Metadata Catalog Research Articles

Reviewing the discoverability and accessibility to data and information products linked to Essential Climate Variables

ABSTRACTEssential Climate Variables (ECVs) are geophysical records generated from systematic Earth Observations associated with climate variations, changes, and impacts. ECVs products support the data and information needs of international frameworks and policies such as the work of the United Nations Framework Convention on Climate Change (UNFCCC) and the Intergovernmental Panel on Climate Change (IPCC). We map the main networks and initiatives publishing ECVs, by presenting an overview of existing satellite-based ECVs, their general data creation characteristics, discoverability and accessibility methods from an end-user perspective. We investigate key initiatives providing or coordinating access to ECV data records, such as the Global Climate Observing System (GCOS), the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS), Joint Working Group on Climate (WGClimate), the Remote Sensing Systems (REMSS), and the European Space Agency Climate Change Initiative (ESA CCI). We find that ECV data discovery and access is difficult and time consuming due to the lack of common data and metadata catalogues. In addition, the selection of fit-for-purpose data records by end-users requires the implementation of interoperable standards and scalable data infrastructures to allow the generation of tailored applications and data-driven information products in support of decision-making processes.

Mapping Cultural Heritage in Coastal Areas with UAS: The Case Study of Lesvos Island

Dynamic processes in coastal zones and human activities in the coastal environment produce pressure on cultural heritage, especially in touristic places. Unmanned aerial systems (UAS) are used as an additional tool for monitoring cultural heritage sites in sensitive coastal areas. UASs provide low-cost accurate spatial data and high-resolution imagery products in various spatial and temporal scales. The use of UAS for mapping cultural heritage sites in the coastal zone is of increasing interest among scientists and archaeologists in terms of monitoring, documentation, mapping, and restoration. This study outlines the integration of UAS data acquisition and structure from motion (SfM) pipeline for the visualization of selected cultural heritage areas (ancient harbors) in the coastal zone. The UAS-SfM methodology produces very detailed orthophoto maps for mapping and detecting cultural heritage sites. Additionally, a metadata cataloging system has been developed in order to facilitate online searching operations for all products of the data acquisition, SfM pipeline, and cartographic processes. For this reason, a specific metadata profile was implemented, based on the European INSPIRE framework. As a result, datasets reusability and catalogs interoperability are promoted.

The ATLAS Metadata Interface (AMI) 2.0 metadata ecosystem: new design principles and features

ATLAS Metadata Interface (AMI) is a generic ecosystem for metadata aggregation, transformation and cataloging. Benefiting from 18 years of feedback in the LHC context, the second major version was recently released. This paper describes the design choices and their benefits for providing high-level metadata-dedicated features. In particular, the Metadata Querying Language (MQL) - a domain-specific language allowing to query databases without knowing the relation between entities - and on the AMI Web framework are described.

IceCube File Catalog

IceCube is a cubic kilometer neutrino detector located at the south pole. Metadata for files in IceCube have traditionally been handled on an application by application basis, with no user-facing access. There has been no unified view of data files, and users often query the filesystem to locate files. Recently effort has been put into creating a unified view in a central metadata catalog. Going for a simple solution, we created a userfacing REST API backed by a NoSQL database. All major data producers add their metadata to this central catalog. Schema generation is identified as an important aspect of multi-application metadata services.

Требования к прототипу системы управления информационными ресурсами в распределенных информационных системах поддержки научных исследований

