Understanding subjects contained in Dunhuang mural images for deep semantic annotation
| Pages | 333-353 |
| DOI | https://doi.org/10.1108/JD-03-2017-0033 |
| Published date | 12 March 2018 |
| Date | 12 March 2018 |
| Author | Xiaoguang Wang,Ningyuan Song,Lu Zhang,Yanyu Jiang |
| Subject Matter | Library & information science,Records management & preservation,Document management,Classification & cataloguing,Information behaviour & retrieval,Collection building & management,Scholarly communications/publishing,Information & knowledge management,Information management & governance,Information management,Information & communications technology,Internet |
Understanding subjects contained
in Dunhuang mural images for
deep semantic annotation
Xiaoguang Wang and Ningyuan Song
School of Information Management, Wuhan University, Wuhan, China
Lu Zhang
Hunan Radio and Television University, Changsha, China, and
Yanyu Jiang
School of Information Management, Wuhan University, Wuhan, China
Abstract
Purpose –The purpose of this paper is to understand the subjects contained in the Dunhuang mural images
as well as their relation structures.
Design/methodology/approach –This paper performed content analysis based on Panofsky’s theory and
237 research papers related to the Dunhuang mural images. UNICET software was also used to study the
correlation structures of subject network.
Findings –The results show that the three levels of subject have all captured the attention of Dunhuang
mural researchers, the iconology occupy the critical position in the whole image study, and the correlation
between iconography and iconology was strong. Further analysis reveals that cultural development,
production, and power and domination have high centralities in the subject network.
Research limitations/implications –The research samples come from three major Chinese journal
databases. However, there are still many authoritative monographs and foreign publications about the
Dunhuang murals which are not included in this study.
Originality/value –The results uncover the subject hierarchies and structures contained in the Dunhuang
murals from the angle of image scholarship which express scholars’intention and contribute to the deep
semantic annotation on digital Dunhuang mural images.
Keywords Semantics, Statistical analysis, Indexing, Information science and documentation,
Document image processing, Information modelling
Paper type Research paper
1. Introduction
Image annotation and indexing are basic approaches in the organization and management
of image resources. In this paper, only graphic images are considered; other recognized
members of the image family such as optical, perceptual, mental, and verbal images
(Mitchell, 1984) are not taken into account. Library and information services usually focus
on using metadata to describe image resources, providing access to the resources using
subject headings. Image annotation, also known as deep image indexing (Clarke, 2015),
delves further into the image itself, and focuses on the contents and semantic structure
revealed in images. Such annotation information is critical when domain experts search
these materials. Taking the Dunhuang murals as an example, the need for such deep
semantic annotation (DSA) of images is perceptible. The Dunhuang grottoes is an
internationally recognized cultural heritage site where the most well-known group is the
Mogao caves, located south-east of the Dunhuang oasis on the Silk Road, in Gansu province,
China. With 492 caves, the total size of the murals reaches more than 45,000 square meters
Journal of Documentation
Vol. 74 No. 2, 2018
pp. 333-353
© Emerald PublishingLimited
0022-0418
DOI 10.1108/JD-03-2017-0033
Received 13 March 2017
Revised 28 September 2017
Accepted 30 September 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0022-0418.htm
The authors thank all who helped to give valuable suggestions and comments. This research is funded
by the Major State Basic Research Development Program of China (904171200), and the Key Research
Center Fund of Chinese Ministry of Education (16JJD870002).
333
Dunhuang
mural images
for DSA
(Roderick and Seigo, 1995). It is regarded as a magnificent mural art palace, a gallery with
1,600 years of art history, and a grand “Library”on the wall. The numerous huge number of
Dunhuang murals contain very exceedingly rich content, making this site a significant
academic treasure with an abundance of vivid materials depicting various aspects of
medieval politics, economics, culture, arts, religion, ethnic relations, and daily dress in
Western China (http://whc.unesco.org/en/list/440). Merely describing a mural painting by its
title, location, year, size, techniques, genre, and a number of subject headings is too minimal
for exploring this cultural, art, and historical treasure. With high resolution digitization and
the emerging semantic annotation technologies, it is now possible to explore new, more
creative, semantic annotation methods for these art works. DSA is one such approach that
has emerged in recent years (Figure 1).
With the rise of digital humanities and the advancement of semantic technologies, the
traditional iconology research modes were also changed. Researchers hope to apply
automatic methods to discover the deep linkages and to integrate information or messages
embedded in images, in order to reach the goal of building a global digital cultural heritage
resource network and a novel digital humanities research infrastructure. This objective also
creates new demands for DSA of images.
DSA of images overlaps with conventional subject indexing, yet has its uniqueness.
First, DSA of images employs precise domain terminologies and natural language to reveal,
as comprehensively as possible, the multi-layered information embedded in images. This is
different from expressing the subject of an image with one or a number of keywords or
subject headings. Second, similar to a back-of-the-book indexing that exposes topics and
entities in the contents, DSA attempts to expose the stories/messages/information contained
in an image along with accurate positioning of these elements within an image.
Nevertheless, instead of organizing the analyzed results (the index terms) alphabetically,
Notes: The map of Mounts Wutai from Cave 61 at the Mogao Caves, Dunhuang, Gansu province,
China, dated to the tenth century and depicting scenery and humans in Mount Wutai, Shanxi
province. The picture is 13.45 meters long and 3.42 meters wide
Figure 1.
Picture of
Mounts Wutai
334
JD
74,2
To continue reading
Request your trial