364 research outputs found

    Experiences in deploying metadata analysis tools for institutional repositories

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    Current institutional repository software provides few tools to help metadata librarians understand and analyze their collections. In this article, we compare and contrast metadata analysis tools that were developed simultaneously, but independently, at two New Zealand institutions during a period of national investment in research repositories: the Metadata Analysis Tool (MAT) at The University of Waikato, and the Kiwi Research Information Service (KRIS) at the National Library of New Zealand. The tools have many similarities: they are convenient, online, on-demand services that harvest metadata using OAI-PMH; they were developed in response to feedback from repository administrators; and they both help pinpoint specific metadata errors as well as generating summary statistics. They also have significant differences: one is a dedicated tool wheres the other is part of a wider access tool; one gives a holistic view of the metadata whereas the other looks for specific problems; one seeks patterns in the data values whereas the other checks that those values conform to metadata standards. Both tools work in a complementary manner to existing Web-based administration tools. We have observed that discovery and correction of metadata errors can be quickly achieved by switching Web browser views from the analysis tool to the repository interface, and back. We summarize the findings from both tools' deployment into a checklist of requirements for metadata analysis tools

    Experiences in deploying metadata analysis tools for institutional repositories

    Get PDF
    Current institutional repository software provides few tools to help metadata librarians understand and analyze their collections. In this article, we compare and contrast metadata analysis tools that were developed simultaneously, but independently, at two New Zealand institutions during a period of national investment in research repositories: the Metadata Analysis Tool (MAT) at The University of Waikato, and the Kiwi Research Information Service (KRIS) at the National Library of New Zealand. The tools have many similarities: they are convenient, online, on-demand services that harvest metadata using OAI-PMH; they were developed in response to feedback from repository administrators; and they both help pinpoint specific metadata errors as well as generating summary statistics. They also have significant differences: one is a dedicated tool wheres the other is part of a wider access tool; one gives a holistic view of the metadata whereas the other looks for specific problems; one seeks patterns in the data values whereas the other checks that those values conform to metadata standards. Both tools work in a complementary manner to existing Web-based administration tools. We have observed that discovery and correction of metadata errors can be quickly achieved by switching Web browser views from the analysis tool to the repository interface, and back. We summarize the findings from both tools' deployment into a checklist of requirements for metadata analysis tools

    Beyond Harvesting: Digital Library Components as OAI Extensions

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    Reusability always has been a controversial topic in Digital Library (DL) design. While componentization has gained momentum in software engineering in general, there has not yet been broad DL standardization in component interfaces. Recently, the Open Archives Initiative (OAI) has begun to address this by creating a standard protocol for accessing metadata archives. It is proposed that this protocol be extended to act as the glue that binds together various components of a typical DL. In order to test the feasibility of this approach, a set of protocol extensions was created, implemented, and integrated as components of production and research DLs. The performance of these components was analyzed from the perspective of execution speed, network traffic, and data consistency. On the whole, this work has simultaneously revealed the feasibility of such OAI extensions for component interaction, and has identified aspects of the OAI protocol that constrain such extensions

    Lessons Learned with Arc, an OAI-PMH Service Provider

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    Web-based digital libraries have historically been built in isolation utilizing different technologies, protocols, and metadata. These differences hindered the development of digital library services that enable users to discover information from multiple libraries through a single unified interface. The Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) is a major, international effort to address technical interoperability among distributed repositories. Arc debuted in 2000 as the first end-user OAI-PMH service provider. Since that time, Arc has grown to include nearly 7,000,000 metadata records. Arc has been deployed in a number of environments and has served as the basis for many other OAI-PMH projects, including Archon, Kepler, NCSTRL, and DP9. In this article we review the history of OAI-PMH and Arc, as well as some of the lessons learned while developing Arc and related OAI-PMH services. Reprinted by permission of the publisher