Описаны технологические подходы, применяемые для создания распределенных информационных систем поддержки научных исследований. Рассмотрены архитектурные решения, разработанные для создания таких систем и принципы интеграции этих систем с внешними источниками. Определены функциональные требования к модели такой информационной системы, которые обусловлены, во-первых, информационными потребностями исследователей, а во-вторых, необходимостью обеспечения надежного и долговременного хранения информации. Рассмотрены правила представления и преобразования метаданных. Описан и реализован прототип такой системы.The article addresses the description of technological approaches used to create distributed information systems for supporting scientific research. We describe the developed architectural solutions which are intended to create such systems and the principles for integrating of these systems with the external sources. The functional requirements for the model of such an information system are determined. These requirements are determined, firstly, by the information needs of researchers, and secondly, by ensuring a reliable and long-term storage of information. The considered model of SIS is implemented in the form of a prototype of the Electronic Library Management System (ELMS IRIS). ELMS IRIS operates with electronic collections. The electronic collection is considered as a set of information objects, united on a semantic basis and having the same structure (data schema). An ELMS allows to work with two types of collections which are the catalogs and the thesauri. The rules of representation and transformation of metadata are discussed. In order to organize metadata exchange between repositories and a metadata server (as well as with other systems with an extended profile), a special service is created that converts metadata from the internal schema into other metadata schemes. The OAI-PMH service is implemented, which periodically synchronizes the metadata of the repository and the metadata server in accordance with the schedule in batch mode. To fill the “Main metadata catalog”, in accordance with the metadata schemas created, managed dictionaries are used from the reference support block. To ensure data interoperability, the application server based on ZooPARK-ZS is also implemented, which provides access to system metadata via Z39.50 and SRW/SRU protocols. The developed model can be used as a model of the system for working with documents related to scientific and educational activities, since it solves the main tasks for these systems which are to provide a system for reliable long-term storage of digital (electronic) documents while preserving all the semantic and functional characteristics of source documents as well as ensuring “transparent” search and access of users to documents. These actions are necessary both for familiarization and for the analysis of the facts contained therein; and organization of collection of information on remote digital repositories supporting protocols OAI-PMH, SRW/SRU, Z39.50.

Full Meta Object profiling for flexible geoprocessing workflows

AbstractThe design and running of complex geoprocessing workflows is an increasingly common geospatial modelling and analysis task. The Business Process Model and Notation (BPMN) standard, which provides a graphical representation of a workflow, allows stakeholders to discuss the scientific conceptual approach behind this modelling while also defining a machine‐readable encoding in XML. Previous research has enabled the orchestration of Open Geospatial Consortium Web Processing Services (WPS) with a BPMN workflow engine. However, the need for direct access to predefined data inputs and outputs results in a lack of flexibility during composition of the workflow and of efficiency during execution. This article develops metadata profiling approaches, described as two possible configurations, which enable workflow management at the meta‐level through a coupling with a metadata catalogue. Specifically, a WPS profile and a BPMN profile are developed and tested using open‐source components to achieve this coupling. A case study in the context of an event mapping task applied within a big data framework and based on analysis of the Global Database of Event Language and Tone database illustrates the two different architectures.

A Meta-Data Manifesto: The Need for Global Health Meta-Data.

Administrative health data recorded for individual health episodes (such as births, deaths, physician visits, and hospital stays) are being widely used to study policy-relevant scientific questions about population health, health services, and quality of care. An increasing number of international health comparisons are undertaken with these data. An essential pre-requisite to such international comparative work is a detailed characterization of existing international health data resources, so that they can be more readily used for comparisons across counties. A major challenge to such international comparative work is the variability across countries in the extent, content, and validity of existing administrative data holdings. Recognizing this, we have undertaken an international proof of concept pilot compiling detailed data about data – i.e., a “meta-data catalogue” – for existing international administrative health data holdings. We describe the methodological process for collecting these meta-data, along with some general descriptive results for selected countries included in the pilot.

What Went Where When? Representing Animal Movements as Simple Darwin Core Occurrences

To usefully describe sensor deployments on animals is a major challenge for advocates of data standards. Bio-logging studies also need to be documented in a standard manner to facilitate discovery and determine relevance? For systems aggregating biodiversity occurrence records, the use of the Darwin Core standard (Wieczorek et al. 2012) to express species occurrences is near ubiquitous. Bio-logging studies are universally multiple instances of species occurrences that output high quality spatial and temporal data recorded by specialists. There are a lot of benefits to summarising these studies by means of a single, flat file record. Simple Darwin Core offers the ability to do this by representing the multiple occurrences as a date range in dwc:eventDate and a footprint polygon using dwc:footprintWKT for the area covered by the track. By also uniformly describing the species, the dwc:basisOfRecord as Machine Observation, and a controlled vocabulary to describe the type of bio-logging data, systems could offer an effective means of querying tracking data. It’s important to look to other data standards initiatives relevant to bio-logging to ensure common usage of Darwin Core terms. The Atlas of Living Australia is using an implementation of Simple Darwin Core to represent data from the bio-logging platform ZoaTrack as occurrence data to make it discoverable via location or species-based searches. Other initiatives, for example Swedish LifeWatch follow a similar approach to represent data from the Wireless Remote Animal Monitoring (WRAM) Scandinavian bio-logging infrastructure. With endorsement from the community, the implementation could be useful as a type of metadata catalogue record, opening it for usage in application programmer interface (API) development and thus enabling machine interoperability between systems and users. In short, bio-logging systems and practitioners would be able to easily discover relevant studies by searching by location and/or species.

