Abstract
In this paper, we present the VAST Collaborative, Multimodal, Web Annotation Tool. It is a collaborative, web-based annotation tool built upon the Ellogon infrastructure, adapted to the content creation and annotation needs of digital cultural heritage. With the help of an annotation methodology and guidelines, the tool has been used to analyse and annotate intangible artifacts (mainly narratives) with moral values. This paper presents the tool and its capabilities, and an evaluation study for assessing its usability.
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Notes
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https://platform.vast-project.eu/ .
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https://platform.vast-project.eu/ .
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The VAST Semantic Annotation Platform: https://github.com/vast-project/ellogon-annotation-tool.
References
Aljabri, M., AlAmir, M., AlGhamdi, M., Abdel-Mottaleb, M., Collado-Mesa, F.: Towards a better understanding of annotation tools for medical imaging: a survey. Multimedia Tools Appli. 81(18), 25877–25911 (2022). https://doi.org/10.1007/s11042-022-12100-1
Apollonio, F.I., Gaiani, M., Bertacchi, S.: Managing cultural heritage with integrated services platform. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2019)
Arampatzakis, V., et al.: Art3mis: ray-based textual annotation on 3d cultural objects. In: CAA 2021 International Conference “Digital Crossroads” (2021)
Bontcheva, K., et al.: Gate teamware: a web-based, collaborative text annotation framework. Lang. Resour. Eval. 47(4), 1007–1029 (2013)
Brooke, J.: SUS: a retrospective. J. Usability Stud. 8(2), 29–40 (2013)
Cassidy, S., Schmidt, T.: Tools for Multimodal Annotation, pp. 209–227. Springer Netherlands, Dordrecht (2017). https://doi.org/10.1007/978-94-024-0881-2_7
de Castilho, R.E., Biemann, C., Gurevych, I., Yimam, S.M.: Webanno: a flexible, web-based annotation tool for clarin. In: Proceedings of the CLARIN Annual Conference (CAC) 2014 (Oct 2014)
Ferrara, A., Montanelli, S., Ruskov, M.: Detecting the semantic shift of values in cultural heritage document collections (short paper). In: Damiano, R., Ferilli, S., Striani, M., Silvello, G. (eds.) Proceedings of the 1st Workshop on Artificial Intelligence for Cultural Heritage, pp. 35–43. No. 3286 in CEUR Workshop Proceedings, Aachen (2022). https://ceur-ws.org/Vol-3286/04_paper.pdf
Garozzo, R., Murabito, F., Santagati, C., Pino, C., Spampinato, C.: Culto: An ontology-based annotation tool for data curation in cultural heritage. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 42, 267–274 (2017)
Gaur, E., Saxena, V., Singh, S.K.: Video annotation tools: A review. In: 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), pp. 911–914 (2018). https://doi.org/10.1109/ICACCCN.2018.8748669
Hornbæk, K., Hertzum, M.: Technology acceptance and user experience: A review of the experiential component in hci, vol. 24(5) (Oct 2017). https://doi.org/10.1145/3127358, https://doi.org/10.1145/3127358
Katakis, I.M., Petasis, G., Karkaletsis, V.: CLARIN-EL web-based annotation tool. In: Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016), pp. 4505–4512. European Language Resources Association (ELRA), Portorož, Slovenia (May 2016). https://aclanthology.org/L16-1713
Lewis, J.R.: The system usability scale: past, present, and future. Inter. J. Hum.-Comput. Interact. 34(7), 577–590 (2018). https://doi.org/10.1080/10447318.2018.1455307
Neves, M., Ševa, J.: An extensive review of tools for manual annotation of documents. Briefings Bioinform. 22(1), 146–163 (2019). https://doi.org/10.1093/bib/bbz130
Ntogramatzis, A.F., Gradou, A., Petasis, G., Kokol, M.: The ellogon web annotation tool: Annotating moral values and arguments. In: Proceedings of the Thirteenth Language Resources and Evaluation Conference, pp. 3442–3450. European Language Resources Association, Marseille, France (Jun 2022), https://aclanthology.org/2022.lrec-1.368
Pande, B., Padamwar, K., Bhattacharya, S., Roshan, S., Bhamare, M.: A review of image annotation tools for object detection. In: 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC), pp. 976–982 (2022). https://doi.org/10.1109/ICAAIC53929.2022.9792665
Stenetorp, P., Pyysalo, S., Topić, G., Ohta, T., Ananiadou, S., Tsujii, J.: Brat: a web-based tool for nlp-assisted text annotation. In: Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics, pp. 102–107. Association for Computational Linguistics (2012)
Sweller, J., van Merriënboer, J.J.G., Paas, F.: Cognitive architecture and instructional design: 20 Years Later. Educ. Psycho. Rev. 31(2), 261–292 (2019). https://doi.org/10.1007/s10648-019-09465-5, http://link.springer.com/10.1007/s10648-019-09465-5
Tan, L.: A survey of nlp annotation platforms (2020). https://github.com/alvations/annotate-questionnaire
Theodosiou, Z., Georgiou, O., Tsapatsoulis, N., Kounoudes, A., Milis, M.: Annotation of cultural heritage documents based on XML dictionaries and data clustering. In: Ioannides, M., Fellner, D., Georgopoulos, A., Hadjimitsis, D.G. (eds.) EuroMed 2010. LNCS, vol. 6436, pp. 306–317. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16873-4_23
Tkachenko, M., Malyuk, M., Holmanyuk, A., Liubimov, N.: Label Studio: Data labeling software (2020-2022). https://github.com/heartexlabs/label-studio, open source software
Tomašević, D., Wells, S., Ren, I.Y., Volk, A., Pesek, M.: Exploring annotations for musical pattern discovery gathered with digital annotation tools. J. Math. Music 15(2), 194–207 (2021). https://doi.org/10.1080/17459737.2021.1943026
Acknowledgments
The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme, in the context of VAST project, under grant agreement No 101004949. This paper reflects only the view of the authors and the European Commission is not responsible for any use that may be made of the information it contains.
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Petasis, G., Ruskov, M., Gradou, A., Kokol, M. (2024). The VAST Collaborative Multimodal Annotation Platform: Annotating Values. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 802. Springer, Cham. https://doi.org/10.1007/978-3-031-45651-0_21
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