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A scoping review of semantic integration of health data and information

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2022年第0期165卷 104834-104834页

作者： Zhang, Hansi Lyu, Tianchen Yin, Pengfei Bost, Sarah He, Xing Guo, Yi Prosperi, Mattia Hogan, Willian R. Bian, Jiang Univ Florida Coll Med Hlth Outcomes & Biomed Informat Gainesville FL USA Univ Florida Coll Med Dept Epidemiol Gainesville FL USA 2197 Mowry Rd 122 Gainesville FL 32610 USA

Objective: We summarized a decade of new research focusing on semantic data integration (SDI) since 2009, and we aim to: (1) summarize the state-of-art approaches on integrating health data and information;and (2) identify the main gaps and challenges of integrating health data and information from multiple levels and *** and Methods: We used PubMed as our focus is applications of SDI in biomedical domains and followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) to search and report for relevant studies published between January 1, 2009 and December 31, 2021. We used Covidence-a systematic review management system-to carry out this scoping ***: The initial search from PubMed resulted in 5,326 articles using the two sets of keywords. We then removed 44 duplicates and 5,282 articles were retained for abstract screening. After abstract screening, we included 246 articles for full-text screening, among which 87 articles were deemed eligible for full-text extraction. We summarized the 87 articles from four aspects: (1) methods for the global schema;(2) data integration strategies (i.e., federated system vs. data warehousing);(3) the sources of the data;and (4) downstream ***: SDI approach can effectively resolve the semantic heterogeneities across different data sources. We identified two key gaps and challenges in existing SDI studies that (1) many of the existing SDI studies used data from only single-level data sources (e.g., integrating individual-level patient records from different hospital systems), and (2) documentation of the data integration processes is sparse, threatening the reproducibility of SDI studies.

关键词： semantic data integration Common data model Common data element Ontology Systematic review and meta -analyses (PRISMA) framework

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Efficient Monitoring of Multi-Disciplinary Engineering Constraints with semantic data integration in the Multi-Model Dashboard Process 19

Efficient Monitoring of Multi-Disciplinary Engineering Const...

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19th IEEE International Conference on Emerging Technology and Factory Automation (ETFA)

作者： Biffl, Stefan Winkler, Dietmar Mordinyi, Richard Scheiber, Stefan Holl, Gerald Vienna Univ Technol Inst Software Technol & Interact Syst CDL Flex A-1040 Vienna Austria Johannes Kepler Univ Linz CDL Automated Software Engn A-4040 Linz Austria

ISBN: (纸本)9781479948451

In a multi-disciplinary engineering project, such as the parallel engineering of industrial production plants, domain experts want to efficiently monitor project-level constraints that depend on technical parameter values in local engineering models. However, the heterogeneous representations of constraint parameters in these engineering models make the automation of constraint monitoring difficult. In this paper, we introduce the Multi-Model Dashboard (MMD) process providing semantically integrated values of parameters and of constraints to domain experts, as parameter values in various local models change during the project. The tool-supported MMD process guides the definition and monitoring of MMD parameters and constraints. We evaluate the effectiveness and efficiency of the MMD process in a feasibility study with requirements and data from real-world use cases at industry partners. Major results are that the MMD process was effective and efficient in eliciting relevant project constraints and model dependencies and in providing data for change impact analysis.

关键词： Software Engineering Methods in Automation semantic data integration Change Impact Analysis Engineering Process Observation

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Enhancing Rare Disease Research with semantic integration of Environmental and Health data 21

Enhancing Rare Disease Research with Semantic Integration of...