An Environmental influences on Child Health Outcomes viewpoint of data analysis centers for collaborative study designs.

A highly complex collaborative study design that pools and extends existing studies, such as the Environmental influences on Child Health Outcomes (ECHO) Program, requires a Data Analysis Center (DAC) with resources and expertise to create a secure environment for housing and analyzing the shared data, harmonize and structure the shared data for different purposes, and apply appropriate and innovative designs and analytic methods. The DAC, in partnership with cohort investigators, must ensure that results from ECHO-wide cohort analyses are appropriately interpreted and reproducible. Understanding the cohorts contributing to ECHO is critical for developing a collaborative environment and the methods to best analyze the data without bias. We further describe the development of the ECHO-wide cohort Metadata Catalog, the architecture of the ECHO-wide cohort data platform, and analytical approaches to facilitate early productivity. The ECHO DAC has established a secure environment for the transfer and storage of ECHO cohort data and information, and initiated processes to promote productive collaborations. Understanding the ECHO DAC responsibilities and assets will help to overcome communication and trust challenges encountered in the initiation of this complex ECHO-wide cohort collaborative research study.

From global action against malaria to local issues: state of the art and perspectives of web platforms dealing with malaria information

BackgroundSince prehistory to present times and despite a rough combat against it, malaria remains a concern for human beings. While evolutions of science and technology through times allowed for some infectious diseases eradication in the 20th century, malaria resists.ObjectivesThis review aims at assessing how Internet and web technologies are used in fighting malaria. Precisely, how do malaria fighting actors profit from these developments, how do they deal with ensuing phenomena, such as the increase of data volume, and did these technologies bring new opportunities for fighting malaria?MethodsEleven web platforms linked to spatio-temporal malaria information are reviewed, focusing on data, metadata, web services and categories of users.ResultsThough the web platforms are highly heterogeneous the review reveals that the latest advances in web technologies are underused. Information are rarely updated dynamically, metadata catalogues are absent, web services are more and more used, but rarely standardized, and websites are mainly dedicated to scientific communities, essentially researchers.ConclusionImprovement of systems interoperability, through standardization, is an opportunity to be seized in order to allow real time information exchange and online multisource data analysis. To facilitate multidisciplinary/multiscale studies, the web of linked data and the semantic web innovations can be used in order to formalize the different view points of actors involved in the combat against malaria. By doing so, new malaria fighting strategies could take place, to tackle the bottlenecks listed in the United Nation Millennium Development Goals reports, but also specific issues highlighted by the World Health Organization such as malaria elimination in international borders.

Collaboration in RDM activities – Practices and development at Aalto University

Watch the VIDEO here. Presenter – Maria SöderholmResearch data management (RDM) is a complex and dynamic topic, and demands diverse expertise, skills and knowledge. The RDM expertise includes subtopics like collection/provision of data; storage and processing of data; long-term preservation requirements of the data; and funders’ demands and solutions to share, re-find and re-use research data. Usually the expertise related to these RDM subtopics is spread to several university units, both academic and administrative. Therefore, many tasks related to RDM, for example, day-to-day practices, the supply of services and the development work are best carried out in a network-based cooperation.In the presentation, we will introduce our RDM related partnership and networking of Aalto University. As a starting point, we introduce the internal service development working principles that our RDM network work is based on. However, the focus will be on describing our RDM working group and development activities.Aalto’s Research Data Management Programme forms the backbone for RDM work. It establishes seven separate action points for RDM activities: 1) open access publishing; 2) implementation of data management planning tool; 3) metadata catalogue for open data; 4) data publishing; 5) comprehensive repository service for storage, back-up and collaboration; 6) combining openness and innovation; and 7) RDM awareness building activities. The actors in the RDM network consist of Research and Innovation Services (leading the group), IT Services, and Learning Centre (previously Library).In the presentation, we will introduce the core actors in more detail, paying attention to the complementarity of the roles; and the activities and the aims, which steer the work. We also discuss the meaning and consequences of the network-based cooperation for the working group.First, the RDM group acts as a joint platform for comprehensive RDM information. Important means of data gathering are surveys and informal discussion with researcher. In the future, formal group discussions on RDM needs are hosted. The previous discussions with researchers have underlined the importance of arranging services for both disciplinary and data specific needs in addition to common university level service needs.Second, the group is a messenger of the RDM topics. Our task is to rise internal RDM awareness and disseminate national and international information and development trends in the university.The third and the most challenging aim is the RDM service planning and delivery. Our task is to identify the existing in-house services, to map the suitable services provided by national and international agents as well as to recognize the needs for new services. Our service portfolio covers both consultation/informational services and technical, hands-on services. However, many of our research data services are still in the planning or piloting stage, thus cooperation with researchers is essential.In our experience, the network-based collaboration model that foster individuals’ interconnectedness is crucial for surviving with the built-in dynamism of RDM. This model provides a non-hierarchical and flexible environment for actions to meet the increasing expectations for research data services we face from the funders, governments, and researchers.

