• Title, Summary, Keyword: Research Data

Search Result 55,889, Processing Time 0.121 seconds

Study about Research Data Citation Based on DCI (Data Citation Index) (Data Citation Index를 기반으로 한 연구데이터 인용에 관한 연구)

  • Cho, Jane
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.50 no.1
    • /
    • pp.189-207
    • /
    • 2016
  • Sharing and reutilizing of research data could not only enhance efficiency and transparency of research process, but also create new science through data integrating and reinterpretationing. Diverse policies about research data sharing and reutilizing have been developing, along with extending of research evaluating spectrum that across research data citation rate to social impact of research output. This study analyzed the scale and citation number of research data which has not been analyzed before in korea through data citation index using Kruskal-Wallis H analysis. As result, genetics and biotechnology are identified as subject areas which have most huge number of research data, however the subject areas that have been highly cited are identified as economics and social study such as, demographic and employment. And Uk Data Archive, Inter-university Consortium for Political and Social Research are analyzed as data repositories which have most highly cited research data. And the data study which describes methodology of data survey, type and so on shows high citation rate than other data type. In the result of altmetrics of research data, data study of social science shows relatively high impact than other areas.

Functional Requirements for Research Data Repositories

  • Kim, Suntae
    • International Journal of Knowledge Content Development & Technology
    • /
    • v.8 no.1
    • /
    • pp.25-36
    • /
    • 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.

A Study on Ontology Design for Research Data Management (연구데이터 관리를 위한 온톨로지 설계에 대한 연구)

  • Park, Ok Nam
    • Journal of Korean Society of Archives and Records Management
    • /
    • v.18 no.1
    • /
    • pp.101-127
    • /
    • 2018
  • The systematic management of research data is vital because it increases research data's value for research reproduction, verification, and reusability. Standard metadata will play a key role in research data registration, management, and data extraction. Research data has various structural relationships, such as research, research data, data sets, and files, and associated with entities such as citations and research results. The study proposes an ontology model for research data management. It also suggests the application of ontology to NTIS. Previous studies, metadata standard analyses, and research data repository case studies were conducted.

Research Data Management of Science and Technology Research Institutes in Korea (국내 과학기술분야 연구기관의 과학데이터 관리 현황)

  • Choi, Myung-Seok;Lee, Seung-Bock;Lee, Sanghwan
    • The Journal of the Korea Contents Association
    • /
    • v.17 no.12
    • /
    • pp.117-126
    • /
    • 2017
  • As the recent research environment and research paradigm have become data-driven, Open Science, based on openness and sharing of public research results, has emerged as a global agenda for scientific research. National policies for sharing and re-use of research data from publicly-funded research are in effect globally. Therefore, in Korea, it is urgent to build policies and infrastructure for sharing and re-use of research data. In this paper, we investigate the current status of research data management of science and technology research institutes in Korea. We conducted in-depth interviews with researchers from 22 research institutes belonging to the National Research Council of Science & Technology, and 20 universities in Korea, asking about terms of creation management utilization of research data, willingness to share data, and needs for sharing and re-use of research data. From these interviews, we drew implications for open research data and future directions.

A Case Study of the Australian Research Data Policy and Support Services (호주의 연구데이터 정책 및 지원체계에 대한 사례 분석)

  • Shim, Wonsik
    • Journal of the Korean Society for information Management
    • /
    • v.36 no.4
    • /
    • pp.227-251
    • /
    • 2019
  • In early 2019, Korea passed the law that introduced data management plan policy similar to those adopted by national funding agencies in other countries. In anticipation of developing research data infrastructure and support services, this study analyzed Australia's relevant policies and policy instruments. A number of face-to-face interviews with the experts at the national funding agency, a national research data agency and a number of research libraries, along with focused literature analysis. In Australia, the 2015 Public Data Policy is applied to research data from publicly funded research. Research data management and sharing is recommended but not required by the national funding agency it its policy documents. Australian National Data Service(ANDS), Australia's national research data agency, is an important component of the national research infrastructure. ANDS plays a wide range of roles including research data platform development, education and training, policy support, and funding agency for small-scale R&D. Some of the Australian research libraries have developed in-house systems for research data storage and publishing. However, there is no significant demand for research data service as yet. Lessons learned include the following: ensuring transparency and predictability of research data policies, establishing a dedicated agency responsible for research data platform development and training, and cultivating data capabilities at research libraries.

Development of Interactive Data Broadcasting System Compliant with ATSC Standards

  • Jeong, Jong-Myeon;Lee, Yong-Ju;Park, Min-Sik;Choi, Ji-Hoon;Choi, Jin-Soo;Kim, Jin-Woong
    • ETRI Journal
    • /
    • v.26 no.2
    • /
    • pp.149-160
    • /
    • 2004
  • In this paper, we present an interactive data broadcasting system compliant with the Advanced Television Systems Committee (ATSC) standards. The proposed system provides users not only with various data broadcasting services but also remote interactive services. For various data broadcasting services, we have adopted a synchronized data injector that calculates the transmission time of synchronized data accurately and multiplexes synchronized data with the data of an MPEG-2 audio-visual program according to the calculated transmission time. To support remote interactive services, we designed and implemented a return channel server connected on a bi-directional interaction channel. Test results show that the proposed system provides both an asynchronous and synchronized data broadcasting service and remote interactive service appropriately.

