• Title/Summary/Keyword: extensive archiving

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Development of Metadata Elements for Intensive Web Archiving (선택적 웹 아카이빙을 위한 메타데이터 요소 개발)

  • Kim, Hee-Jung;Lee, Hye-Won
    • Journal of the Korean Society for information Management
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    • v.24 no.2
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    • pp.143-160
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    • 2007
  • As digital preservation becomes increasingly important, interest in web archiving has correspondingly increased. The processes of web archiving depend on the types of acquisition methods employed, the organization and storage of data, their completeness, and their scope. This study develops metadata for intensive web archiving. Several web archiving projects are reviewed and analyzed. As a result, administrative metadata has been suggested in addition to the basic elements from the Dublin Core.

A Study on Design and Development Process of Narrative Archiving Policy : Focused on S-NAP of Seoul Metropolitan Archives (서사 기반 수집 실행지침의 설계와 개발절차 서울기록원의 S-NAP을 중심으로)

  • Lee, Kyung Nam;Lee, Hyeon Jung
    • The Korean Journal of Archival Studies
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    • no.65
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    • pp.199-226
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    • 2020
  • It is widely agreed that a documentation strategy that considers the social context of fragmented records is needed for documentation of social memories. This paper examined a new methodology named Seoul Narrative Archiving Policy(S-NAP) which was developed for the documentation of social memories in metropolitan areas. Also, the paper reviewed the applicability of S-NAP through the collection cases of Seoul Metropolitan Archives. The development process of the S-NAP is as follows. First, acquisition topic domains that cover an entire metropolitan region were developed. Next, implementation units(S-NAP) were designed through extensive data analysis that encompasses social, economic, culture, and art areas and reflects outcomes of regional studies. As a result, a total of nine acquisition topic domains, 61 parents S-NAP, and 184 children S-NAP were derived from the aforementioned methodology and methods. Finally, this paper proposed the applicability of S-NAP as archival contents and as a supportive tool for archival activity networks.

A Study on Construction of Digital Museum Archiving Regarding Dance Costume (무용공연작품 의상을 위한 디지털 뮤지엄 아카이빙 구축)

  • Jeong, Yu-Jin;Yoo, Ji-Young;Baek, Hyun-Soon
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.1
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    • pp.81-88
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    • 2019
  • This article aims to identify the characters and theme shown in dance costume and utilize them from an educational perspective by constructing digital museum archiving, which can be systematically collected, classified and stored from dance costume. It deals with definition of digital museum archiving as theoretical background and examples of how to create digital museum archiving as research content. The role that archiving plays in digital museum and effectiveness have been demonstrated. Archive is a term used to indicate extensive material and its storage and referred to as an integrative model of display in the computer-generated space. When it comes to producing dance costume as a form of digital museum, the museum is to be made in the computer-generated area of dance costume. The museum shows each division of major, medium and minor classification. The major classification divides genre of dance performance into Korean dance, modern dance and ballet. The middle involves choreographers, costume designers. The minor categorization includes newspaper, interviews, performance pictures, and programs. Digital museum has the value of space utilization, creation, culture, utilization of multiple educational programs, offering of digital museum content, two-way communication, and program development of the new display form.

Design of Subject-based Community Model by Linkage Heterogeneous Content: Focused on Field of Biological Science

  • Ahn, Bu-Young;Kim, Ji-Young;Oh, Chung-Shick;Lee, Myung-Sun
    • International Journal of Contents
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    • v.6 no.3
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    • pp.10-14
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    • 2010
  • Researchers in Korea and elsewhere have carried out a wide variety of important research activities in their respective fields, producing valuable research results. For such diverse research results to be shared and exchanged among researchers working in the same discipline and research subject there needs to be a community environment based on free utilization of information. Against this backdrop, this study seeks to classify and reprocess the reference/factual content owned by the KISTI (Korea Institute of Science and Technology Information), a state-run distributor of information on science and technology, by the different research subjects. It also seeks to develop and provide a community model based on the concepts of open archiving and open access for the researchers specialized in the related fields of research. This community model is developed focusing on the research results from the field of bioscience, where the most extensive studies are currently being conducted. To develop the community model, this study: (a) surveys the current status of the content owned by KISTI; (b) analyzes the patterns and characteristics of biological scientific content among the KISTI-owned content; and (c) designs a web platform where researchers can freely upload/download research results.

DP-LinkNet: A convolutional network for historical document image binarization

  • Xiong, Wei;Jia, Xiuhong;Yang, Dichun;Ai, Meihui;Li, Lirong;Wang, Song
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.5
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    • pp.1778-1797
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    • 2021
  • Document image binarization is an important pre-processing step in document analysis and archiving. The state-of-the-art models for document image binarization are variants of encoder-decoder architectures, such as FCN (fully convolutional network) and U-Net. Despite their success, they still suffer from three limitations: (1) reduced feature map resolution due to consecutive strided pooling or convolutions, (2) multiple scales of target objects, and (3) reduced localization accuracy due to the built-in invariance of deep convolutional neural networks (DCNNs). To overcome these three challenges, we propose an improved semantic segmentation model, referred to as DP-LinkNet, which adopts the D-LinkNet architecture as its backbone, with the proposed hybrid dilated convolution (HDC) and spatial pyramid pooling (SPP) modules between the encoder and the decoder. Extensive experiments are conducted on recent document image binarization competition (DIBCO) and handwritten document image binarization competition (H-DIBCO) benchmark datasets. Results show that our proposed DP-LinkNet outperforms other state-of-the-art techniques by a large margin. Our implementation and the pre-trained models are available at https://github.com/beargolden/DP-LinkNet.