Architecture of a spatial data service system for statistical analysis and visualization of regional climate changes

The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.

Electron Bio-Imaging Centre (eBIC): the UK national research facility for biological electron microscopy.

The recent resolution revolution in cryo-EM has led to a massive increase in demand for both time on high-end cryo-electron microscopes and access to cryo-electron microscopy expertise. In anticipation of this demand, eBIC was set up at Diamond Light Source in collaboration with Birkbeck College London and the University of Oxford, and funded by the Wellcome Trust, the UK Medical Research Council (MRC) and the Biotechnology and Biological Sciences Research Council (BBSRC) to provide access to high-end equipment through peer review. eBIC is currently in its start-up phase and began by offering time on a single FEI Titan Krios microscope equipped with the latest generation of direct electron detectors from two manufacturers. Here, the current status and modes of access for potential users of eBIC are outlined. In the first year of operation, 222 d of microscope time were delivered to external research groups, with 95 visits in total, of which 53 were from unique groups. The data collected have generated multiple high- to intermediate-resolution structures (2.8-8 Å), ten of which have been published. A second Krios microscope is now in operation, with two more due to come online in 2017. In the next phase of growth of eBIC, in addition to more microscope time, new data-collection strategies and sample-preparation techniques will be made available to external user groups. Finally, all raw data are archived, and a metadata catalogue and automated pipelines for data analysis are being developed.

Pilot implementation of the US EPA interoperable watershed network

BackgroundThe mission of the United States Environmental Protection Agency (EPA) is to protect human health and the environment, including air, water and land. Understanding the extent of pollution in waters and identifying waters for protection has been based in part on water quality monitoring data collected and shared by parties (federal, state, tribal, and local) throughout the U.S. To date, this monitoring data has been largely represented by data collected as a water quality sample (data collected by a technician in the field or analyzed in a lab). EPA’s “STORage and RETrieval” (STORET) and the Water Quality Exchange (WQX) have served as the repository for all this sampling data. However, these tools and systems were not designed to handle today’s continuous water quality sensors. EPA has therefore embarked on the Interoperable Watersheds Network (IWN) project, which is focused on identifying a common set of formats and standards for data, and on testing and validating these standards as well as new ways of sharing data and metadata. The completed IWN will greatly expand the sharing of data and its use, thereby streamlining the assessment, restoration, and protection of surface water quality at all levels of government.MethodsStakeholder workgroups were engaged to assist with developing requirements for the three major project components: required attributes and query capability for a centralized metadata catalog, technological and data requirements for data providers, and desired functionality for a web-based discovery tool that provides access to the catalog services and provider data.ResultsThe pilot implementation of IWN uses the Open Geospatial Consortium (OGC) Sensor Observation Service (SOS) 2.0 and WaterML2 standards as the foundation for a distributed sensor data sharing network. Data owners in locations across the United States have worked with EPA to publish their continuous sensor data and related metadata either through “data appliances” running the open-source 52° North implementation of SOS or using commercial software like Kisters’ KiWIS product.Metadata are harvested into a centralized catalog that provides a REST Service API for sensor discovery. Users can discover data by querying for specific parameters, or using spatial boundaries such as HUC, county, a buffered point, or a user defined polygon. The sensor results are returned as GeoJSON, which can be used to create maps. The API also provides the service endpoints for the sensors, which can be used to access the continuous data to create charts or download the data for other analysis.ConclusionThe pilot IWN demonstrates that standards-based interoperability can provide a sound basis for a national-scale clearinghouse for continuous sensor data, though scalability of the approach will need further testing. Selected technical detail, lessons learned, and future plans for the IWN are included in the discussion.

