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Adopting international standards within health research communities can elevate data FAIRness and widen analysis possibilities. The purpose of this study was to evaluate the mapping feasibility against HL7® Fast Healthcare Interoperability Resources® (FHIR)® of a generic metadata schema (MDS) created for a central search hub gathering COVID-19 health research (studies, questionnaires, documents = MDS resource types). Mapping results were rated by calculating the percentage of FHIR coverage. Among 86 items to map, total mapping coverage was 94%: 50 (58%) of the items were available as standard resources in FHIR and 31 (36%) could be mapped using extensions. Five items (6%) could not be mapped to FHIR. Analyzing each MDS resource type, there was a total mapping coverage of 93% for studies and 95% for questionnaires and documents, with 61% of the MDS items available as standard resources in FHIR for studies, 57% for questionnaires and 52% for documents. Extensions in studies, questionnaires and documents were used in 32%, 38% and 43% of items, respectively. This work shows that FHIR can be used as a standardized format in registries for clinical, epidemiological and public health research. However, further adjustments to the initial MDS are recommended – and two additional items even needed when implementing FHIR. Developing a MDS based on the FHIR standard could be a future approach to reduce data ambiguity and foster interoperability.

Background The Health Avatar Platform provides a mobile health environment with interconnected patient Avatars, physician apps, and intelligent agents (termed IoA3) for data privacy and participatory medicine; however, its fully decentralized architecture has come at the expense of decentralized data management and data provenance. Objective The introduction of blockchain and smart contract technologies to the legacy Health Avatar Platform with a clinical metadata registry remarkably strengthens decentralized health data integrity and immutable transaction traceability at the corresponding data-element level in a privacy-preserving fashion. A crypto-economy ecosystem was built to facilitate secure and traceable exchanges of sensitive health data. Methods The Health Avatar Platform decentralizes patient data in appropriate locations (ie, on patients’ smartphones and on physicians’ smart devices). We implemented an Ethereum-based hash chain for all transactions and smart contract–based processes to guarantee decentralized data integrity and to generate block data containing transaction metadata on-chain. Parameters of all types of data communications were enumerated and incorporated into 3 smart contracts, in this case, a health data transaction manager, a transaction status manager, and an application programming interface transaction manager. The actual decentralized health data are managed in an off-chain manner on appropriate smart devices and authenticated by hashed metadata on-chain. Results Metadata of each data transaction are captured in a Health Avatar Platform blockchain node by the smart contracts. We provide workflow diagrams each of the 3 use cases of data push (from a physician app or an intelligent agents to a patient Avatar), data pull (request to a patient Avatar by other entities), and data backup transactions. Each transaction can be finely managed at the corresponding data-element level rather than at the resource or document levels. Hash-chained metadata support data element–level verification of data integrity in subsequent transactions. Smart contracts can incentivize transactions for data sharing and intelligent digital health care services. Conclusions Health Avatar Platform and interconnected patient Avatars, physician apps, and intelligent agents provide a decentralized blockchain ecosystem for health data that enables trusted and finely tuned data sharing and facilitates health value-creating transactions with smart contracts.

The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework leverages existing Community Coordinated Modeling Center services: Run on Request post processing tools that generate model time series outputs and the new Community Coordinated Modeling Center Metadata Registry that describes simulation runs using Space Physics Archive Search and Extract metadata. The new CAMEL visualization tool compares the modeled time series with observational data and computes a suite of skill scores such as Prediction Efficiency, Root Mean Square Error, and Symmetric Signed Percentage Bias. Model data pairs used for skill calculations are obtained considering a user selected maximum difference between the time of observation and the nearest model output. The system renders available data for all locations and time periods selected using interactive visualizations that allow the user to zoom, pan, and pick data values along traces. Skill scores are reported for each selected event or aggregated over all events for all participating model runs. Separately, scores are reported for all locations (satellites or stations) and for each location individually. We are building on past experiences with model data comparisons of magnetosphere and ionosphere model outputs from GEM2008, GEMCEDAR Electrodynamics Thermosphere Ionosphere, and the SWPC Operational Space Weather Model challenges. The CAMEL visualization tool is demonstrated using three validation studies: (a) Wang Sheeley Arge heliosphere simulations compared against OMNI solar wind data, (b) ground magnetic perturbations from several magnetosphere and ionosphere electrodynamics models as observed by magnetometers, and (c) electron fluxes from several ring current simulations compared to Radiation Belt Storm Probes Helium Oxygen Proton Electron instrument measurements, integrated over different energy ranges.

