linked data
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Electronic Health Record (EHR) systems currently in use are not designed for widely interoperable longitudinal health data. Therefore, EHR data cannot be properly shared, managed and analyzed. In this article, we propose two approaches to making EHR data more comprehensive and FAIR (Findable, Accessible, Interoperable, and Reusable) and thus more useful for diagnosis and clinical research. Firstly, the data modeling based on the LinkML framework makes the data interoperability more realistic in diverse environments with various experts involved. We show the first results of how diverse health data can be integrated based on an easy-to-understand data model and without loss of available clinical knowledge. Secondly, decentralizing EHRs contributes to the higher availability of comprehensive and consistent EHR data. We propose a technology stack for decentralized EHRs and the reasons behind this proposal. Moreover, the two proposed approaches empower patients because their EHR data can become more available, understandable, and usable for them, and they can share their data according to their needs and preferences. Finally, we explore how the users of the proposed solution could be involved in the process of its validation and adoption.
- Klíčová slova
- Distributed electronic health records, FAIR principles, HL7 FHIR, bio-data management, ontology,
- MeSH
- data management MeSH
- elektronické zdravotní záznamy * MeSH
- lidé MeSH
- sémantický web * MeSH
- software MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Sex chromosomes present a genomic region which to some extent, differs between the genders of a single species. Reliable high-throughput methods for detection of sex chromosomes specific markers are needed, especially in species where genome information is limited. Next generation sequencing (NGS) opens the door for identification of unique sequences or searching for nucleotide polymorphisms between datasets. A combination of classical genetic segregation analysis along with RNA-Seq data can present an ideal tool to map and identify sex chromosome-specific expressed markers. To address this challenge, we established genetic cross of dioecious plant Rumex acetosa and generated RNA-Seq data from both parental generation and male and female offspring. RESULTS: We present a pipeline for detection of sex linked genes based on nucleotide polymorphism analysis. In our approach, tracking of nucleotide polymorphisms is carried out using a cross of preferably distant populations. For this reason, only 4 datasets are needed - reads from high-throughput sequencing platforms for parent generation (mother and father) and F1 generation (male and female progeny). Our pipeline uses custom scripts together with external assembly, mapping and variant calling software. Given the resource-intensive nature of the computation, servers with high capacity are a requirement. Therefore, in order to keep this pipeline easily accessible and reproducible, we implemented it in Galaxy - an open, web-based platform for data-intensive biomedical research. Our tools are present in the Galaxy Tool Shed, from which they can be installed to any local Galaxy instance. As an output of the pipeline, user gets a FASTA file with candidate transcriptionally active sex-linked genes, sorted by their relevance. At the same time, a BAM file with identified genes and alignment of reads is also provided. Thus, polymorphisms following segregation pattern can be easily visualized, which significantly enhances primer design and subsequent steps of wet-lab verification. CONCLUSIONS: Our pipeline presents a simple and freely accessible software tool for identification of sex chromosome linked genes in species without an existing reference genome. Based on combination of genetic crosses and RNA-Seq data, we have designed a high-throughput, cost-effective approach for a broad community of scientists focused on sex chromosome structure and evolution.
