skip to main content
10.1145/3594739.3605101acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
short-paper

ARDUOUS: Tutorial on Annotation of useR Data for UbiquitOUs Systems - Developing a Data Annotation Protocol

Published:08 October 2023Publication History

ABSTRACT

Data annotation is key to a large number of fields, including ubiquitous computing. Documenting the quality and extent of annotation is increasingly recognised as an important aspect of understanding the validity, biases and limitations of systems built using this data: hence, it is also relevant to regulatory and compliance needs and outcomes. However, the process of annotation often receives little attention, and is characterised in the literature as “under-described” and “invisible work”. In this tutorial, we bring together existing resources and methods to present a framework for the iterative development and evaluation of an annotation protocol, from requirements gathering, setting scope, development, documentation, piloting and evaluation, through to scaling-up annotation processes for a production annotation process. We also explore the potential of semi-supervised approaches and state-of-the-art methods such as the use of generative AI in supporting annotation workflows, and how such approaches are validated and their strengths and weaknesses characterised. This tutorial is designed to be suitable for people from a wide range of backgrounds, as annotation can be understood as a highly interdisciplinary task and often requires collaboration with subject matter experts from relevant fields. Participants will trial and evaluate a selection of annotation interfaces and walk through the process of evaluating the outcomes. By the end of the workshop, participants will develop a deeper understanding of the task of developing an annotation protocol and aspects of the requirements and context which should be taken into account.

Presentations and code from this event will be shared openly on a Github repository.

References

  1. Artificial Intelligence Act. 2021. Proposal for a regulation of the European Parliament and the Council laying down harmonised rules on Artificial Intelligence (Artificial Intelligence Act) and amending certain Union legislative acts. EUR-Lex-52021PC0206 (2021).Google ScholarGoogle Scholar
  2. Patrícia Bota, Joana Silva, Duarte Folgado, and Hugo Gamboa. 2019. A semi-automatic annotation approach for human activity recognition. Sensors 19, 3 (2019), 501.Google ScholarGoogle ScholarCross RefCross Ref
  3. Karine Lacourse, Ben Yetton, Sara Mednick, and Simon C. Warby. 2020. Massive online data annotation, crowdsourcing to generate high quality sleep spindle annotations from EEG data. Scientific Data 7, 1 (2020), 190. https://doi.org/10.1038/s41597-020-0533-4Google ScholarGoogle ScholarCross RefCross Ref
  4. Tanushree Mitra, C. J. Hutto, and Eric Gilbert. 2015. Comparing Person- and Process-Centric Strategies for Obtaining Quality Data on Amazon Mechanical Turk. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (Seoul, Republic of Korea) (CHI ’15). Association for Computing Machinery, New York, NY, USA, 1345–1354. https://doi.org/10.1145/2702123.2702553Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Janis Pagel, Nils Reiter, Ina Rösiger, and Sarah Schulz. 2018. A unified text annotation workflow for diverse goals. In Sandra Kübler/Heike Zinsmeister (Hg.), Proceedings of the Workshop on Annotation in Digital Humanities, co-located with ESSLLI. 31–36.Google ScholarGoogle Scholar
  6. Teodor Stoev and Kristina Yordanova. 2021. BehavE: Behaviour Understanding Through Automated Generation of Situation Models. In KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI, Virtual Event, September 27–October 1, 2021, Proceedings. Springer, 362–369.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Emma L. Tonkin and Kristina Yordanova. 2020. ARDUOUS 2020: 4th International Workshop on Annotation of useR Data for UbiquitOUs Systems – Welcome and Committees. In 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE Computer Society, Los Alamitos, CA, USA, 1–2. https://doi.org/10.1109/PerComWorkshops48775.2020.9156077Google ScholarGoogle ScholarCross RefCross Ref
  8. Ding Wang, Shantanu Prabhat, and Nithya Sambasivan. 2022. Whose AI Dream? In Search of the Aspiration in Data Annotation.. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI ’22). Association for Computing Machinery, New York, NY, USA, Article 582, 16 pages. https://doi.org/10.1145/3491102.3502121Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Jingru Yang, Ju Fan, Zhewei Wei, Guoliang Li, Tongyu Liu, and Xiaoyong Du. 2018. Cost-effective data annotation using game-based crowdsourcing. Proceedings of the VLDB Endowment 12, 1 (2018), 57–70.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Kristina Yordanova and Adeline Paiement. 2018. PerCom Workshops 2018 Committees. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). i–ii. https://doi.org/10.1109/PERCOMW.2018.8480146Google ScholarGoogle ScholarCross RefCross Ref
  11. Kristina Yordanova, Adeline Paiement, Max Schröder, Emma L. Tonkin, Przemysław Woznowski, Carl Magnus Olsson, Joseph Rafferty, and Timo Sztyler. 2018. Challenges in annotation of user data for ubiquitous systems: Results from the 1st arduous workshop. CoRR abs/1803.05843 (2018). https://doi.org/10.48550/arXiv.1803.05843 arxiv:1803.05843 [cs.CY]Google ScholarGoogle ScholarCross RefCross Ref
  12. Kristina Yordanova, Emma L. Tonkin, and Adeline Paiement. 2019. ARDUOUS 2019 – 3rd International Workshop on Annotation of user Data for Ubiquitous Systems – Welcome and Committees. In 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE Computer Society, Los Alamitos, CA, USA, 1–2. https://doi.org/10.1109/PERCOMW.2019.8730683Google ScholarGoogle ScholarCross RefCross Ref
  13. Kristina Yordanova, Emma L. Tonkin, and Teodor Stoev. 2021. ARDUOUS 2021: 5th International Workshop on Annotation of useR Data for UbiquitOUs Systems – Welcome and Committees. In 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). 1–2. https://doi.org/10.1109/PerComWorkshops51409.2021.9430959Google ScholarGoogle ScholarCross RefCross Ref
  14. Kristina Yordanova, Emma L. Tonkin, and Teodor Stoev. 2022. Annotation of User Data for Ubiquitous Systems – Welcome and Committees. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE Computer Society, Los Alamitos, CA, USA, i–ii. https://doi.org/10.1109/PerComWorkshops53856.2022.9767338Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. ARDUOUS: Tutorial on Annotation of useR Data for UbiquitOUs Systems - Developing a Data Annotation Protocol

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          UbiComp/ISWC '23 Adjunct: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
          October 2023
          822 pages
          ISBN:9798400702006
          DOI:10.1145/3594739

          Copyright © 2023 ACM

          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 the author(s) 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].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 8 October 2023

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • short-paper
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate764of2,912submissions,26%

          Upcoming Conference

        • Article Metrics

          • Downloads (Last 12 months)44
          • Downloads (Last 6 weeks)6

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format .

        View HTML Format