A picture is worth a thousand words: Art indexing in electronic databases

Roberts, Helene E.

doi:10.1002/asi.1145.abs

Cited by 10 publications

(4 citation statements)

References 9 publications

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“…This is one of the great challenges in teaching Art History 101. The gap is reflected in the way that searches are made of public art resources (McCorry and Morrison 1995;Roberts 2001;Sundt 2002;Choi and Rasmussen 2003). Including folksonomic terms in museum records would seem a promising way to provide access along facets of interest to the general public.…”

Section: Bridging a Semantic Gapmentioning

confidence: 99%

Exploring the potential for social tagging and folksonomy in art museums: Proof of concept

Trant

2006

New Review of Hypermedia and Multimedia

106

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Documentation of art museum collections has been traditionally written by and for art historians. To make art museum collections broadly accessible, and to enable art museums to engage their communities, means of access need to reflect the perspectives of other groups and communities. Social Tagging (the collective assignment of keywords to resources) and its resulting Folksonomy (the assemblage of concepts expressed in such a cooperatively developed system of classification) offer ways for art museums to engage with their communities and to understand what users of on-line museum collections see as important. Proof of Concept studies at The Metropolitan Museum of Art compared terms assigned by trained cataloguers and untrained cataloguers to existing museum documentation, and explored the potential for social tagging to improve access to museum collections. These preliminary studies, the results of which are reported here, have shown the potential of social tagging and folksonomy to open museum collections to new, more personal meanings. Untrained cataloguers identified content elements not described in formal museum documentation. Results from these tests -the first in the domainprovided validation for exploring social tagging and folksonomy as an access strategy within The Metropolitan Museum, motivation to proceed with a broader inter-institutional collaboration, and input into the development of a multi-institutional collaboration exploring tagging in art museums. Tags assigned by users might help bridge the semantic gap between the professional discourse of the curator and the popular language of the museum visitor. The steve collaboration (http://www.steve.museum) is building on these early studies to develop shared tools and research methods that enable social tagging of art museum collections and explore the utility of folksonomy for providing enhanced access to collections.

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Section: Bridging a Semantic Gapmentioning

confidence: 99%

Exploring the potential for social tagging and folksonomy in art museums: Proof of concept

Trant

2006

New Review of Hypermedia and Multimedia

106

View full text Add to dashboard Cite

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“…With human information needs increasingly extending to visual materials, the issue of describing image information needs becomes more important (Choi & Rasmussen, 2003;Goodrum, 2005;Roberts, 2001). The problem of formulating queries for searching images becomes magnified due to the wordless nature of images (Cleveland & Cleveland, 2009).…”

Section: Role Of Domain Knowledge In Designing Information Retrieval mentioning

confidence: 99%

Role of domain knowledge in developing user‐centered medical‐image indexing

Wang

Erdelez

Allen

et al. 2011

J. Am. Soc. Inf. Sci.

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An efficient and robust medical-image indexing procedure should be user-oriented. It is essential to index the images at the right level of description and ensure that the indexed levels match the user's interest level. This study examines 240 medical-image descriptions produced by three different groups of medical-image users (novices, intermediates, and experts) in the area of radiography. This article reports several important findings: First, the effect of domain knowledge has a significant relationship with the use of semantic image attributes in image-users' descriptions. We found that experts employ more high-level image attributes which require highreasoning or diagnostic knowledge to search for a medical image (Abstract Objects and Scenes) than do novices; novices are more likely to describe some basic objects which do not require much radiological knowledge to search for an image they need (Generic Objects) than are experts. Second, all image users in this study prefer to use image attributes of the semantic levels to represent the image that they desired to find, especially using those Received July 3, 2011; revised September 16, 2011; accepted September 16, 2011 © 2011 ASIS&T • Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/asi.21686 specific-level and scene-related attributes. Third, image attributes generated by medical-image users can be mapped to all levels of the pyramid model that was developed to structure visual information. Therefore, the pyramid model could be considered a robust instrument for indexing medical imagery. IntroductionMedical images provide vital clinical data and are considered a powerful educational resource due to their immediate, informative, and illustrative nature. Medical images can be used by clinicians for their daily practice of medicine, such as making diagnoses, planning treatment, and monitoring responses to therapy as well as for medical education and research (Cleveland & Cleveland, 2009;Kalpathy-Cramer & Hersh, 2010;Müller, Michoux, Bandon, & Geissbuhler, 2004). Past studies have reported significant learning improvements when using medical images during classes and self-education for medical students and residents (Dawes, Vowler, Allen, & Dixon, 2004; KalpathyCramer & Hersh, 2010). A single hospital radiology department alone produced 50,000 images per day in 2006 (Müller , 2007). With the dramatic explosion of digital image collections in medicine, it is important to develop advanced techniques for effective and efficient management of this information, enabling users quick and easy access in a clinically meaningful way.Image information systems (e.g., picture archiving and communication systems) provide rapid access to digitalized film images and allow users to access medical-image databases based on combinations of a patient's identification, visit dates, and study characteristics (e.g., modality and study description) (Müller et al., 2004). However, to fulfill users' various requirements under different contexts of u...