- MeSH
- genetické markery genetika MeSH
- genom lidský MeSH
- geny vázané na chromozom X * MeSH
- geny vázané na chromozom Y * MeSH
- jednonukleotidový polymorfismus genetika MeSH
- lidé MeSH
- polymerázová řetězová reakce MeSH
- RNA genetika MeSH
- sekvenční analýza RNA metody MeSH
- software * MeSH
- vysoce účinné nukleotidové sekvenování metody MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- genetické markery MeSH
- RNA MeSH
BACKGROUND: The capacity to use data linkage and artificial intelligence to estimate and predict health indicators varies across European countries. However, the estimation of health indicators from linked administrative data is challenging due to several reasons such as variability in data sources and data collection methods resulting in reduced interoperability at various levels and timeliness, availability of a large number of variables, lack of skills and capacity to link and analyze big data. The main objective of this study is to develop the methodological guidelines calculating population-based health indicators to guide European countries using linked data and/or machine learning (ML) techniques with new methods. METHOD: We have performed the following step-wise approach systematically to develop the methodological guidelines: i. Scientific literature review, ii. Identification of inspiring examples from European countries, and iii. Developing the checklist of guidelines contents. RESULTS: We have developed the methodological guidelines, which provide a systematic approach for studies using linked data and/or ML-techniques to produce population-based health indicators. These guidelines include a detailed checklist of the following items: rationale and objective of the study (i.e., research question), study design, linked data sources, study population/sample size, study outcomes, data preparation, data analysis (i.e., statistical techniques, sensitivity analysis and potential issues during data analysis) and study limitations. CONCLUSIONS: This is the first study to develop the methodological guidelines for studies focused on population health using linked data and/or machine learning techniques. These guidelines would support researchers to adopt and develop a systematic approach for high-quality research methods. There is a need for high-quality research methodologies using more linked data and ML-techniques to develop a structured cross-disciplinary approach for improving the population health information and thereby the population health.
The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard.
- Klíčová slova
- Data management plan, Machine-actionable data management plan, Ontology, Semantic web technologies,
- MeSH
- bio-ontologie * MeSH
- data management * MeSH
- řízený slovník MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: International comparisons of population birth data provide essential benchmarks for evaluating perinatal health policies. OBJECTIVES: This study aimed to describe routine national data sources in Europe by their ability to provide core perinatal health indicators. METHODS: The Euro-Peristat Network collected routine national data on a recommended set of core indicators from 2015 to 2021 using a federated protocol based on a common data model with 16 data items. Data providers completed an online questionnaire to describe the sources used in each country. We classified countries by the number of data items they provided (all 16, 15-14, < 14). RESULTS: A total of 29 out of the 31 countries that provided data responded to the survey. Routine data sources included birth certificates (15 countries), electronic medical records (EMR) from delivery hospitalisations (16 countries), direct entry by health providers (9 countries), EMR from other care providers (7 countries) and Hospital Discharge Summaries (7 countries). Completeness of population coverage was at least 98%, with 17 countries reporting 100%. These databases most often included mothers giving birth in the national territory, regardless of nationality or place of residence (24 countries), whereas others register births to residents only. In 20 countries, routine sources were linked, including linkage between birth and death certificates (16 countries). Countries providing all 16 items (n = 8) were more likely to use EMRs from delivery hospitalisations (100%) compared to 50% and 11% in countries with 15-14 items (n = 12) and < 14 items (n = 9), respectively. Linkage was also more common in these countries (100%) versus 75% and 56%, respectively. Other data source characteristics did not differ by the ability to provide data on core perinatal indicators. CONCLUSIONS: There are wide differences between countries in the data sources used to construct perinatal health indicators in Europe. Countries using EMR linking to other sources had the best data availability.
- Klíčová slova
- Europe, birth data, international comparisons, perinatal indicators, pregnancy,
- MeSH
- elektronické zdravotní záznamy statistika a číselné údaje MeSH
- informační zdroje MeSH
- lidé MeSH
- novorozenec MeSH
- perinatální péče * statistika a číselné údaje normy MeSH
- rodné listy * MeSH
- rutinně sbírané zdravotní údaje * MeSH
- těhotenství MeSH
- Check Tag
- lidé MeSH
- novorozenec MeSH
- těhotenství MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- srovnávací studie MeSH
- Geografické názvy
- Evropa epidemiologie MeSH
Mining, water-reservoir impoundment, underground gas storage, geothermal energy exploitation and hydrocarbon extraction have the potential to cause rock deformation and earthquakes, which may be hazardous for people, infrastructure and the environment. Restricted access to data constitutes a barrier to assessing and mitigating the associated hazards. Thematic Core Service Anthropogenic Hazards (TCS AH) of the European Plate Observing System (EPOS) provides a novel e-research infrastructure. The core of this infrastructure, the IS-EPOS Platform (tcs.ah-epos.eu) connected to international data storage nodes offers open access to large grouped datasets (here termed episodes), comprising geoscientific and associated data from industrial activity along with a large set of embedded applications for their efficient data processing, analysis and visualization. The novel team-working features of the IS-EPOS Platform facilitate collaborative and interdisciplinary scientific research, public understanding of science, citizen science applications, knowledge dissemination, data-informed policy-making and the teaching of anthropogenic hazards related to georesource exploitation. TCS AH is one of 10 thematic core services forming EPOS, a solid earth science European Research Infrastructure Consortium (ERIC) (www.epos-ip.org).
