Metadata Repository Research Articles

Infrastructures and services for remote sensing data production management across multiple satellite data centers

With the number of satellite sensors and date centers being increased continuously, it is becoming a trend to manage and process massive remote sensing data from multiple distributed sources. However, the combination of multiple satellite data centers for massive remote sensing (RS) data collaborative processing still faces many challenges. In order to reduce the huge amounts of data migration and improve the efficiency of multi-datacenter collaborative process, this paper presents the infrastructures and services of the data management as well as workflow management for massive remote sensing data production. A dynamic data scheduling strategy was employed to reduce the duplication of data request and data processing. And by combining the remote sensing spatial metadata repositories and Gfarm grid file system, the unified management of the raw data, intermediate products and final products were achieved in the co-processing. In addition, multi-level task order repositories and workflow templates were used to construct the production workflow automatically. With the help of specific heuristic scheduling rules, the production tasks were executed quickly. Ultimately, the Multi-datacenter Collaborative Process System (MDCPS) were implemented for large-scale remote sensing data production based on the effective management of data and workflow. As a consequence, the performance of MDCPS in experiments environment showed that those strategies could significantly enhance the efficiency of co-processing across multiple data centers.

Reasoning on Constraints for Incoherent Operations in Metadata Repository Systems

Reasoning on Constraints for Incoherent Operations in Metadata Repository Systems

A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution.

This study describes our efforts in developing a standards-based semantic metadata repository for supporting electronic health record (EHR)-driven phenotype authoring and execution. Our system comprises three layers: 1) a semantic data element repository layer; 2) a semantic services layer; and 3) a phenotype application layer. In a prototype implementation, we developed the repository and services through integrating the data elements from both Quality Data Model (QDM) and HL7 Fast Healthcare Inteoroperability Resources (FHIR) models. We discuss the modeling challenges and the potential of our system to support EHR phenotype authoring and execution applications.

Herding Linked Data: Semantic Search and Navigation Among Scholarly Datasets

Linked Data seem to play a seminal role in the establishment of the Semantic Web as the next-generation Web. This is even more important for digital object collections and educational institutions that aim not only at promoting and disseminating their content but also at aiding its discoverability and contextualization. In this paper we show how repository metadata can be exposed as Linked Data, thus enhancing their machine understandability and contributing to the LOD cloud. We use a popular digital repository system, namely DSpace, as our deployment platform. Without requiring additional annotations that would harden the curation task, educational resources are semantically enhanced by reusing and transforming existing metadata values. Our effort comes complete with an updated UI that allows for reasoning-based search and navigation between linked resources within and outside the scope of the digital repository. Therefore ontological descriptions of resources can now be accessed from within the repository’s core context, linked from outside datasets, link to external datasets and get discovered by semantic search.

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world.

A Geospatial Semantic Enrichment and Query Service for Geotagged Photographs.

With the increasing abundance of technologies and smart devices, equipped with a multitude of sensors for sensing the environment around them, information creation and consumption has now become effortless. This, in particular, is the case for photographs with vast amounts being created and shared every day. For example, at the time of this writing, Instagram users upload 70 million photographs a day. Nevertheless, it still remains a challenge to discover the “right” information for the appropriate purpose. This paper describes an approach to create semantic geospatial metadata for photographs, which can facilitate photograph search and discovery. To achieve this we have developed and implemented a semantic geospatial data model by which a photograph can be enrich with geospatial metadata extracted from several geospatial data sources based on the raw low-level geo-metadata from a smartphone photograph. We present the details of our method and implementation for searching and querying the semantic geospatial metadata repository to enable a user or third party system to find the information they are looking for.

Managing Serials Data as a Community: Partnering With the Global Open Knowledgebase (GOKb)

The Global Open Knowledgebase (GOKb) is a project to develop and maintain a freely available repository of metadata that describes electronic journals and books using a community-managed approach. In preparation for GOKb's public preview at the end of 2014, the North Carolina State University (NCSU) Libraries launched a pilot to create a partnership model for participating libraries. Based on a presentation at the 2015 North Carolina Serials Conference, Eric Hanson, Xiaoyan Song, and Kristen Wilson from NCSU Libraries share their experiences partnering with GOKb, including the workflows and tools that NCSU has established for contributing to GOKb, opportunities for library and vendor partners, and GOKb's linked data service.

The center for expanded data annotation and retrieval.

The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments.

