中文    English

Journal of library and information science in agriculture ›› 2020, Vol. 32 ›› Issue (9): 6-14.doi: 10.13998/j.cnki.issn1002-1248.2020.09.20-0411

• Research on Digital Humanities from a technical perspective • Previous Articles     Next Articles

Semantic Annotation of Image Resources in Digital Humanities

CHEN Tao1,*, SHAN Rongrong2, LI Hui1,3   

  1. 1. Shanghai Library/Institute of Scientific & Technical Information of Shanghai, Shanghai 201100;
    2. Department of Library, Information and Archives, Shanghai University, Shanghai 200444;
    3. Department of Information Management, Nanjing University, Nanjing 210046
  • Received:2020-01-08 Online:2020-09-05 Published:2020-09-30

Abstract: [Purpose/Significance] A large number of image resources in digital humanities have not been in effective use for a long time, and the phenomenon of "isolated image islands" is intensifying. The International Image Interoperability Framework (IIIF) opens a new window for more in-depth interactions with image applications. Image annotation is the key to breaking image islands and enhancing image recognition. [Method/Process] Based on IIIF framework, this paper proposes three dimensions of image annotation: image-level metadata injection, object-level content transcription, and semantic-level deep annotation connection. At the same time, the ontology management platform built in the paper provides ontology support for semantic annotation of image resources. [Results/Conclusions] This paper takes Night-Shining White, a monochrome ink-on-paper painting by Han Gan, as an example. In this case, the paper discusses the new interactive experience and research mode brought by the use of image annotation and IIIF technology in semantic enhancement of images, object tag clustering and precise associations of resources. It indicates that the combination of IIIF, linked data and artificial intelligence (AI) is bound to open a new era of digital humanities research.

Key words: international image interoperability framework (IIIF), semantic annotation, ontology, linked data, digital humanities

CLC Number: 