Background Semantic interoperability is essential for improving data quality and sharing. The ISO/IEC 11179 Metadata Registry (MDR) standard has been highlighted as a solution for standardizing and registering clinical data elements (DEs). However, the standard model has both structural and semantic limitations, and the number of DEs continues to increase due to poor term reusability. Semantic types and constraints are lacking for comprehensively describing and evaluating DEs on real-world clinical documents. Methods We addressed these limitations by defining three new types of semantic relationship (dependency, composite, and variable) in our previous studies. The present study created new and further extended existing semantic types (hybrid atomic and repeated and dictionary composite common data elements [CDEs]) with four constraints: ordered, operated, required, and dependent. For evaluation, we extracted all atomic and composite CDEs from five major clinical documents from five teaching hospitals in Korea, 14 Fast Healthcare Interoperability Resources (FHIR) resources from FHIR bulk sample data, and MIMIC-III (Medical Information Mart for Intensive Care) demo dataset. Metadata reusability and semantic interoperability in real clinical settings were comprehensively evaluated by applying the CDEs with our extended semantic types and constraints. Results All of the CDEs (n = 1142) extracted from the 25 clinical documents were successfully integrated with a very high CDE reuse ratio (46.9%) into 586 CDEs (259 atomic and 20 unique composite CDEs), and all of CDEs (n = 238) extracted from the 14 FHIR resources of FHIR bulk sample data were successfully integrated with high CDE reuse ration (59.7%) into 96 CDEs (21 atomic and 28 unique composite CDEs), which improved the semantic integrity and interoperability without any semantic loss. Moreover, the most complex data structures from two CDE projects were successfully encoded with rich semantics and semantic integrity. Conclusion MDR-based extended semantic types and constraints can facilitate comprehensive representation of clinical documents with rich semantics, and improved semantic interoperability without semantic loss.

For the successful development of the astrophysics and, accordingly, for obtaining more complete knowledge of the Universe, it is extremely important to combine and comprehensively analyze information of various types (e.g., about charged cosmic particles, gamma rays, neutrinos, etc.) obtained by using divers large-scale experimental setups located throughout the world. It is obvious that all kinds of activities must be performed continually across all stages of the data life cycle to help support effective data management, in particular, the collection and storage of data, its processing and analysis, refining the physical model, making preparations for publication, and data reprocessing taking refinement into account. In this paper we present a general approach to construction and the architecture of a system to be able to collect, store, and provide users' access to astrophysical data. We also suggest a new approach to the construction of a metadata registry based on the blockchain technology., Comment: 11 pages, 2 figures

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An intelligent mobile augmented reality (IMAR) can be a useful scheme when users want get additional information about products or objects in a store. One of the problems to be resolved in the service is how to manage huge number of augmented objects. One of the approaches is to separate object's metadata from real objects. By doing this, we can reduce amount of storage and object searching time. However, to apply such scheme seamlessly, we have to well organize each object's metadata and store them efficiently. To do this, this paper present a scheme that is based on metadata registry (MDR). In the scheme, all objects are organized in the ways specified by MDR standards.

A smart greenhouse monitors the internal and external context information of the greenhouse in real time and keeps the internal environment in an optimal condition for the growth of crops. In this paper, we propose a smart greenhouse system based on MAPE-K that can automatically control the greenhouse. All information of the proposed system is stored and managed through an ontology knowledge repository based on ISO-IEC 11179 (metadata registry, MDR). Furthermore, we design a low cost smart greenhouse by interoperating the smart devices.

