good diagnostic performance for lung cancer, and the conventional CT model showed overall better performance than the CT of PET/CT model. Metadata information derived from PET/CT can improve the performance of deep learning systems.


Assuntos
Aprendizado Profundo , Fluordesoxiglucose F18 , Processamento de Imagem Assistida por Computador/métodos , Neoplasias Pulmonares/diagnóstico por imagem , Metadados , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Idoso , Diagnóstico Diferencial , Humanos , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Curva ROC , Estudos Retrospectivos
18.
RECIIS (Online) ; 15(1): 6-11, jan.-mar. 2021.
Artigo em Inglês | LILACS | ID: biblio-1152250

RESUMO

This commentary discusses recent developments in 'knowledge graph' technology over the course of the Covid-19 pandemic. Recently experiencing a surge in popularity, knowledge graphs are technologies that assist with data integration through structured metadata modeling. Researchers tag and collate vast amounts of diverse data using knowledge graphs, yet problems related to semantic drift and more salient issues related to the political economy of information and communication technologies persist. Researchers should anticipate that the semantics of these Covid-19 knowledge graphs can change over time. Equally important, researchers should also consider all stakeholders involved, including those stakeholders that might be excluded.


Este comentário discute desenvolvimentos recentes na tecnologia de 'gráficos de conhecimento' durante o curso da pandemia de Covid-19. Gráficos de conhecimento, que vêm tendo um aumento de popularidade, são tecnologias que auxiliam com a integração de dados através de modelamento estruturado de metadados. Pesquisadores rotulam e agregam vastas quantidades de dados diversos usando gráficos de conhecimento, entretanto persistem problemas relacionados a variações semânticas e questões mais salientes relacionadas à economia política de tecnologias de informação e comunicação. Os pesquisadores devem prever que a semântica desses gráficos de conhecimento para Covid-19 pode variar com o tempo. Igualmente importante, os pesquisadores devem também considerar todas as partes interessadas envolvidas, incluindo as que poderiam ser excluídas.


Este ejemplo analiza los desarrollos recientes en la tecnología de 'gráficos de conocimiento' durante la pandemia de Covid-19. Recientemente experimentando un aumento en popularidad, los gráficos de conocimiento son tecnologías que ayudan a la integración de datos a través del modelado de metadatos estructurados. Los investigadores etiquetan y recopilan grandes cantidades de datos diversos utilizando gráficos de conocimiento, pero persisten los problemas relacionados con la deriva semántica y cuestiones más importantes relacionadas con la economía política de las tecnologías de la información y la comunicación. Los investigadores deben prever que la semántica de estos gráficos de conocimiento de Covid-19 puede cambiar con el tiempo. También es importante que los investigadores consideren a todas las partes interesadas involucradas, incluso las que podrían quedar excluidas.


Assuntos
Humanos , Infecções por Coronavirus , Comunicação , Metadados , Betacoronavirus , Web Semântica , Gráficos por Computador , Informação , Tecnologia da Informação
19.
Sci Data ; 8(1): 78, 2021 03 08.
Artigo em Inglês | MEDLINE | ID: mdl-33686079

RESUMO

Using brain atlases to localize regions of interest is a requirement for making neuroscientifically valid statistical inferences. These atlases, represented in volumetric or surface coordinate spaces, can describe brain topology from a variety of perspectives. Although many human brain atlases have circulated the field over the past fifty years, limited effort has been devoted to their standardization. Standardization can facilitate consistency and transparency with respect to orientation, resolution, labeling scheme, file storage format, and coordinate space designation. Our group has worked to consolidate an extensive selection of popular human brain atlases into a single, curated, open-source library, where they are stored following a standardized protocol with accompanying metadata, which can serve as the basis for future atlases. The repository containing the atlases, the specification, as well as relevant transformation functions is available in the neuroparc OSF registered repository or https://github.com/neurodata/neuroparc .


Assuntos
Mapeamento Encefálico/normas , Encéfalo/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador , Metadados
20.
BMC Bioinformatics ; 22(1): 117, 2021 Mar 10.
Artigo em Inglês | MEDLINE | ID: mdl-33691615

RESUMO

BACKGROUND: Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance. RESULTS: Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis. CONCLUSION: AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/ .


Assuntos
Resistência Microbiana a Medicamentos/genética , Microbiologia Ambiental , Genes Bacterianos , Metadados , Metagenômica , Ecossistema , Internet , Metagenoma , Software
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