A process-driven platform to manage datasets for research

ABSTRACT
 Objectives
 
 Accumulate, manage and control shared access to research data; 
 Transform and maintain transformation state information about research data; 
 Analyse and investigate data in related sets using open and bespoke tools; 
 Publish extracted data to a secure safe haven environment.
 
 ApproachThe Research Data Management Platform (RDMP) is a set of data structures and processes, sharing a core Catalogue, to manage electronic health records, genomic data and imaging data throughout their lifecycle from identification and acquisition to safe disposal or archival and retention in secured Safe Havens (SH).
 The architecture components of the RDMP consist of the Catalogue and five internal processes: Data Load, Catalogue Management, Data Quality, Data Summary, and Data Extraction. These are designed to enforce rigorous information governance standards relevant to the processing and anonymisation of personal identifiable data. The Catalogue serves as the single ‘source of truth’ about the datasets which all RDMP processes consult. This facilitates repeatable, reliable and auditable operations on the data.
 The novelty of the RDMP is that it dynamically and seamlessly captures and preserves data transformation processes along with the primary research data to promote reuse and curation of continuously accruing research data repositories in a secure SH environment. Thus, the RDMP brings transparency and reproducibility that benefits research programmes in a way that archival of static data objects does not.
 ResultsThe RDMP has been in production use since July 1st 2014. There are 107 datasets configured in the Catalogue, with up to 67 dataset extractions for each of 48 research projects. It has provided data for 32 high-impact journal papers published in the last year.
 Improvements in turnaround time:
 
 Research project data provision reduced from six months to two weeks;
 Data loading reduced from two days to a few hours; 
 Research query response reduced from days to within a day, due to improved and standardised metadata catalogue
 
 ConclusionThe RDMP is a key component in automating the regular release of datasets and rationalising dataset changes over time to ensure reliable delivery of extracts to research projects. The tools and processes comprising the RDMP not only fulfil the RDM requirements of researchers, but also support seamless collaboration of data cleaning, data transformation, data summarisation and data quality assessment activities by different research groups.

Persistent Identifier Practice for Big Data Management at NCI

The National Computational Infrastructure (NCI) manages over 10 PB research data, which is co-located with the high performance computer (Raijin) and an HPC class 3000 core OpenStack cloud system (Tenjin). In support of this integrated High Performance Computing/High Performance Data (HPC/HPD) infrastructure, NCI’s data management practices includes building catalogues, DOI minting, data curation, data publishing, and data delivery through a variety of data services. The metadata catalogues, DOIs, THREDDS, and Vocabularies, all use different Uniform Resource Locator (URL) styles. A Persistent IDentifier (PID) service provides an important utility to manage URLs in a consistent, controlled and monitored manner to support the robustness of our national ‘Big Data’ infrastructure. In this paper we demonstrate NCI’s approach of utilising the NCI’s PID Service to consistently manage its persistent identifiers with various applications.

Spatial Data Sharing: A Pilot Study of French SDIs

Since the appearance of Spatial Data Infrastructure several years ago, there has been a tremendous increase in spatial data available on the Internet. This situation raises several research issues, in terms of identifying the content actually accessible via this medium and its impact on governance and local authority management. Our study proposes a mixed methodology applied to 45 French institutional infrastructures, to compare the objectives stated by their promoters, their content, and the actual services provided. The methodology, based on an analysis of interviews with Spatial Data Infrastructure (SDI) coordinators and their answers to questionnaires, as well as a study of their websites and an exploration of over 160,000 metadata in their metadata catalogues, produced varied results concerning data accessibility, stakeholder networks, the interoperability of tools, and informational equality in different regions. Despite the proactive stance of SDI promoters, only 15.7% of data are open-access. Their interoperability remains restricted to specific types of actors and themes. Although geocollaboration organised by SDIs is very active, it only concerns the public sector. These disparities also concern their informational dimension, as some regions have considerable resources at their disposal, but others do not.