  • G250
[1] 马林青, 韩若画(译). 数字人文: 改变知识创新与分享的游戏规则[M]. 北京: 中国人民大学出版社, 2018.
[2] 大卫·M 贝里, 安德斯·费格约德. 数字人文: 数字时代的知识与批判[M]. 王晓光, 译. 大连: 东北财经大学出版社, 2019.
[3] ALBERTO S.International image interoperability framework(IIIF): A panoramic view[J]. JLIS. it, 2017, 8(1): 50-66.
[4] STUART S, ROBERT S, TOM C.The international image interoperability framework(IIIF): A community & technology approach for web-based images[J]. Society for imaging science and technology, 2015, 8: 16-21.
[5] SARAH A L.Review: International image interoperability framework(IIIF)[J]. Journal of the American musicological society, 2018, 71(2): 561-572.
[6] ANDY C.IIIF: Unshackle your images[C]. MW2016: Museums and the Web 2016, Los Angeles, USA, 2016.
[7] TRISTAN R, ROB L, JEFFREY C S C, et al. IIIF at Scale[EB/OL].[2020-04-04]. https://mw20.museweb.net/paper/iiif-at-scale/.
[8] JULIEN A R.Suggested measures for deploying IIIF in swiss cultural heritage institutions[EB/OL]. [2020-04-05].https://www.researchgate.net/publication/340966631_Swiss_institutions_climbing_up_the_IIIF_ladder.
[9] IIIF collections in Japan[EB/OL]. [2020-04-04].https://www.kanzaki.com/works/2016/pub/image-annotator?u=https://nakamura196.github.io/iiif/data/collection/collection.json.
[10] 耿曼曼. 图书馆图像资源开发利用: 国际图像互操作框架[J]. 图书馆学研究, 2019, 18: 37-45.
[11] 张轶. 国际图像互操作框架及其应用分析[J]. 数字图书馆论坛,2019, 5: 42-49.
[12] 付跃安. 国际图像互操作框架(IIIF)及在数字资源集成中的应用[J]. 图书馆论坛, 2020, 4: 159-166.
[13] GRASSI M, MORBIDONI C, NUCCI M, et al.Pundit: Creating, exploring and consuming semantic annotations[C]. In proceedings of the 3rd international workshop on semantic digital archives, Valletta, Malta, 2013.
[14] SIMON R, BARKER E, ISAKSEN L, et al.Linked data annotation without the pointy brackets: Introducing recogito[J]. Journal of map & geography libraries: Advances in geospatial information, collections & archives, 2017, 13(1): 111-132.
[15] LAURA H, GUUS S, JAN W, et al.Semantic annotation of image collections[EB/OL]. [2020-05-10].https://www.cs.vu.nl/~guus/papers/Hollink03b.pdf.
[16] ZHENG Y Z, LI Z X, ZHANG C L.A hybrid architecture based on CNN for image semantic annotation[C]. 9th international conference on intelligent information processing(IIP), Melbourne, Australia. 2016,11: 81-90.
[17] STORK L, WEBER A, GASSZOM E, et al.Semantic annotation of natural history collections[J]. Web semantics, 2019, 59: 100462.
[18] PIERRE A, ILYA Z, JUAN P.A Classification of Semantic Annotation Systems[J]. Semantic Web, 2012, 3: 223-248.
[19] 王晓光, 徐雷, 李纲. 敦煌壁画数字图像语义描述方法研究[J]. 中国图书馆学报, 2014, 40(1): 50-59.
[20] WANG X G, SONG N Y, ZHANG L, et al.Understanding subjects contained in Dunhuang mural images for deep semantic annotation[J]. Journal of documentation, 2018, 74(2): 333-353.
[21] 徐雷, 王晓光. 叙事型图像语义标注模型研究[J]. 中国图书馆学报, 2017, 43(5): 70-83.
[22] 陈金菊, 欧石燕. 数字图像语义标注模型比较与分析[J]. 图书情报工作, 2018, 62(6): 116-124.
[23] 陈涛, 张永娟, 刘炜, 等. 关联数据发布的若干规范及建议[J]. 中国图书馆学报, 2019, 45(1): 34-46.
[24] ADRIAN R.YOLO object detection with OpenCV[EB/OL]. [2020-04-18].https://www.pyimagesearch.com/2018/11/12/yolo-object-detection-with-opencv/.
[25] GONZALO V-C, NIELS D L, MUBARAK S.Holistic object detection and image understanding[J]. Computer vision and image understanding, 2019, 181: 1-13.
[26] FILESTACK. Comparing image tagging services: Google vision, Microsoft cognitive services, amazon rekognition and clarifai[EB/OL].[2020-05-20]. https://blog.filestack.com/thoughts-and-knowledge/comparing-google-vision-microsoft-cognitive-amazon-rekognition-clarifai/.
[1] HUANG Shuiqing, ZHANG Wei, LIU Liu. Construction and Development of an Autonomous Knowledge System for Computational Humanities [J]. Journal of library and information science in agriculture, 2026, 38(5): 16-34.
[2] ZHANG Ling. Integrating Digital Humanities and Agricultural Knowledge Services A Simulation Modeling Perspectives [J]. Journal of library and information science in agriculture, 2026, 38(2): 79-89.
[3] Haoxian WANG, Ziming ZHOU, Feifei DING, Chengfu WEI. Digital Humanities & Large Language Models: Practice and Research in Semantic Retrieval of Ancient Documents [J]. Journal of library and information science in agriculture, 2024, 36(9): 89-101.
[4] FAN Kexin, XIAN Guojian, ZHAO Ruixue, HUANG Yongwen, SUN Tan. Ontology Construction for Intelligent Control and Application of Crop Germplasm Resources [J]. Journal of library and information science in agriculture, 2024, 36(3): 92-107.
[5] HU Shoumin, DONG Huanqing. Framework for the Semantic Description of Images with Integrated Events and Emotions [J]. Journal of library and information science in agriculture, 2024, 36(2): 51-60.
[6] Zhihao GUAN, Zhiyi SHAN, Tian LI, Ruixue ZHAO. Knowledge Model and Construction of Soybean Breeding [J]. Journal of library and information science in agriculture, 2024, 36(11): 79-91.
[7] ZHANG Xingwang, DUAN Xuechun, XIN Jie. A Study on the Knowledge-Based Description Framework and Application Scenarios of Ancient Chinese Map Documents in the Digital Intelligence Era [J]. Journal of library and information science in agriculture, 2023, 35(9): 4-11.
[8] SHAN Shuyang, XIA Cuijuan, LIU Qianqian. Exploration of Genealogy Public Knowledge Service Model with the Resources and Technology: Taking the Exhibition Project of "AR Surname Wall" as an Example [J]. Journal of library and information science in agriculture, 2023, 35(6): 83-92.
[9] LV Ruijuan, ZHANG Jingbei, YAN Dan, CAI Yingchun. Innovative Development of AIGC and GLAM: Review of "Shaping the Future: AIGC and GLAM Innovative Development" Cutting-Edge Academic Forum [J]. Journal of library and information science in agriculture, 2023, 35(5): 27-36.
[10] XIAO Keyi, LI Yunfan. Present Situation and Enlightenment of Chinese University Libraries' Participation in Digital Humanistic Educational Service from the Perspective of Supply and Demand Matching [J]. Journal of library and information science in agriculture, 2023, 35(5): 37-50.
[11] HUANG Shuiqing, WANG Xiaoguang, XIA Cuijuan, OUYANG Jiang. Advancing the Work on Ancient Classics in the New Era and Accelerating Innovative and Intelligent Development [J]. Journal of library and information science in agriculture, 2022, 34(5): 4-20.
[12] CHAI Miaoling, ZOU Yixing, TAN Rongzhi, ZENG Yi, REN Yunyue. Research and Practice on Association of Scientific Data and Scientific Literature Oriented to Knowledge Service of Agricultural Industry [J]. Journal of library and information science in agriculture, 2022, 34(3): 37-50.
[13] CHEN Wen, WANG Dongliang, XU Yunhao, CHEN Yuping, YANG Youqing. The Construction of Metadata Model for Digital Resources of Cultural Creativity Works [J]. Journal of library and information science in agriculture, 2022, 34(12): 77-86.
[14] HE Lin, WU Shuai, YE Yahui, BAI Ying. Analysis of the Group Characteristics of Yuhua Heroes based on Lightweight Ontology [J]. Journal of library and information science in agriculture, 2022, 34(12): 33-44.
[15] SHANG Hongli, ZHANG Sijie, WEI Zhipeng, YANG Kehu, ZHOU Wenjie. Evidence Integration Framework of Evidence-based Digital Humanities [J]. Journal of library and information science in agriculture, 2022, 34(11): 38-47.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!