  • PDF

Information Technology Infrastructure for Agriculture Genotyping Studies

  • Pardamean, Bens;Baurley, James W.;Perbangsa, Anzaludin S.;Utami, Dwinita;Rijzaani, Habib;Satyawan, Dani
    • Journal of Information Processing Systems
    • /
    • v.14 no.3
    • /
    • pp.655-665
    • /
    • 2018
  • In efforts to increase its agricultural productivity, the Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development has conducted a variety of genomic studies using high-throughput DNA genotyping and sequencing. The large quantity of data (big data) produced by these biotechnologies require high performance data management system to store, backup, and secure data. Additionally, these genetic studies are computationally demanding, requiring high performance processors and memory for data processing and analysis. Reliable network connectivity with large bandwidth to transfer data is essential as well as database applications and statistical tools that include cleaning, quality control, querying based on specific criteria, and exporting to various formats that are important for generating high yield varieties of crops and improving future agricultural strategies. This manuscript presents a reliable, secure, and scalable information technology infrastructure tailored to Indonesian agriculture genotyping studies.

An impact of meteorological Initial field and data assimilation on CMAQ ozone prediction in the Seoul Metropolitan Area during June, 2007 (기상 모델의 초기장 및 자료동화 차이에 따른 수도권 지역의 CMAQ 오존 예측 결과 - 2007년 6월 수도권 고농도 오존 사례 연구 -)

  • Lee, Dae-Gyun;Lee, Mi-Hyang;Lee, Yong-Mi;Yoo, Chul;Hong, Sung-Chul;Jang, Kee-Won;Hong, Ji-Hyung
    • Journal of Environmental Impact Assessment
    • /
    • v.22 no.6
    • /
    • pp.609-626
    • /
    • 2013
  • Air quality models have been widely used to study and simulate many air quality issues. In the simulation, it is important to raise the accuracy of meteorological predicted data because the results of air quality modeling is deeply connected with meteorological fields. Therefore in this study, we analyzed the effects of meteorological fields on the air quality simulation. This study was designed to evaluate MM5 predictions by using different initial condition data and different observations utilized in the data assimilation. Among meteorological scenarios according to these input data, the results of meteorological simulation using National Centers for Environmental Prediction (Final) Operational Global Analysis data were in closer agreement with the observations and resulted in better prediction on ozone concentration. And in Seoul, observations from Regional Meteorological Office for data assimilations of MM5 were suitable to predict ozone concentration. In other areas, data assimilation using both observations from Regional Meteorological Office and Automatical Weather System provided valid method to simulate the trends of meteorological fields and ozone concentrations. However, it is necessary to vertify the accuracy of AWS data in advance because slightly overestimated wind speed used in the data assimilation with AWS data could result in underestimation of high ozone concentrations.

Development Procedure of Data Organization of Data Repositories for Construction Engineering Research Cyberinfrastructure (건설공학 연구의 사이버 인프라를 위한 데이터 저장소의 데이터 구성의 단계적 개발방법)

  • Lee, Chang-Ho
    • Journal of the Architectural Institute of Korea
    • /
    • v.36 no.10
    • /
    • pp.177-188
    • /
    • 2020
  • The cyberinfrastructure for construction engineering research provides construction engineering researchers and engineers with a research environment that includes data repository, tools, and other computing services through the internet. As a main component of the cyberinfrastructure, the data repository stores the research project data and serves for data curation with data uploads/downloads. Since the data curation naturally depends on how the data is organized in the data repository, the data organization is important for practically useful data repositories. This paper uses the notation of classes and attributes of a data model to discuss the procedural steps to develop the efficient data organization of data repositories such as the data depot of DesignSafe for natural hazards engineering. The procedural development steps begins with the definition of uses for and the size of data repository. The basic organization of main data of the data repository is explored, and then the elaboration of data is proceeded. After the usage of data is evaluated by using a number of evaluation criteria, the data organization is improved based on the evaluation results. These development steps are repeated with various possible sequences until the efficient data organization is finally developed for data repositories for construction engineering research.

The Functional Requirements of Core Elements for Research Data Management and Service (연구 데이터 관리 및 서비스를 위한 핵심요소의 기능적 요건)

  • Kim, Juseop;Kim, Suntae;Choi, Sangki
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.53 no.3
    • /
    • pp.317-344
    • /
    • 2019
  • Increasing the value of data, paradigm shifts in research methods, and specific manifestations of open science indicate that research is no longer text-centric, but data-driven. In this study, we analyzed the services for DCC, ICPSR, ANDS and DataONE to derive key elements and functional requirements for research data management and services that are still insufficient in domestic research. Key factors derived include DMP writing support, data description, data storage, data sharing and access, data citations, and data management training. In addition, by presenting functional requirements to the derived key elements, this study can be applied to construct and operate RDM service in the future.