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“…are not designed to locate copies of specific images and so are not suitable for impact assessment. In fact, some experts believe that text queries are difficult or not appropriate to find images (e.g., Brunskill & Jörgensen, 2005; Choi & Rasmussen, 2003; Pu, 2005; Roberts, 2001), and so some image identification technology uses pattern recognition algorithms instead. Nontext image searching is technically possible now and is available online with the image search engine TinEye.…”

Section: Introductionmentioning

confidence: 99%

Can the impact of scholarly images be assessed online? An exploratory study using image identification technology

Kousha

Thelwall

Rezaie

2010

J. Am. Soc. Inf. Sci.

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The web contains a huge number of digital pictures. For scholars publishing such images it is important to know how well used their images are, but no method seems to have been developed for monitoring the value of academic images. In particular, can the impact of scientific or artistic images be assessed through identifying images copied or reused on the Internet? This article explores a case study of 260 NASA images to investigate whether the TinEye search engine could theoretically help to provide this information.The results show that the selected pictures had a median of 11 online copies each. However, a classification of 210 of these copies reveals that only 1.4% were explicitly used in academic publications, reflecting research impact, and the majority of the NASA pictures were used for informal scholarly (or educational) communication (37%). Additional analyses of world famous paintings and scientific images about pathology and molecular structures suggest that image contents are important for the type and extent of image use. Although it is reasonable to use statistics derived from TinEye for assessing image reuse value, the extent of its image indexing is not known. IntroductionScientists are increasingly evaluated by the number of journal articles that they produce or the number of citations that their work attracts (e.g., Moed, 2005). This is Received March 3, 2010; revised April 25, 2010; accepted April 26, 2010 © 2010 ASIS&T • Published online 2 June 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/asi.21370 not applicable to the arts and humanities, however, because of the wide variety of outputs that they routinely create. Books and monographs are often seen as the prime output in the humanities (see Nederhof, 2006;Huang & Chang, 2008), whereas artists might be judged by the prestige of galleries exhibiting their work, whether a piece has been performed by internationally recognized performers or from where they have received commissions. Currently, however, a significant number of scientists engage in some work akin to the arts and humanities: Stephen Hawking and many other scientists have authored popular books; Martyn Poliakoff (a chemist) is regularly seen in the popular science Nottingham Science YouTube channel, and NASA maintains a huge online archive of free space-related images. These activities all seem valuable for the popularization of science and for science education, yet because the outputs are atypical for researchers, their creators may be insufficiently recognized for their efforts, undermining their motivation to continue with similar projects in the future.The Web has created new opportunities for publishing and sharing digital images for research, artistic, or social activities. The enormous increase in the number of digital images on the Internet has coincided with the development of many easy ways to access, duplicate, or modify them. Thus, it is important to assess the impact of online digital images as a type of nonstandard research output. Whereas mo...

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A picture is worth a thousand words: Art indexing in electronic databases

Cited by 10 publications

References 9 publications

Exploring the potential for social tagging and folksonomy in art museums: Proof of concept

Exploring the potential for social tagging and folksonomy in art museums: Proof of concept

Role of domain knowledge in developing user‐centered medical‐image indexing

Can the impact of scholarly images be assessed online? An exploratory study using image identification technology

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