Over the past years, efforts have been made by the NSDI to re-engineer the geospatial feature data sets and compile and serve their metadata as per ISO/OGC specifications. These are required for provision of interoperable geospatial data services in a service-oriented architecture and automated development of GIS applications. Identification, registration and maintenance of metadata of the feature data sets and related services from the national- and state-level partnering agencies in a central metadata registry, called the National Data Registry (NDR), are essential for improving data utilization. Registering spatial data sets and services may typically involve capturing their semantics (definition), making each data item persistently and uniquely identifiable by assigning unique identifiers and organizing/maintaining their schema and associated classification systems (code lists) in a set of standard registers. In line with these requirements, a proof-of-concept (PoC) of a National Data Registry (NDR) for the Indian NSDI has been implemented and demonstrated using data services from Survey of India, National Remote Sensing Centre and the Ministry of Railways’ train running information. The PoC successfully demonstrated the utility of a sample registry and technical architecture and led to the development of a strategy for selection of a suitable system integrator for a real-life NDR development for the NSDI.

The management of vocabularies in the evolving linked data environment requires different tools and processes from those libraries and other memory institutions have used in the past. The RDA (Resource Description and Access) standard has taken the lead in building tools and providing services as part of its RDA Registry development. The evolution of the current RDA Registry and the Open Metadata Registry (OMR), on which the RDA Registry is built, are described, including the rationale for directions, decisions, and ongoing development.

The ISO/IEC 11179 Metadata registry (MDR) is an international standard that was developed to register and share metadata. ISO/IEC 11179 represents an MDR as a metamodel that is an object model. However, it is difficult to develop an MDR based on ISO/IEC 11179 because the standard has no clear criteria to transform the metamodel into a database. In this paper, we suggest the design of an MDR data model that is based on object-relational transformation methodology (ORTM) for the MDR implementation. Hence, we classify the transformation methods of ORTM according to the corresponding relationships. After classification, we propose modeling rules by defining the standard use of the transformation. This paper builds the relational database tables as an implementation result of an MDR data model. Through experiments and evaluation, we verify the proposed modeling rules and evaluate the suitability of the created table structures. As the result, the proposed method shows that the table structures preserve classes and relationships of the standard metamodel well.

Ontology integration carries significant importance in terms of reuse of knowledge and interoperability. In this paper, a framework for ontology integration based on extended metadata registry plus (XMDR+) is focused, that is, we try to developer a methods for ontology integration to provide high quality Semantic Web services. To sum up, the ontology integration framework proposed herein not only produces global ontologies; but also defines such methods, and, thereby, performs better in extending and integrating ontologies. The framework will rely on a model independent of ontology storage structures, but will be capable of representing semantic relationships between different ontology systems.

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

Objectives Extension of the standard model while retaining compliance with it is a challenging issue because there is currently no method for semantically or syntactically verifying an extended data model. A metadata-based extended model, named CCR+, was designed and implemented to achieve interoperability between standard and extended models. Methods Furthermore, a multilayered validation method was devised to validate the standard and extended models. The American Society for Testing and Materials (ASTM) Community Care Record (CCR) standard was selected to evaluate the CCR+ model; two CCR and one CCR+ XML files were evaluated. Results In total, 188 metadata were extracted from the ASTM CCR standard; these metadata are semantically interconnected and registered in the metadata registry. An extended-data-model-specific validation file was generated from these metadata. This file can be used in a smartphone application (Health Avatar CCR+) as a part of a multilayered validation. The new CCR+ model was successfully evaluated via a patient-centric exchange scenario involving multiple hospitals, with the results supporting both syntactic and semantic interoperability between the standard CCR and extended, CCR+, model. Conclusions A feasible method for delivering an extended model that complies with the standard model is presented herein. There is a great need to extend static standard models such as the ASTM CCR in various domains: the methods presented here represent an important reference for achieving interoperability between standard and extended models.

