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SurvAnnT: Facilitating Community-Led Scientific Surveys and Annotations

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Linking Theory and Practice of Digital Libraries (TPDL 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13541))

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Abstract

A core research activity in many scientific domains concerns gathering data via questionnaire-based surveys. Meanwhile, annotation projects, that require input by field specialists, are invaluable in various research areas. Surveys and annotation projects share inherent similarities, since they both depend on participants who are prompted to answer a set of questions referring to particular artifacts (e.g., text segments). Both tasks are hindered by their dependence on volunteering, often requiring participants of a particular background, thus burdening research conductors to seek suitable ones. In this paper, we present SurvAnnT, a platform that facilitates the creation and management of surveys and annotation projects. SurvAnnT goes beyond existing tools offering customizable gamification aspects to motivate participation, as well as expert finding mechanisms to facilitate the identification of suitable participants.

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Notes

  1. 1.

    SurvAnnT: http://survannt.athenarc.gr.

  2. 2.

    Source code: https://github.com/athenarc/SurvAnnT.

  3. 3.

    Simple questionnaires are represented by null resources.

  4. 4.

    Qualtrics Survey: https://www.qualtrics.com/.

  5. 5.

    Amazon MTurk: https://www.mturk.com.

  6. 6.

    Premise: https://www.premise.com/.

  7. 7.

    Prolific: https://www.prolific.co/.

  8. 8.

    Doccano: https://doccano.herokuapp.com/.

  9. 9.

    Stall catchers: https://stallcatchers.com/about.

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Authors and Affiliations

  1. University of the Peloponnese, Tripoli, Greece

    Anargiros Tzerefos

  2. IMSI-ATHENA RC, Marousi, Greece

    Anargiros Tzerefos, Ilias Kanellos, Serafeim Chatzopoulos, Theodore Dalamagas & Thanasis Vergoulis

Authors
  1. Anargiros Tzerefos
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  2. Ilias Kanellos
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  3. Serafeim Chatzopoulos
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  4. Theodore Dalamagas
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  5. Thanasis Vergoulis
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Corresponding author

Correspondence to Anargiros Tzerefos .

Editor information

Editors and Affiliations

  1. University of Padua, Padua, Italy

    Gianmaria Silvello

  2. Universidad Politécnica de Madrid, Madrid, Spain

    Oscar Corcho

  3. CNR-ISTI – National Research Council, Pisa, Italy

    Paolo Manghi

  4. University of Padua, Padua, Italy

    Giorgio Maria Di Nunzio

  5. Linnaeus University, Växjö, Sweden

    Koraljka Golub

  6. University of Padua, Padua, Italy

    Nicola Ferro

  7. Sapienza University of Rome, Rome, Italy

    Antonella Poggi

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Tzerefos, A., Kanellos, I., Chatzopoulos, S., Dalamagas, T., Vergoulis, T. (2022). SurvAnnT: Facilitating Community-Led Scientific Surveys and Annotations. In: Silvello, G., et al. Linking Theory and Practice of Digital Libraries. TPDL 2022. Lecture Notes in Computer Science, vol 13541. Springer, Cham. https://doi.org/10.1007/978-3-031-16802-4_61

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  • DOI: https://doi.org/10.1007/978-3-031-16802-4_61

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16801-7

  • Online ISBN: 978-3-031-16802-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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