• Journal of Ecology and Environment
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• v.41 no.5
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• pp.142-144
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• 2017

In recent decades, as it becomes increasingly important to monitor and research long-term ecological changes, worldwide attempts are being conducted to integrate and manage ecological data in a unified framework. Especially domestic ecological data in South Korea should be first standardized based on predefined common protocols for data integration, since they are often scattered over many different systems in various forms. Additionally, foreign ecological data should be converted into a proper unified format to be used along with domestic data for association studies. In this study, our interest is to integrate ECN data with Korean domestic ecological data under our unified framework. For this purpose, we employed our semi-automatic data conversion tool to standardize foreign data and utilized ground beetle (Carabidae) datasets collected from 12 different observatory sites of ECN. We believe that our attempt to convert domestic and foreign ecological data into a standardized format in a systematic way will be quite useful for data integration and association analysis in many ecological and environmental studies.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.2
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• pp.139-143
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• 2021

In this study, data repository information registered in re3data (re3data.org), a research data registry, was collected. Based on collected data, the current status was analyzed for 354 repositories (approximately 14% of total repositories) in the field using keywords in the ecological field suggested by two experts. Major metadata formats used to describe data in ecological research data repositories include Federal Geographic Data Committee Content Standard for Digital Geospatial Metadata (FGDC/CSDGM), Dublin Core, ISO 19115, Ecological Metadata Language (EML), Directory Interchange Format (DIF), Darwin Core, Data Documentation Initiative (DDI), and DataCite Metadata Schema. The number of ecological repositories according to country is 102 in the US, 34 in Germany, 31 in Canada, and one in Korea. A total of 771 non-profit organizations and 12 for-profit organizations are involved in the construction of the ecological field research data repository. Data version control ratio of the ecological field research data repositories registered in re3data was analyzed to be somewhat higher (86.6%) than the total ratio (83.9%). Results of this study can be used to establish policies to build and operate a research data repository in the ecological field.

• Journal of Ecology and Environment
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• v.41 no.3
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• pp.78-84
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• 2017

Recently, great demands are rising around the globe for monitoring and studying of long-term ecological changes. To go with the stream, many researchers in South Korea have attempted to share and integrate ecological data for practical use. Although some achievements were made in the meantime, we still have to overcome a big obstacle that existing ecological data in South Korea are mostly spread all over the country in various formats of computer files. In this study, we aim to handle the situation by developing a semi-automatic data conversion tool for Korean ecological data standardization, based on some predefined protocols for ecological data collection and management. The current implementation of this tool works on only five species (libythea celtis, spittle bugs, mosquitoes, pinus, and quercus mongolica), helping data managers to quickly and efficiently obtain a standardized format of ecological data from raw collection data. With this tool, the procedure of data conversion is divided into four steps: data file and protocol selection step, species selection step, attribute mapping step, and data standardization step. To find the usability of this tool, we utilized it to conduct the standardization of raw five species data collected from six different observatory sites of Korean National Parks. As a result, we could obtain a common form of standardized data in a relatively short time. With the help of this tool, various ecological data could be easily integrated into the nationwide common platform, providing broad applicability towards solving many issues in ecological and environmental system.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.9-21
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• 2020

Ecological communities adapt the concept of informatics in the late 20 century and develop rapidly in the early 21 century to form Ecoinformatics as the new approach of ecological research. The new approach takes into account the data-intensive nature of ecology, the precious information content of ecological data, and the growing capacity of computational technology to leverage complex data as well as the critical need for informing sustainable management of complex ecosystems. It comprehends techniques for data management, data analysis, synthesis, and forecasting on ecological research. The present paper attempts to review the development history, studies and application cases of ecoinformatics in ecological research especially on Long Term Ecological Research (LTER). From the applications show that the ecoinformatics approach and management system have formed a new paradigm in ecological research.

• Korean Journal of Ecology and Environment
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• v.51 no.3
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• pp.212-220
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• 2018

Ecological and ecosystem database is becoming very necessary to understand origins and relationship between human and nature and also to minimize disturbance caused by human activities. An ecological information portal can play important roles as a computing system to collect knowledge, distributed research findings and separated data from researchers. In this study, we designed and developed ecological information portal service (EcoBank 1.0) for collecting and providing ecological information for diverse classes of stakeholders. To reach the goal, we had reviewed related and comparable ecological database portals to design conceptual structure of EcoBank system including database management framework. Then, we developed some functions of ecosystem analysis for each stake-holders (researchers, general public and policy makers). As a result of this study, we successfully designed of EcoBank system covering the functions of Digital Object Identifier(DOI) publishing and data quality management process. Also, we (1) applied ecological indices for calculating biodiversity by administrative boundary for policy makers, (2) provided statistical information of econature map for general public and distribution characteristics of species for researchers. To make a successful establishment of EcoBank, we have to collect and build up related database and offer various and reliable ecological data consistently. We expect that the successful construction of EcoBank will help not only to accomplish sustainable development goals but also to raise the welfare of ecosystem in Korea.

