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Robust annotation positioning in digital documents

Published: 01 March 2001 Publication History

Abstract

Increasingly, documents exist primarily in digital form. System designers have recently focused on making it easier to read digital documents, with annotation as an important new feature. But supporting annotation well is difficult because digital documents are frequently modified, making it challenging to correctly reposition annotations in modified versions. Few systems have addressed this issue, and even fewer have approached the problem from the users' point of view. This paper reports the results of two studies examining user expectations for robust annotation positioning in modified documents. We explore how users react to lost annotations, the relationship between types of document modifications and user expectations, and whether users pay attention to text surrounding their annotations. Our results could contribute substantially to effective digital document annotation systems.

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Cited By

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  • (2024)Magic Markup: Maintaining Document-External Markup with an LLMCompanion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming10.1145/3660829.3660836(22-31)Online publication date: 11-Mar-2024
  • (2023)Ten years and a million links: building a global taxonomic library connecting persistent identifiers for names, publications and peopleBiodiversity Data Journal10.3897/BDJ.11.e10791411Online publication date: 14-Sep-2023
  • (2022)Investigating the Use of AR Glasses for Content Annotation on Mobile DevicesProceedings of the ACM on Human-Computer Interaction10.1145/35677276:ISS(430-447)Online publication date: 14-Nov-2022
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Recommendations

Reviews

Maxine Cohen

This paper reports the results of two studies examining user expectations of robust annotation positioning in modified documents. The authors present an interesting case for one of the problems encountered by users as we move our world ever deeper into the electronic management and revision of documents. The authors clearly define the terms needed to better understand the annotation positioning problem. The first issue they address is how digital annotations work. The second issue is how documents are modified. Starting with a discussion of the way paper based annotations work, the authors then relate it to the digital annotation arena. They introduce the concept of an anchor and of a context related to a content area, both of which are needed to create a robust annotation. They then discuss the issue of modification, and present a modification classification scheme describing three types of modifications: deletes, rewords, and moves. They describe what it means when an annotation is “orphaned” (when an online document changes and the link to the annotation is lost). The authors include a good summary of the current research and challenges in the area, including reporting on several studies of users using an electronic annotation system. They acknowledge many of the commercial systems already performing electronic annotations, and describe how they work. They provide a good set of references. Their study extends the work of others further by delving into peoples’ expectations in dealing with annotations, using those expectations to further fine-tune the annotation algorithms. The article contains several interesting and excellent tables that further explain the authors’ results and findings. Two trends seem to emerge from their studies: the greater the percentage of the annotation anchor text found, the more satisfied people are; and the more drastic the modifications to the anchor text, the less satisfied people were when the annotation anchor was found. This second finding was a little surprising. It seems that with significant changes, participants were all right if the annotation was orphaned. Keywords, proper names, and quotations are important factors to figure into the annotation algorithm. Online Computing Reviews Service

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Published In

cover image ACM Conferences
CHI '01: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
March 2001
559 pages
ISBN:1581133278
DOI:10.1145/365024
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 01 March 2001

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Author Tags

  1. annotation
  2. annotation system design
  3. digital
  4. documents
  5. robust

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CHI '01 Paper Acceptance Rate 69 of 352 submissions, 20%;
Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

View all
  • (2024)Magic Markup: Maintaining Document-External Markup with an LLMCompanion Proceedings of the 8th International Conference on the Art, Science, and Engineering of Programming10.1145/3660829.3660836(22-31)Online publication date: 11-Mar-2024
  • (2023)Ten years and a million links: building a global taxonomic library connecting persistent identifiers for names, publications and peopleBiodiversity Data Journal10.3897/BDJ.11.e10791411Online publication date: 14-Sep-2023
  • (2022)Investigating the Use of AR Glasses for Content Annotation on Mobile DevicesProceedings of the ACM on Human-Computer Interaction10.1145/35677276:ISS(430-447)Online publication date: 14-Nov-2022
  • (2022)Spotlights: Designs for Directing Learners' Attention in a Large-Scale Social Annotation PlatformProceedings of the ACM on Human-Computer Interaction10.1145/35555986:CSCW2(1-36)Online publication date: 11-Nov-2022
  • (2021)Test Case Recording using JavaScript for Automation TestingInternational Journal of Recent Technology and Engineering10.35940/ijrte.A5810.051012110:1(153-157)Online publication date: 30-May-2021
  • (2019)SpaceInk: Making Space for In-Context AnnotationsProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology10.1145/3332165.3347934(871-882)Online publication date: 17-Oct-2019
  • (2019)Collaborative Practices with Structured DataProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300330(1-14)Online publication date: 2-May-2019
  • (2018)Maintaining reading experience continuity across e-book revisionsResearch and Practice in Technology Enhanced Learning10.1186/s41039-018-0093-913:1Online publication date: 20-Dec-2018
  • (2017)Semantic Annotation of Heterogeneous Data SourcesProceedings of the 13th International Conference on Semantic Systems10.1145/3132218.3132221(73-80)Online publication date: 11-Sep-2017
  • (2016)Freeform digital ink annotations in electronic documentsComputers and Graphics10.1016/j.cag.2015.10.01455:C(1-20)Online publication date: 1-Apr-2016
  • Show More Cited By

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