With the increasing adoption of Electronic Health Records (EHR), the amount of data produced at the patient bedside is rapidly increasing. Secondary use is there by an important field to investigate in order facilitate research and evaluation. In these work we discussed issues related to data representation and semantics within EHR that need to be address in order to facilitate secondary of structured data in oncology. We propose and evaluate ontology based methods for heterogeneous diagnosis terminologies integration in oncology. We then extend obtained model to enable tumoral disease representation and links with diagnosis as recorded in EHR. We then propose and implement a complete architecture combining a clinical data warehouse, a metadata registry and web semantic technologies and standards. This architecture enables syntactic and semantic integration of a broad range of hospital information System observation. Our approach links data with external knowledge (ontology), in order to provide a knowledge resource for an algorithm for tumoral disease identification based on diagnosis recorded within EHRs. As it based on the ontology classes, the identification algorithm is uses an integrated view of diagnosis (avoiding semantic heterogeneity). The proposed architecture leading to algorithm on the top of an ontology offers a flexible solution. Adapting the ontology, modifying for instance the granularity provide a way for adapting aggregation depending on specific needs, Avec la montée en charge de l’informatisation des systèmes d’information hospitaliers, une quantité croissante de données est produite tout au long de la prise en charge des patients. L’utilisation secondaire de ces données constitue un enjeu essentiel pour la recherche ou l’évaluation en santé. Dans le cadre de cette thèse, nous discutons les verrous liés à la représentation et à la sémantique des données, qui limitent leur utilisation secondaire en cancérologie. Nous proposons des méthodes basées sur des ontologies pour l’intégration sémantique des données de diagnostics. En effet, ces données sont représentées par des terminologies hétérogènes. Nous étendons les modèles obtenus pour la représentation de la maladie tumorale, et les liens qui existent avec les diagnostics. Enfin, nous proposons une architecture combinant entrepôts de données, registres de métadonnées et web sémantique. L’architecture proposée permet l’intégration syntaxique et sémantique d’un grand nombre d’observations. Par ailleurs, l’intégration de données et de connaissances (sous la forme d’ontologies) a été utilisée pour construire un algorithme d’identification de la maladie tumorale en fonction des diagnostics présents dans les données de prise en charge. Cet algorithme basé sur les classes de l’ontologie est indépendant des données effectivement enregistrées. Ainsi, il fait abstraction du caractère hétérogène des données diagnostiques initialement disponibles. L’approche basée sur une ontologie pour l’identification de la maladie tumorale, permet une adaptation rapide des règles d’agrégation en fonction des besoins spécifiques d’identification. Ainsi, plusieurs versions du modèle d’identification peuvent être utilisées avec des granularités différentes.

Recently, user demands for integrated searches over different information sources have been increasing rapidly. However, it is not easy to seamlessly integrate distributed heterogeneous information retrieval systems. In particular, resolving the discrepancies in the structures and semantics in the databases that are to be integrated is one of the most challenging research issues. In this paper, we propose an iKRISTAL system that integrates distributed, heterogeneous information retrieval systems without requiring source code-level modifications of the participating systems. The key element of our approach to address the structural and semantic discrepancies is to make use of schema mapping and a standardized framework for metadata registry. We have implemented and deployed a prototype implementation that integrates six different information sources, each of which is built upon heterogeneous schemas. Furthermore, we evaluated the performance of our approach under various configurations.

In order to support empirical medical research concerning reuse and improvement of the expressiveness of study data and hence promote syntactic as well as semantic interoperability, services are required for the maintenance of data element collections. As part of the project for the implementation of a German metadata repository for empirical research we assessed the ability of ISO/IEC 11179 “Information technology – Metadata registries (MDR)” part 3 edition 3 Final Committee Draft “Registry metamodel and basic attributes” to represent healthcare standards. First step of the evaluation was a reformulation of ISO’s metamodel with the terms and structures of the different healthcare standards. In a second step, we imported instances of the healthcare standards into a prototypical database implementation representing ISO’s metamodel. Whereas the flat structure of disease registries as well as some controlled vocabularies could be easily mapped to the ISO’s metamodel, complex structures as used in reference models of electronic health records or classifications could be not exhaustively represented. A logical reconstruction of an application will be needed in order to represent them adequately. Moreover, the correct linkage between elements from ISO/IEC 11179 edition 3 and concepts of classifications remains unclear. We also observed some restrictions of ISO/IEC 11179 edition 3 concerning the representation of items of the Operational Data Model from the Clinical Data Interchange Standards Consortium, which might be outside the scope of a MDR. Thus, despite the obvious strength of the ISO/IEC 11179 edition 3 for metadata registries, some issues should be considered in its further development.