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Proceedings of the 10th International Joint Conference on Knowledge Graphs

作者： Albert Navarro-Gallinad Fabrizio Orlandi Declan O'Sullivan Trinity College Dublin ADAPT Centre for Digital Content Ireland

ISBN: (纸本)9781450395656

Knowledge Graph (KG) approaches are increasingly being used for data integration processes to combine clinical data with other data sources. Health data Researchers (HDR) could benefit from these technologies since they require additional types of data outside the health sector, like environmental data, to better understand the extrinsic factors that influence health outcomes in rare disease research. However, using and directly navigating the combined data in the KG can be an obstacle for HDRs. To address this problem, the semantic Environmental and Rare Disease data integration Framework (SERDIF) was designed to hide the complexities for these researchers when exploring linked environmental observations with clinical data using a KG approach. The framework was evaluated by HDRs for a case study on Anti-neutrophil cytoplasm antibody (ANCA)-associated vasculitis (AAV) in Ireland, and promising usability and effectiveness results were observed. HDRs studying AAV were able to access, explore and export environmental related data to be used as input for their statistical models. SERDIF has the potential to be a solution for HDRs, who require a flexible methodology to integrate environmental data with longitudinal and geospatial diverse clinical data, in their hypothesis validation of environmental factors for rare disease research.

关键词： Rare diseases Usability Testing Knowledge Graph Environmental Health semantic data integration

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Ontology-Based Digital Infrastructure for data-Driven Glass Development

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ADVANCED ENGINEERING MATERIALS 2025年第8期27卷

作者： Chen, Ya-Fan Arendt, Felix Bornhoeft, Hansjoerg de Camargo, Andrea S. S. Deubener, Joachim Diegeler, Andreas Gogula, Shravya Jaimes, Altair T. Contreras Kempf, Sebastian Kilo, Martin Limbach, Rene Mueller, Ralf Niebergall, Rick Pan, Zhiwen Puppe, Frank Reinsch, Stefan Schottner, Gerhard Stier, Simon Waurischk, Tina Wondraczek, Lothar Sierka, Marek Friedrich Schiller Univ Jena Otto Schott Inst Mat Res Lobdergraben 32 D-07743 Jena Germany Tech Univ Clausthal Inst Nonmet Mat Zehntner Str 2a D-38678 Clausthal Zellerfeld Germany Friedrich Schiller Univ Jena Otto Schott Inst Mat Res Fraunhoferstr 6 D-07743 Jena Germany BAM Fed Inst Mat Res & Testing Div 5 6 Glasses Richard Willstatter Str 11 D-12489 Berlin Germany Fraunhofer Inst Silicate Res ISC Bronnbach 28 D-97877 Wertheim Germany Fraunhofer Inst Silicate Res ISC Neunerpl 2 D-97082 Wurzburg Germany Univ Wurzburg Chair Artificial Intelligence & Knowledge Syst D-97074 Wurzburg Germany

The development of new glasses is often hampered by inefficient trial-and-error approaches. The traditional glass manufacturing process is not only time-consuming, but also difficult to reproduce with inevitable variations in process parameters. These challenges are addressed by implementing an ontology-based digital infrastructure coupled with a robotic melting system. This system facilitates high-throughput glass synthesis and ensures the collection of consistent process data. In addition, the digital infrastructure includes machine learning models for predicting glass properties and a tool for extracting patent information. Current glass databases have significant gaps in the relationships between compositions, process parameters, and properties due to inconsistent studies and nonconforming units. In addition, process parameters are often omitted, and even original literature references provide limited information. By continuously expanding the database with consistent, high-quality data, it is aimed to fill these gaps and accelerate the glass development process.

关键词： application ontology digital infrastructure glasses glass ontology semantic data integration

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Seamless Science: Lifting Experimental Mechanical Testing Lab data to an Interoperable semantic Representation

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ADVANCED ENGINEERING MATERIALS 2025年第8期27卷

