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Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE): Questionnaire data and timing-and-tracking data gathered from digital arts exhibition visitors

Markellou, Marina; Salmouka, Foteini, 2022, "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE): Questionnaire data and timing-and-tracking data gathered from digital arts exhibition visitors", https://doi.org/10.17903/FK2/39NZQM, Κατάλογος Δεδομένων SoDaNet, First version, UNF:6:yghLr4AfcLli0M4ikMC9Kw== [fileUNF]
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The data presented in this data project were collected in the context of the research project “AI TRACE - Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience”. The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.)under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project Number: 782). AI TRACE aimed at developing an ethically compliant behavioural analysis and visualization tool in the form of a metalanguage that can be used in the museum sector to track, analyse and present data collected from exhibition visitors in the form of a personalized 3D digital object. AI TRACE showcases Artificial Intelligence subsystems. The data presented in this data project were collected during the Preparatory Activity event that took place in October 2021 during the 17th edition of the Athens Digital Arts Festival (ADAF). The research activity was hosted at the new premises of the Museum of Modern Greek Culture, at a specially designed exhibition space. The purpose of this activity was to collect data for methodological testing and for feeding the AI subsystem. The data files derived from the research activities and provided here are:
  1. Data that was gathered from a pre-visit questionnaire which was completed by 231 survey participants. The questionnaire explores visitors' motivations for visiting and preferences of a digital arts exhibition, their relationship with digital arts, their mood and attitude before the visit, and certain demographic characteristics. For the purpose of the research, visitors of the Athens Digital Arts Festival who voluntarily participated in the survey were approached. The dataset can be used to analyse various characteristics of museum visitors, such as their motivation to visit, their interests and their relationship with art, in relation to their personal characteristics (gender, age, status).
  2. Timing-and-tracking (T&T) data -more specifically time spent in each exhibit and trajectory- which were extracted from video recordings in the exhibition space. Regular festival visitors were recruited at the entrance of the exhibition area by the research assistants. Participants (N=273) were asked to sign an informed consent form before filling the online anonymous questionnaire and entering the exhibition space. A custom-made software was used to blur their faces during video recording for data anonymization purposes. The tracking data were extracted via BORIS (Behavioral Observation Research Interactive Software), an open-source event logging software for video/audio coding and live observations that is developed by the University of Torino. The datasets can be used to analyse visitors’ behavior in relation to demographic characteristics, their motivations, interests and relation to arts, as well as their pre-visit mood and attitudes.
  3. The data file containing both questionnaire data and timing-and-tracking (T&T) data for a subset of the sample (N=223). This data can be used in combination to analyse the behaviour of museum visitors in relation to their demographic characteristics, motivations for visiting, their preferences and their relationship with digital arts, as well as in relation to their mood and attitude before the visit.
Social Sciences
DIGITAL ARTS, MUSEUM STUDIES, VISUALISATION TOOL, MUSEUM VISITORS, ATHENS, GREECE, MUSEUMS, CULTURAL FACILITIES, CULTURAL EVENTS, CULTURAL RESOURCES, ARTIFICIAL INTELLIGENCE, ARTISTIC ACTIVITIES, EXHIBITIONS, WORKS OF ART, ETHICS, VISITS TO RECREATIONAL FACILITIES, VISUAL ARTS
Salmouka, F. (2022). Creating a data representation tool for museum visitor research: museological and audience perspective. EUTIC 2022: In the Intersection of Art, Science and Technology: Dialogos Between Humans and Machines, Ionian University, Corfu, Greece. (forthcoming)
Citation Metadata  
doi:10.17903/FK2/39NZQM
2022-12-15
Quantitative Study with Data
Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE): Questionnaire data and timing-and-tracking data gathered from digital arts exhibition visitors
AI TRACE
ekke-1-0062-ΕΝ
Markellou, Marina
(Panteion University, Department of Communication, Media and Culture)
- ORCID:
https://orcid.org/0000-0002-3744-2801
https://www.researchgate.net/profile/Marina-Markellou

Salmouka, Foteini
(Panteion University, Department of Communication, Media and Culture)
- ORCID:
https://orcid.org/0000-0003-2775-5748
https://www.researchgate.net/profile/Foteini-Salmouka

SoDaNet - EKKE

Use email button above to contact.

