• International Journal of Knowledge Content Development & Technology
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• v.8 no.1
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• pp.25-36
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• 2018

Research data must be testable. Science is all about verification and testing. To make data testable, tools used to produce, collect, and examine data during the research must be available. Quite often, however, these data become inaccessible once the work is over and the results being published. Hence, information and the related context must be provided on how research data are preserved and how they can be reproduced. Open Science is the international movement for making scientific research data properly accessible for research community. One of its major goals is building data repositories to foster wide dissemination of open data. The objectives of this research are to examine the features of research data, common repository platforms, and community requests for the purpose of designing functional requirements for research data repositories. To analyze the features of the research data, we use data curation profiles available from the Data Curation Center of the Purdue University, USA. For common repository platforms we examine Fedora Commons, iRODS, DataONE, Dataverse, Open Science Data Cloud (OSDC), and Figshare. We also analyze the requests from research community. To design a technical solution that would meet public needs for data accessibility and sharing, we take the requirements of RDA Repository Interest Group and the requests for the DataNest Community Platform developed by the Korea Institute of Science and Technology Information (KISTI). As a result, we particularize 75 requirement items grouped into 13 categories (metadata; identifiers; authentication and permission management; data access, policy support; publication; submission/ingest/management, data configuration, location; integration, preservation and sustainability, user interface; data and product quality). We hope that functional requirements set down in this study will be of help to organizations that consider deploying or designing data repositories.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.5-20
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• 1999

Recently, the new software paradigm in information technology (IT) is the component-based development (CBD) technology that has brought as a result of the distributed computing environment (DCE). The CBD has reduced a program developing time and has been designed to make a distributed computing environment easier in the Internet and Intranet environments. These changes of software technology have influence on the geographic information system (GIS) and the CBD technology is highly needed as a point of view of the technique and policy of the geographic information system. In this paper, we designed and implemented an Enterprise Server for the efficient development and management of GIS components. Especially, the Enterprise Server was developed with the Enterprise JavaBeans Specification 1.1 that had been proposed as an industry standard by the Sun Microsystems. The Enterprise Server can allows users to manage the Unified Modeling Language (UML) and Design Patterns for the development of GIS components, develop a GIS component container which obeyed the Open Geodata Interoperability Specification (OpenGlS), manage spatial metadata through a spatial XML (eXtensible Markup Language) engine, and implement a TESTBED server for testing and verification of developed GIS components.

• The Korean Journal of Archival Studies
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• no.25
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• pp.91-129
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• 2010

As it grows more heavily reliant on information system, researchers seek for various ways to manage and utilize of dataset records which is accumulated in public information system. It might be needed to adjust date and enhance the quality of public administrative dataset records during transferring to archive system or sharing server. The purpose of this paper is presenting data adjustment and quality enhancement methods for public administrative dataset records, and it refers to ETT procedure and method of construction of datawarehouses. It suggests seven typical examples and processing method of data adjustment and quality enhancement, which are (1) verification of quantity and data domain (2) code conversion for a consistent code value (3) making component with combinded information (4) making a decision of precision of date data (5) standardization of data (6) comment information about code value (7) capturing of metadata. It should be reviewed during dataset record transfer. This paper made Data adjustment and quality enhancement requirements for dataset record transfer, and it could be used as data quality requirement of administrative information system which produces dataset.