A semantic web services discovery approach based on a mobile agent using metadata

PurposeThe success of web services involved the adoption of this technology by different service providers through the web, which increased the number of web services, as a result making their discovery a tedious task. The UDDI standard has been proposed for web service publication and discovery. However, it lacks sufficient semantic description in the content of web services, which makes it difficult to find and compose suitable web services during the analysis, search, and matching processes. In addition, few works on semantic web services discovery take into account the user’s profile. The purpose of this paper is to optimize the web services discovery by reducing the search space and increasing the number of relevant services.Design/methodology/approachThe authors propose a new approach for the semantic web services discovery based on the mobile agent, user profile and metadata catalog. In the approach, each user can be described by a profile which is represented in two dimensions: personal dimension and preferences dimension. The description of web service is based on two levels: metadata catalog and WSDL.FindingsFirst, the semantic web services discovery reduces the number of relevant services through the application of matching algorithm “semantic match”. The result of this first matching restricts the search space at the level of UDDI registry, which allows the users to have good results for the “functional match”. Second, the use of mobile agents as a communication entity reduces the traffic on the network and the quantity of exchanged information. Finally, the integration of user profile in the service discovery process facilitates the expression of the user needs and makes intelligible the selected service.Originality/valueTo the best knowledge of the authors, this is the first attempt at implementing the mobile agent technology with the semantic web service technology.

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Software industry has evolved to multi-product and multi-platform development based on a mix of proprietary and open source components. Such integration has occurred in software ecosystems through a software product line engineering (SPLE) process. However, metadata are underused in the SPLE and interoperability challenge. The proposed method is first, a semantic metadata enrichment software ecosystem (SMESE) to support multi-platform metadata driven applications, and second, based on mapping ontologies SMESE aggregates and enriches metadata to create a semantic master metadata catalogue (SMMC). The proposed SPLE process uses a component-based software development approach for integrating distributed content management enterprise applications, such as digital libraries. To perform interoperability between existing metadata models (such as Dublin Core, UNIMARC, MARC21, RDF/RDA and BIBFRAME), SMESE implements an ontology mapping model. SMESE consists of nine sub-systems: 1) Metadata initiatives & concordance rules; 2) Harvesting of web metadata & data; 3) Harvesting of authority metadata & data; 4) Rule-based semantic metadata external enrichment; 5) Rule-based semantic metadata internal enrichment; 6) Semantic metadata external & internal enrichment synchronization; 7) User interest-based gateway; 8) Semantic master catalogue. To conclude, this paper proposes a decision support process, called SPLE decision support process (SPLE-DSP) which is then used by SMESE to support dynamic reconfiguration. SPLE-DSP consists of a dynamic and optimized metadata-based reconfiguration model. SPLE-DSP takes into account runtime metadata-based variability functionalities, context-awareness and self-adaptation. It also presents the design and implementation of a working prototype of SMESE applied to a semantic digital library.

Opendoar-A champion of open access repositories in the world

The onset of e-publishing technologies including multimedia authoring, web page designing and related hosting facilities and access tools in the web environment has brought about a significant impact on the libraries i.e. creation of Digital Library. The open access movement was triggered by the journal crisis due to exorbitant price increase in the publications. During the 1990s several e-print archives as well as a few hundred peer reviewed, electronic, scholarly journals emerged. Open access movement is a worldwide effort to provide free online access to scholarly literature like peer reviewed journal articles and preprints. Digital repositories are developing rapidly as a key element of research cyber infrastructure. These include all collected resources in all formats especially contributions from home institutional published and unpublished and is accessible to end users both within and outside of the institution. By 2003, there was a tremendous growth in the Open access research archives in the world in accordance to open access movement. There was need for listing registry of such repositories in order to make them visible to the world of academicians and researchers. A repository registry is a web based metadata catalog that points to repositories. There were several listings of repositories and open access arcives, but there was no single comprehensive list which recorded all the available repositories. Repositories needed to be categorised with clear information on subject coverage, their collection, the content and preservation policies etc. In occardance with Open Access movement Open DOAR & ROAR were set up.