UML 메타모델링과 모델의 변환을 통한 전자정부 표준 프레임워크 기반의 코드 생성 자동화

Abstract In the process of extending the UML model for a various domain, comply with the UML metamodel andit is possible to obtain a number of advantages. However, the UML metamodel is necessary to redefine the diagrammust be defined via the Profile in order to expand and transformation the UML metamodel from a variety of sourcesusing the UML metamodel is becoming increase massive scale. it is necessary to use only those extracts the elementrelative to the target to be used to extend a UML metamodel. Used to re-define the extension of the UML Metamodeland Profile based UML modeling tools and metadata repositories by analysis tools, can develop more quickly and easily, by utilizing these tools can improve the quality of development in the SW industry. In this paper, we present an algorithm that of the profile through the expansion of the UML metamodel and shows the results in actually applying e-government standards framework. Key Words : Meta Model, UML, SW Quality, MDD, Electronic government standard framework

A Linked Dataset of medical educational resources

AbstractReusable educational resources became increasingly important for enhancing learning and teaching experiences, particularly in the medical domain where resources are particularly expensive to produce. While interoperability across educational resources metadata repositories is yet limited to the heterogeneity of metadata standards and interface mechanisms with a lack of shared or aligned controlled vocabularies, Linked Data (LD) principles, based on W3C standards and supported through a wide range of tools, open up opportunities to alleviate such problems. We introduce the “mEducator Linked Educational Resources” dataset, which offers a range of open educational resources for the medical domain, exposed through LD principles. Data have been generated through a combination of manual curation and semi‐automated harvesting techniques, and state‐of‐the‐art enrichment and clustering techniques were deployed in order to classify and categorize data, toward improved reusability and access. Data are currently used by a range of educational applications and is accessible for third parties and developers, for instance through the LinkedUp Catalog and other registries, to facilitate further take‐up and applications.

Shared Geospatial Metadata Repository for Ontario University Libraries: Collaborative Approaches

Successfully providing access to special collections of digital geospatial data in academic libraries relies upon complete and accurate metadata. Creating and maintaining metadata using specialized standards is a formidable challenge for libraries. The Ontario Council of University Libraries’ Scholars GeoPortal project, which created a shared geospatial data infrastructure, involved centrally curating metadata for shared geospatial data collections, using a collaborative and cost-effective consortial model. This article presents the background and findings of the Scholars GeoPortal project. Through the development of advanced library systems and expertise, libraries in Ontario have improved discovery and access to geospatial data for researchers.

A Comparative Study of Descriptive Metadata in Audio Archives of IRIB Using the PBCore Metadata Standard

Abstract. Objective: The purpose of the present research was to compare the descriptive metadata of the audio archives of the Islamic Republic of Iran Broadcasting (IRIB) to the content classes of the PBCore metadata standard (i.e. Intellectual Content, Intellectual Property, Instantiation, and Extension). Methods: Using comparative survey, the tags of the PBCore metadata standard were extracted and translated. A checklist was also developed of fields classified under Intellectual Content, Intellectual Property, Instantiation, and Extension. Using these tags and fields the applications of each audio archive were compared to the PBCore metadata standard. Findings: The results indicated that the descriptive metadata of IRIB’s audio archives conforms to the PBCore metadata standard by 63 percent. The results also showed that audio archives conformed to the PBCore standard in terms of intellectual content, intellectual property, and instantiation, but not in terms of extension. This could be because storage and retrieval experts at IRIB focus primarily on domestic demands and ignore international standards. The results also suggest that the PBCore metadata standard can be used to describe the archives of IRIB for storage and retrieval. Conclusion: Overall, the results indicated the conformity of the audio archives of IRIB to the PBCore metadata standard. However, extensions are needed in the web, intranet, and internet to provide a repository for metadata from external systems. This will also allow for integration and standardization in converting and creating metadata for transfer between IRIB centers and foreign archives.

Metadata Repositories in Database-driven Information Systems

Abstract Database-driven information systems provide, by definition, a good level of integration for the various data representations corresponding to heterogeneous information requirements, generated by users with different business perspectives. However, current technologies provide little support for the integration of the system specifications. This paper identifies the key factors which contribute to the semantic integration of the information system metadata, and proposes a possible architecture for an integrated metadata repository.

A Graph-based Approach to Key Variable Mapping

This paper describes the Key Variable Mapping System (KVMS) - a metadata repository, and tools for carrying out disclosure risk assessments. The KVMS repository contains metadata relating to the collection instruments used to populate private databases, and partition graphs for encoding possibilities for record matching. Analyses are conducted to assist in the identification of key variables. The data entry system used to populate the repository is described, along with details of the data structures and algorithms used to query the repository and generate a particular form of analysis. KVMS provides a framework for disclosure risk analyses that depend on a prevailing data environment.

Enhancing an Open-Access Linguistics Journal Archive with Library of Congress-like Metadata: A Case Study of the Effectiveness for Improving Discovery

The University of Kansas has hosted the Kansas Working Papers in Linguistic (KWPL) in its digital repository, KU ScholarWorks, since 2007, but complete subject metadata, based on Library of Congress Subject Headings, was added only in 2013. The purpose of this study was to determine the efficacy of adding Library of Congress subject headings in enhancing discoverability and increasing downloads. Results have provided compelling evidence that the additional metadata has led to an overall increase of downloads from KWPL by 66% in the year following the addition of the enhanced metadata.