Metadata registry (MDR) is the international standard, developed by ISO/IEC for exchange and sharing data between databases. Many MDR systems are used in diverse domains such as medical service, bibliography, environment for sharing and integrating data. However, those systems have different physical structures individually because the MDR standard defines only the metamodel for registering and storing metadata. It causes heterogeneity between the system structures and requires additional cost to maintain interoperability. ISO/IEC 13249-8 Metadata Registry Access (MRA) is developing as an international standard to provide a consistent access facility to data stored in different metadata registries. However, MRA does not consider the relationships between the concepts (classes) defined in the MDR specification. It causes that incorrect query results returned from MDR systems. It also requires additional cost of modeling and rewriting queries to reflect each physical model. Therefore, this paper suggests eMRA which considers the relationships between the concepts in MDR. The comparative evaluations are described to show the advantages of eMRA. eMRA has superior performance in query modeling and referential integrity than MRA defined by the relationship between the concept of MDR.

Rankraščių rinkiniai – tai labai įvairaus pobūdžio rankraščiai, paprastai apibrėžiami kaip „ranka ant popieriaus arba pergamento užrašytas tekstas arba dokumentas“ (Peter Beal). Tai gali būti šeimos ar asmeniniai dokumentai, dienoraščiai, laiškai, archyvų rinkiniai ir kt. Viduramžių rankraščiai – kodeksai, žemėlapiai, muzikos kūriniai arba jų fragmentai – sudaro specialią rankraš­čių rūšį. Kaip ir inkunabulai, rankraščių rinkiniai yra vertingiausia bibliotekų paveldo dalis, dėl jų mus pasiekia itin daug informacijos apie viduramžių istoriją, kultūrą, literatūrą, socialinę istoriją, gyvenimo tendencijas. Be šių šaltinių informacija būtų dingusi. Senų ir retų rankraščių tyri­mai svarbūs tiek šalies, tiek visos Europos kultūros ir socialinei istorijai. Žvelgiant iš humanitarinių mokslų perspektyvos, būtina išskirti keletą veiksnių, kurie lėmė reikšmingus pokyčius tyrinėjant rankraščius ir pirmąsias spausdintines knygas. Pa­čiu svarbiausiu laikomas informacinių technologijų poveikis beveik visoms tyrimo sritims. Šie pokyčiai lėmė ir naujos disciplinos – skaitmeninių humanitarinių mokslų atsiradimą. Pasak Toby’o Burrowso, viduramžių tyrinėtojai yra „pažangiausi skaitmeninių technologi­jų taikymo humanitarinių mokslų tyrimuose atstovai“. Vis dėlto T. Burrowsas išskiria ir keletą keblumų, susijusių su interneto ir skaitmeninės bibliotekos paslaugomis. Jis nurodo „integracijos ir sąveikos tarp daugybės skirtingų interneto svetainių stygių“ bei terminolo­gijos nenuoseklumą taikant aprašomuosius standartus. Savo ruožtu tai sukelia probleminę situaciją, nes „tyrinėtojams visame pasaulyje kyla daug sunkumų rasti, naudotis ir dalytis žiniomis apie viduramžių rankraščių kolekcijas“. Visiškai pritariame T. Burrowso minčiai, kad šią problemą galima išspręsti sukuriant tarptautinę bendradarbiavimo infrastruktūrą, kuri leistų tvarkyti turinį ir tarpusavyje susijusias žinias. Mūsų nuomone, ši infrastuktūra gali būti įgyvendinta technologinėje semantinio žiniatinklio ir sujungtų atvirų duomenų (angl. Semantic Web and Linked Open Data) terpėje. Straipsnyje aptariami viduramžių rankraščių ir inkunabulų bei jų fragmentų tyrimai ir šių šal­tinių aprašymas kaip skaitmeninių humanitarinių mokslų projekto dalis, taikant šią naują tech­nologiją. Nagrinėjamas šios srities Kroatijos Zadaro universiteto Informacijos mokslų fakulteto vykdomas mokslinių tyrimų projektas. Projekto tikslas – atrinkti duomenų elementus, reikalingus tiksliam minėtų šaltinių aprašymui ir jų standartizavimui, naudojant senų ir retų knygų tyrinėtojų parengtas bibliografijos, kodikologijos, paleografijos bei tipografijos ontologijas.Straipsnyje pateikiamas ir trumpas technologinės semantinio tinklo infrastruktūros bei jo standartų įvadas. Detaliai aprašoma metodika, padedanti paskelbti pasirinktą žodyną kaip vieną iš metaduomenų registro paslaugų. Pateikiamas sujungtų atvirų duomenų paskelbimo pavyzdys – pri­statatomas grafikas, vaizduojantis iš dalies rekonstruoto rankraščio fragmento aprašymą. Kadangi visos minėtos disciplinos naudoja savo žodynus ir ontologijas, straipsnio autorės siūlo orientuotis ne į vieno bendro žodyno naudojimą, o į atitinkamų terminų sąsajų projektavimą vadovaujantis SKOS taisyklėmis. Taip būtų kuriami būsimos tarptautinės bendradarbiavimo struktūros pagrindai.