• The Journal of Sustainable Design and Educational Environment Research
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• v.7 no.1
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• pp.39-55
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• 2008

The purpose of this study is to suggest improvement of certification standards of environment friendly architecture in ecological environment field by surveying and analyzing actual status of actual certification schools of environment friendly architecture per ecological environment elements through extracting ecological environment elements which is possible to analyze in quantity certification standards of environment friendly architecture. As contents of the study, first, certification as an examination on certification system of environment friendly architecture, summary of certification system of environment friendly architecture, ecological environment elements which is possible for quantitative analysis of ecological environment certification standards were extracted. Second, actual status of ecological environment elements per school grade, region, and population increase by collecting actual data of certification schools of environment friendly architecture. Third, using analysis data of ecological environment elements, ecological area ratio of certification schools of environment friendly architecture per weighted values of space types was calculated and the results were analyzed as the follows. (1) In case of preliminary certification out of total objects of investigation schools was average 34.06% but in this case of certification, it was reduced to 33.07%. However, it is difficult to make judgment as actual evidence data since ecological area ratio of actual preliminary certification is data based on drawing planes. Therefore, in case of this certification, elementary schools was investigated at average 33.11%, middle schools 34.81%, and high schools 31.28% and middle school showed the highest relatively. (2) Besides, average composition ratio of ecological area ratio was 63.04% in case of this certification regardless of school grade and region and it was analyzed that about 70% of ecological area ratio is composed of the natural based green area including pure natural based green land and 6.89% of ecological learning institute.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.5 no.2
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• pp.43-49
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• 2024

Ecological monitoring provides indispensable data for biodiversity conservation and sustainable resource management. However, the complexity and variability inherent in ecological monitoring data necessitate robust verification processes to ensure data integrity. This study employed Benford's Law, a statistical principle traditionally used in fields such as finance and health sciences, to evaluate the authenticity of ecological monitoring data related to the abundance of migratory bird species across various locations in South Korea. Benford's Law anticipates a specific logarithmic distribution of leading digits in naturally occurring numerical datasets. Our investigation involved two stages of analysis: a first-order analysis considering the leading digit and a second-order analysis examining the first two digits of bird population counts. While the first-order analysis displayed moderate conformity to Benford's Law that suggested overall data integrity, the second-order analysis revealed more pronounced deviations, indicating potential inconsistencies or inaccuracies in certain subsets of the data. Although our data did not perfectly align with Benford's Law, these deviations underscore the complex nature of ecological research, which is influenced by a multitude of environmental, methodological, and human factors.

• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.1-9
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• 2012

The purpose of ecological risk assessment in soil ecosystem is to protect ecological receptors and to provide a scheme of efficient management for soil contaminants. Developed countries have already prepared the methodologies of ecological risk assessment by considering their soil properties, land use, and ecological receptors. In this study, we compared the soil ecological risk assessment processes in the similarity and differences in methodology. Four countries, except for USA, adjusted the toxicological data for ecological risk assessment, based on their representative soil properties because the soil properties affect toxic effects to ecological receptors. The soil ecological risk assessment methodology of Netherlands and UK was based on 'Technical guidance document on risk assessment (TGD)' of European Chemical Bureau (ECB). Australia, USA, and Canada developed their autonomous methodology. In the Netherlands, UK, Australia, and Canada, they employed the species sensitivity distribution (SSD) approach if sufficient toxicity data are available. The USA determined the ecological soil screening level by obtaining the geometric mean of toxicological data for three species. Furthermore, all countries consider secondary poisoning in their soil ecological risk assessment. The latest risk assessment methodology of soil ecosystem that this study investigated can be used to explore what Korea needs to develop the Korean ecological risk assessment methodology of soil ecosystem in the future.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.135-140
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• 2023

The intricate relationship between species and their ecosystems has been a focal point of ecological research for decades. With the advent of big data and artificial intelligence, we are now able to explore this relationship with unprecedented depth and precision. This review delves into the transformative role of these technologies in ecological research, emphasizing their potential to enhance our understanding of species-ecosystem linkages.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.187-192
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• 2023

The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.