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: A minority of European countries have participated in international comparisons with high level data on lung cancer. However, the nature and extent of data collection across the continent is simply unknown, and without accurate data collection it is not possible to compare practice and set benchmarks to which lung cancer services can aspire. METHODS: Using an established network of lung cancer specialists in 37 European countries, a survey was distributed in December 2014. The results relate to current practice in each country at the time, early 2015. The results were compiled and then verified with co-authors over the following months. RESULTS: Thirty-five completed surveys were received which describe a range of current practice for lung cancer data collection. Thirty countries have data collection at the national level, but this is not so in Albania, Bosnia-Herzegovina, Italy, Spain and Switzerland. Data collection varied from paper records with no survival analysis, to well-established electronic databases with links to census data and survival analyses. CONCLUSION: Using a network of committed clinicians, we have gathered validated comparative data reporting an observed difference in data collection mechanisms across Europe. We have identified the need to develop a well-designed dataset, whilst acknowledging what is feasible within each country, and aspiring to collect high quality data for clinical research.
- Klíčová slova
- Audit, Data collection, Datasets, Epidemiology, Lung Cancer,
- MeSH
- databáze faktografické statistika a číselné údaje MeSH
- lékařská onkologie metody statistika a číselné údaje MeSH
- lidé MeSH
- nádory plic diagnóza terapie MeSH
- sběr dat metody statistika a číselné údaje MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Evropa MeSH
In this chapter, we demonstrate the advantage of the simultaneous multicurve nonlinear least-squares analysis over that of the conventional single-curve analysis. Fitting results are subjected to thorough Monte Carlo analysis for rigorous assessment of confidence intervals and parameter correlations. The comparison is performed on a practical example of simulated steady-state reaction kinetics complemented with isothermal calorimetry (ITC) data resembling allosteric behavior of rabbit muscle pyruvate kinase (RMPK). Global analysis improves accuracy and confidence limits of model parameters. Cross-correlation between parameters is also reduced with accompanying enhancement of the model-testing power. This becomes especially important for validation of models with "difficult" highly cross-correlated parameters. We show how proper experimental design and critical evaluation of data can improve the chance of differentiating models.
- MeSH
- kalorimetrie MeSH
- králíci MeSH
- metoda Monte Carlo MeSH
- metoda nejmenších čtverců MeSH
- pyruvátkinasa chemie metabolismus MeSH
- zvířata MeSH
- Check Tag
- králíci MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- Názvy látek
- pyruvátkinasa MeSH
UNLABELLED: With biodiversity research activities being increasingly shifted to the web, the need for a system of persistent and stable identifiers for physical collection objects becomes increasingly pressing. The Consortium of European Taxonomic Facilities agreed on a common system of HTTP-URI-based stable identifiers which is now rolled out to its member organizations. The system follows Linked Open Data principles and implements redirection mechanisms to human-readable and machine-readable representations of specimens facilitating seamless integration into the growing semantic web. The implementation of stable identifiers across collection organizations is supported with open source provider software scripts, best practices documentations and recommendations for RDF metadata elements facilitating harmonized access to collection information in web portals. DATABASE URL: : http://cetaf.org/cetaf-stable-identifiers.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
- Publikační typ
- časopisecké články MeSH
- tisková chyba MeSH