Background Clinical trials use many case report forms (CRFs) per patient. Because of the astronomical number of potential CRFs, data element re-use at the design stage is attractive to foster compatibility of data from different trials. The objective of this work is to assess the technical feasibility of a CRF editor with connection to a public metadata registry (MDR) to support data element re-use. Results Based on the Medical Data Models portal, an ISO/IEC 11179-compliant MDR was implemented and connected to a web-based CRF editor. Three use cases were implemented: re-use at the form, item group and data element levels. Conclusions CRF design with data element re-use from a public MDR is feasible. A prototypic system is available. The main limitation of the system is the amount of available MDR content.

OntoSoft is a distributed semantic registry for scientific software. This paper describes three major novel contributions of OntoSoft: 1) a software metadata registry designed for scientists, 2) a distributed approach to software registries that targets communities of interest, and 3) metadata crowdsourcing through access control. Software metadata is organized using the OntoSoft ontology along six dimensions that matter to scientists: identify software, understand and assess software, execute software, get support for the software, do research with the software, and update the software. OntoSoft is a distributed registry where each site is owned and maintained by a community of interest, with a distributed semantic query capability that allows users to search across all sites. The registry has metadata crowdsourcing capabilities, supported through access control so that software authors can allow others to expand on specific metadata properties.

ISO/IEC-11179 is an international standard that documents the standardization and registration of metadata to make data understandable and shareable. This standardization and registration allows for easier locating, retrieving, and transmitting data from disparate databases. The standard defines the how metadata are conceptually modeled and how they are shared among parties, but does not define how data is physically represented as bits and bytes. The standard consists of six parts. Part 1 provides a high-level overview of the standard and defines the basic element of a metadata registry - a data element. Part 2 defines the procedures for registering classification schemes and classifying administered items in a metadata registry (MDR). Part 3 specifies the structure of an MDR. Part 4 specifies requirements and recommendations for constructing definitions for data and metadata. Part 5 defines how administered items are named and identified. Part 6 defines how administered items are registered and assigned an identifier.

In healthcare domain there is a plethora of health information but no mechanism of satisfying customized users' requirements and providing demand oriented information. Healthcare domain is facing challenge of finding healthcare information that meets user requirements. Semantics can provide interoperable, automated and seamlessly meaningful communication for healthcare domain. Healthcare information is increasing with the increase of medical databases over the internet. In this matter provision of right information to appropriate users over the web is a great challenge. Semantic web technologies can address this issue by ensuring extensible, flexible and efficient information discovery related to diseases and clinical processes. We implemented a semantic registry that is a service registry as well as metadata registry. It manages and secures healthcare information and processes in a consistent way in compliance with emerging international standards and technical specifications. We evaluated our system through Patient Registration Scenario implemented semantically in our OWL- S framework.

This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

Metadata registry (MDR) is based on the international standard ISO/IEC 11179. The committee of ISO/IEC JTC 1/SC 32, which had standardized the MDR, has started to improvise the MDR, and the improvised version is named extended MDR (XMDR). However, the XMDR does not fully support the ontology concept, and no method is available for mapping ontology registrations onto registries. To overcome the limitations of the outdated XMDR, this paper proposes an extended XMDR (XMDR+) framework. The XMDR+ framework provides a method for mapping of ontology registrations between the metadata registry and ontologies. To improve the functions of the XMDR, we have proposed herein a framework that is capable of defining a model that manages the relations not only among ontological concepts but also among instances, and guarantees the management and storage of their relationships for supporting valid relations of the ontologies.