Exposing scholarly information as Linked Open Data: RDFizing DSpace contents

Purpose – This paper aims to introduce a transformation engine which can be used to convert an existing institutional repository installation into a Linked Open Data repository. Design/methodology/approach – The authors describe how the data that exist in a DSpace repository can be semantically annotated to serve as a Semantic Web (meta)data repository. Findings – The authors present a non-intrusive, standards-compliant approach that can run alongside with current practices, while incorporating state-of-the art methodologies. Originality/value – Also, they propose a set of mappings between domain vocabularies that can be (re)used towards this goal, thus offering an approach that covers both the technical and semantic aspects of the procedure.

A semantically enabled metadata repository for scientific data

The LASP Extended Metadata Repository (LEMR) is a semantically enabled repository of information (metadata) about the scientific datasets that LASP offers to the public. The repository enables the provision of consistent, current, verified metadata to our users. It serves as a Single Source of Truth for this information, enabling more rigorous metadata management and addressing problems related to duplication of information. The linked open data aspect of the repository allows interlinking of concepts both within and across organizations and web sites. Associated interfaces allow users to browse and search the metadata. This information can be dynamically incorporated into web pages, so web page content is always up-to-date and consistent across the lab. With this information we can generate metadata records in a variety of schemas, such as ISO or SPASE, allowing federation with other organizations interested in our data. We leveraged open source technologies to build the repository and the dynamic web pages that read from it. VIVO, an open source semantic web application, provided key capabilities such as ontology and triple store management interfaces. AngularJS, an open source JavaScript framework for building web dynamic applications, was also invaluable in developing web pages that provide semantically enabled public interfaces to the metadata. In this paper we discuss our use of these tools and what we had to craft in order to meet our lab-specific needs.

A case study on propagating and updating provenance information using the CIDOC CRM

Provenance information of digital objects maintained by digital libraries and archives is crucial for authenticity assessment, reproducibility and accountability. Such information is commonly stored on metadata placed in various Metadata Repositories (MRs) or Knowledge Bases (KBs). Nevertheless, in various settings it is prohibitive to store the provenance of each digital object due to the high storage space requirements that are needed for having complete provenance. In this paper, we introduce provenance-based inference rules as a means to complete the provenance information, to reduce the amount of provenance information that has to be stored, and to ease quality control (e.g., corrections). Roughly, we show how provenance information can be propagated by identifying a number of basic inference rules over a core conceptual model for representing provenance. The propagation of provenance concerns fundamental modelling concepts such as actors, activities, events, devices and information objects, and their associations. However, since a MR/KB is not static but changes over time due to several factors, the question that arises is how we can satisfy update requests while still supporting the aforementioned inference rules. Towards this end, we elaborate on the specification of the required add/delete operations, consider two different semantics for deletion of information, and provide the corresponding update algorithms. Finally, we report extensive comparative results for different repository policies regarding the derivation of new knowledge, in datasets containing up to one million RDF triples. The results allow us to understand the tradeoffs related to the use of inference rules on storage space and performance of queries and updates.

Information technology for clinical, translational and comparative effectiveness research. Findings from the section clinical research informatics.

To select and summarize key contributions to current research in the field of Clinical Research Informatics (CRI). A bibliographic search using a combination of MeSH and free terms search over PubMed was performed followed by a blinded review. The review process resulted in the selection of four papers illustrating various aspects of current research efforts in the area of CRI. The first paper tackles the challenge of extracting accurate phenotypes from Electronic Healthcare Records (EHRs). Privacy protection within shared de-identified, patient-level research databases is the focus of the second selected paper. Two other papers exemplify the growing role of formal representation of clinical data - in metadata repositories - and knowledge - in ontologies - for supporting the process of reusing data for clinical research. The selected articles demonstrate how concrete platforms are currently achieving interoperability across clinical research and care domains and have reached the evaluation phase. When EHRs linked to genetic data have the potential to shift the research focus from research driven patient recruitment to phenotyping in large population, a key issue is to lower patient re-identification risks for biomedical research databases. Current research illustrates the potential of knowledge engineering to support, in the coming years, the scientific lifecycle of clinical research.

Sensor-Based Architecture for Medical Imaging Workflow Analysis

The growing use of computer systems in medical institutions has been generating a tremendous quantity of data. While these data have a critical role in assisting physicians in the clinical practice, the information that can be extracted goes far beyond this utilization. This article proposes a platform capable of assembling multiple data sources within a medical imaging laboratory, through a network of intelligent sensors. The proposed integration framework follows a SOA hybrid architecture based on an information sensor network, capable of collecting information from several sources in medical imaging laboratories. Currently, the system supports three types of sensors: DICOM repository meta-data, network workflows and examination reports. Each sensor is responsible for converting unstructured information from data sources into a common format that will then be semantically indexed in the framework engine. The platform was deployed in the Cardiology department of a central hospital, allowing identification of processes' characteristics and users' behaviours that were unknown before the utilization of this solution.