作者： Schilling, Markus Bruns, Sebastian Bayerlein, Bernd Kryeziu, Jehona Schaarschmidt, Jorg Waitelonis, Jorg Dolabella Portella, Pedro Durst, Karsten Bundesanstalt Mat Forsch & Prufung BAM Met High Temp Mat Unter Eichen 87 D-12205 Berlin Germany Tech Univ Darmstadt TUDa Phys Met Peter Grunberg Str 2 D-64287 Darmstadt Germany Karlsruhe Inst Technol KIT Inst Nanotechnol INT Hermann von Helmholtz Pl 1 D-76344 Eggenstein Leopoldshafen Germany FIZ Karlsruhe Leibniz Inst Informat Infrastruct Inst Appl Informat & Formal Descript Methods AIFB Hermann von Helmholtz Pl 1 D-76344 Eggenstein Leopoldshafen Germany Fraunhofer Inst Werkstoffmech IWM Wohlerstr 11 D-79108 Freiburg Germany

The scientific landscape is undergoing rapid transformations with the advent of the digital age which revolutionizes research methodologies. In materials science and engineering, an adoption of modern data management techniques is desirable to maximize the efficiency and accessibility of research efforts. Traditional practices in testing laboratories are usually inadequate for efficient data acquisition and utilization as they lead to local storage and difficulty in publication and correlation with other results. Electronic laboratory notebooks (ELNs) are promising prospects in this respect. semantic concepts and ontologies enhance interoperability by standardizing experimental data representation. An in-laboratory pipeline seamlessly integrating an ELN with transformation scripts to convert experimental into interoperable data in a machine-actionable format is created in this study as a proof of concept. Tensile test results and the corresponding tensile test ontology are used exemplary. Linking ELN data to semantic concepts enriches the stored information while improving interpretability and reusability. Involving undergraduate students builds a bridge between theory and practice during their training and promotes their digital skills. This study underscores the potential of ELNs and knowledge representations as beneficial means toward improved data management practices that enhance collaborative research and education while ensuring compatibility with evolving standards and technologies.

关键词： electronic laboratory notebooks mechanical testing ontologies semantic data integration semantic web technologies

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Evaluating the usability of a semantic environmental health data framework: Approach and study

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semantic WEB 2023年第5期14卷 787-810页

作者： Navarro-Gallinad, Albert Orlandi, Fabrizio Scott, Jennifer Little, Mark O'Sullivan, Declan Trinity Coll Dublin ADAPT Ctr Digital Content Sch Comp Sci & Stat Dublin Ireland Univ Dublin Trin Hlth Kidney Ctr Trin Coll Dublin Trin Translat Med Inst Dublin Ireland

Environmental exposures transported across air, land and water can affect our health making us more susceptible to developing a disease. Therefore, researchers need to face the complex task of integrating environmental exposures and linking them to health events with the relevant spatiotemporal and health context for individuals or populations. We present a usability evaluation approach and study of a semantic framework (i.e. Knowledge Graph, Methodology and User Interface) to enable Health data Researchers (HDR) to link particular health events with environmental data for rare disease research. The usability study includes 17 HDRs with expertise in health data related to Anti-Neutrophil Cytoplasmic Antibody (ANCA)-associated vasculitis (AAV) in Ireland and Kawasaki Disease in Japan, and with no previous practical experience in using semantic Web (SW) technologies. The evaluation results are promising in that they indicate that the framework is useful in allowing researchers themselves to link health and environmental data whilst hiding the complexities of SW technologies. As a result of this work, we also discuss the limitations of the approach together with the applicability to other domains. Beyond the direct impact on environmental health studies, the description of the evaluation approach can guide researchers in making SW technologies more accessible to domain experts through usability studies.

关键词： Usability testing semantic data integration knowledge graph environmental health data rare disease research

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Special issue on semantic Web Meets Health data Management

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semantic WEB 2023年第5期14卷 785-786页

作者： Stefanidis, Kostas Kondylakis, Haridimos Rao, Praveen Tampere Univ Tampere Finland FORTH ICS Iraklion Greece Univ Missouri Columbia MO USA

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A semantic Technologies Toolkit for Bridging Early Diagnosis and Treatment in Brain Diseases: Report from the Ongoing EU-Funded Research Project ALAMEDA 15th

A Semantic Technologies Toolkit for Bridging Early Diagnosis...