    2017 DWH Long-Term Data Management Coordination Workshop Report

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    On June 7 and 8, 2017, the Coastal Response Research Center (CRRC)[1], NOAA Office of Response and Restoration (ORR) and NOAA National Marine Fisheries Service (NMFS) Restoration Center (RC), co-sponsored the Deepwater Horizon Oil Spill (DWH) Long Term Data Management (LTDM) workshop at the ORR Gulf of Mexico (GOM) Disaster Response Center (DRC) in Mobile, AL. There has been a focus on restoration planning, implementation and monitoring of the on-going DWH-related research in the wake of the DWH Natural Resource Damage Assessment (NRDA) settlement. This means that data management, accessibility, and distribution must be coordinated among various federal, state, local, non-governmental organizations (NGOs), academic, and private sector partners. The scope of DWH far exceeded any other spill in the U.S. with an immense amount of data (e.g., 100,000 environmental samples, 15 million publically available records) gathered during the response and damage assessment phases of the incident as well as data that continues to be produced from research and restoration efforts. The challenge with the influx in data is checking the quality, documenting data collection, storing data, integrating it into useful products, managing it and archiving it for long term use. In addition, data must be available to the public in an easily queried and accessible format. Answering questions regarding the success of the restoration efforts will be based on data generated for years to come. The data sets must be readily comparable, representative and complete; be collected using cross-cutting field protocols; be as interoperable as possible; meet standards for quality assurance/quality control (QA/QC); and be unhindered by conflicting or ambiguous terminology. During the data management process for the NOAA Natural Resource Damage Assessment (NRDA) for the DWH disaster, NOAA developed a data management warehouse and visualization system that will be used as a long term repository for accessing/archiving NRDA injury assessment data. This serves as a foundation for the restoration project planning and monitoring data for the next 15 or more years. The main impetus for this workshop was to facilitate public access to the DWH data collected and managed by all entities by developing linkages to or data exchanges among applicable GOM data management systems. There were 66 workshop participants (Appendix A) representing a variety of organizations who met at NOAA’s GOM Disaster Response Center (DRC) in order to determine the characteristics of a successful common operating picture for DWH data, to understand the systems that are currently in place to manage DWH data, and make the DWH data interoperable between data generators, users and managers. The external partners for these efforts include, but are not limited to the: RESTORE Council, Gulf of Mexico Research Initiative (GoMRI), Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), the National Academy of Sciences (NAS) Gulf Research Program, Gulf of Mexico Alliance (GOMA), and National Fish and Wildlife Foundation (NFWF). The workshop objectives were to: Foster collaboration among the GOM partners with respect to data management and integration for restoration planning, implementation and monitoring; Identify standards, protocols and guidance for LTDM being used by these partners for DWH NRDA, restoration, and public health efforts; Obtain feedback and identify next steps for the work completed by the Environmental Disasters Data Management (EDDM) Working Groups; and Work towards best practices on public distribution and access of this data. The workshop consisted of plenary presentations and breakout sessions. The workshop agenda (Appendix B) was developed by the organizing committee. The workshop presentations topics included: results of a pre-workshop survey, an overview of data generation, the uses of DWH long term data, an overview of LTDM, an overview of existing LTDM systems, an overview of data management standards/ protocols, results from the EDDM working groups, flow diagrams of existing data management systems, and a vision on managing big data. The breakout sessions included discussions of: issues/concerns for data stakeholders (e.g., data users, generators, managers), interoperability, ease of discovery/searchability, data access, data synthesis, data usability, and metadata/data documentation. [1] A list of acronyms is provided on Page 1 of this report

    A tool for metadata analysis

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    We describe a Web-based metadata quality tool that provides statistical descriptions and visualisations of Dublin Core metadata harvested via the OAI protocol. The lightweight nature of development allows it to be used to gather contextualized requirements and some initial user feedback is discussed

    A Comparison of Neuroelectrophysiology Databases

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    As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. These archives provide researchers with tools to store, share, and reanalyze neurophysiology data though the means of accomplishing these objectives differ. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. While many tools are available to reanalyze data on and off the archives' platforms, this article features Reproducible Analysis and Visualization of Intracranial EEG (RAVE) toolkit, developed specifically for the analysis of intracranial signal data and integrated with the discussed standards and archives. Neuroelectrophysiology data archives improve how researchers can aggregate, analyze, distribute, and parse these data, which can lead to more significant findings in neuroscience research.Comment: 25 pages, 8 figures, 1 tabl

    Leveraging OAI Harvesting to Disseminate Theses

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    NDLTD, the Networked Digital Library of Theses and Dissertations, supports and encourages the production and archiving of Electronic Theses and Dissertations (ETDs). While many current NDLTD member institutions and consortia have individual collections accessible online, there has until recently been no single mechanism to aggregate all ETDs to provide NDLTD-wide services (e.g., searching). With the emergence of the Open Archives Initiative (OAI), that has changed. The OAI’s Protocol for Metadata Harvesting is a robust interoperability solution that defines a standard method of exchanging metadata. While working with the OAI to develop and test the metadata harvesting standard, we have set up and actively maintain a central NDLTD metadata collection and multiple user portals. Member sites are encouraged to contribute to this central archive by supporting the OAI protocol, along with particular standards and conventions that have been specifically devised to support ETDs. We discuss in this article our experiences in building this distributed digital library based upon the work of the OAI
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