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15th International Conference on Metadata and semantic Research, MTSR

作者： Maga-Nteve, Christoniki Kontopoulos, Efstratios Tsolakis, Nikos Katakis, Ioannis Mathioudis, Evangelos Mitzias, Panagiotis Avgerinakis, Konstantinos Meditskos, Georgios Karakostas, Anastasios Vrochidis, Stefanos Kompatsiaris, Ioannis Ctr Res & Technol Informat Technol Inst Hellas Greece Catalink Ltd Nicosia Cyprus Univ Nicosia Sch Sci & Engn Dept Comp Sci CY-2417 Nicosia Cyprus Aristotle Univ Thessaloniki Sch Informat Thessaloniki Greece

ISBN: (纸本)9783030988760;9783030988753

semanticWeb technologies are increasingly being deployed in various e-health scenarios, prominently due to their inherent capacity to harmonize heterogeneous information from diverse sources and devices, as well as their capability to providemeaningful interpretations and higher-level insights. This paper reports on ongoing work in the recently started EU-funded project ALAMEDA towards a semantic toolkit for bridging the gap between early diagnosis and treatment in a variety of brain diseases. The toolkit comprises (a) a semantic model serving as the underlying knowledge base for the toolkit;(b) a flexible semantic data integration framework;(c) a semantics-enabled conversational agent for interacting with human users and other components of the ALAMEDA system.

关键词： Ontologies semantic data integration Conversational agent Brain disease e-health

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PMD Core Ontology: Achieving semantic interoperability in materials science

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MATERIALS & DESIGN 2024年 237卷

作者： Bayerlein, Bernd Schilling, Markus Birkholz, Henk Jung, Matthias Waitelonis, Jorg Maedler, Lutz Sack, Harald Bundesanstalt Materialforschung & prufung BAM Unter Eichen 87 D-12205 Berlin Germany Leibniz Inst Mat Engn IWT Badgasteiner Str 3 D-28359 Bremen Germany Fraunhofer Inst Mech Mat IWM Wohlerstr 11 D-79108 Freiburg Im Breisgau Germany FIZ Karlsruhe Leibniz Inst Informat Infrastructure Hermann-von-Helmholtz-Pl 1 D-76344 Eggenstein Leopoldshafen Germany Univ Bremen Badgasteiner Str 3 D-28359 Bremen Germany

Knowledge representation in the Materials Science and Engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant (consistent) and variant (context-specific) knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. In this paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology-the Platform MaterialDigital Core Ontology (PMDco)-via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications.

关键词： Ontology Materials science and engineering Knowledge representation Reproducibility semantic interoperability semantic data integration

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An Architecture and a Methodology Enabling Interoperability within and across Universities 13

An Architecture and a Methodology Enabling Interoperability ...

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13th IEEE International Conference on Knowledge Graph (ICKG)

作者： Giunchiglia, Fausto Maltese, Vincenzo Ganbold, Amarsanaa Zamboni, Alessio Univ Trento Dept Informat Engn & Comp Sci DISI Trento Italy Univ Trento Disseminat & Evaluat Res Results Div Trento Italy Natl Univ Mongolia Dept Informat & Comp Sci DICS Ulaanbaatar Mongolia

ISBN: (纸本)9781665451017

We propose a general methodology and an infrastructure which allows to achieve interoperability within the same university and across universities. The former goal is achieved by incrementally defining and building a knowledge graph (KG) using data coming from multiple heterogeneous databases. Interoperability across universities is achieved by having a reference KG schema that each university can adapt to the local needs, but keeping track of the changes, and by natively supporting multilinguality. We achieve this latter requirement by exploiting a multilingual lexical resource containing more than one thousand languages and by seamlessly translating across the schemas and also (to some extent) across the data written in the local languages. The effectiveness of the proposed approach is proven by the services developed in the context of two different projects conducted in two universities in Italy and Mongolia.

关键词： ontology knowledge graph semantic data integration

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