Markellou, Marina
(Panteion University, Department of Communication, Media and Culture)


The data presented in this data project were collected in the context of the research project “AI TRACE - Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience”. The research project was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.)under the “2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project Number: 782). AI TRACE aimed at developing an ethically compliant behavioural analysis and visualization tool in the form of a metalanguage that can be used in the museum sector to track, analyse and present data collected from exhibition visitors in the form of a personalized 3D digital object. AI TRACE showcases Artificial Intelligence subsystems. The data presented in this data project were collected during the Preparatory Activity event that took place in October 2021 during the 17th edition of the Athens Digital Arts Festival (ADAF). The research activity was hosted at the new premises of the Museum of Modern Greek Culture, at a specially designed exhibition space. The purpose of this activity was to collect data for methodological testing and for feeding the AI subsystem. The data files derived from the research activities and provided here are:
  1. Data that was gathered from a pre-visit questionnaire which was completed by 231 survey participants. The questionnaire explores visitors' motivations for visiting and preferences of a digital arts exhibition, their relationship with digital arts, their mood and attitude before the visit, and certain demographic characteristics. For the purpose of the research, visitors of the Athens Digital Arts Festival who voluntarily participated in the survey were approached. The dataset can be used to analyse various characteristics of museum visitors, such as their motivation to visit, their interests and their relationship with art, in relation to their personal characteristics (gender, age, status).
  2. Timing-and-tracking (T&T) data -more specifically time spent in each exhibit and trajectory- which were extracted from video recordings in the exhibition space. Regular festival visitors were recruited at the entrance of the exhibition area by the research assistants. Participants (N=273) were asked to sign an informed consent form before filling the online anonymous questionnaire and entering the exhibition space. A custom-made software was used to blur their faces during video recording for data anonymization purposes. The tracking data were extracted via BORIS (Behavioral Observation Research Interactive Software), an open-source event logging software for video/audio coding and live observations that is developed by the University of Torino. The datasets can be used to analyse visitors’ behavior in relation to demographic characteristics, their motivations, interests and relation to arts, as well as their pre-visit mood and attitudes.
  3. The data file containing both questionnaire data and timing-and-tracking (T&T) data for a subset of the sample (N=223). This data can be used in combination to analyse the behaviour of museum visitors in relation to their demographic characteristics, motivations for visiting, their preferences and their relationship with digital arts, as well as in relation to their mood and attitude before the visit.


Social Sciences
DIGITAL ARTS

MUSEUM STUDIES

VISUALISATION TOOL

MUSEUM VISITORS

ATHENS

GREECE

MUSEUMS
(ELSST)
https://elsst.cessda.eu

CULTURAL FACILITIES
(ELSST)
https://elsst.cessda.eu

CULTURAL EVENTS
(ELSST)
https://elsst.cessda.eu

CULTURAL RESOURCES
(ELSST)
https://elsst.cessda.eu

ARTIFICIAL INTELLIGENCE
(ELSST)
https://elsst.cessda.eu

ARTISTIC ACTIVITIES
(ELSST)
https://elsst.cessda.eu

EXHIBITIONS
(ELSST)
https://elsst.cessda.eu

WORKS OF ART
(ELSST)
https://elsst.cessda.eu

ETHICS
(ELSST)
https://elsst.cessda.eu

VISITS TO RECREATIONAL FACILITIES
(ELSST)
https://elsst.cessda.eu

VISUAL ARTS
(ELSST)
https://elsst.cessda.eu

Cultural activities and participation; Leisure, tourism and sport; Social behaviour and attitudes
Salmouka, F. (2022). Creating a data representation tool for museum visitor research: museological and audience perspective. EUTIC 2022: In the Intersection of Art, Science and Technology: Dialogos Between Humans and Machines, Ionian University, Corfu, Greece. (forthcoming)

Markellou, M. & Salmouka, F. (2023). Emerging Technologies, Digital Arts and the Public. Proceedings of scientific conference of the AI TRACE research project, 19-20 December 2022. Athens. (In Greek)
doi:
10.17903/ai_trace
https://doi.org/10.17903/ai_trace

English
Hellenic Foundation for Research and Innovation (H.F.R.I.)
“2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers” (Project Number: 782)

Social Data Network
(SoDaNet)
https://sodanet.gr



2022-12-07
Klironomos, Nicolas
2022-11-29
Start: 2021-10-21
End: 2021-10-18

Start: 2021-10-21
End: 2021-10-18

SPSS
Version: 28

Research data
First version
y
n
Geospatial Metadata  
Greece
Attica
Athens
Museum of Modern Greek Culture (MNEP)

Museum
Social Science and Humanities Metadata  
Digital arts exhibition visitors of any age, occupation and ethnicity.
Longitudinal: Cohort/Event-based
Non-probability: Availability
Self-administered questionnaire: Web-based (CAWI); Other
Structured questionnaire; Technical instrument(s)
Data processing and cleaning with SPSS v.28
Individual
Questionnaire data collected from visitors to the digital arts exhibition: 231 questionnaires Tracking data collected from digital arts visitors: 273 people Questionnaire and tracking data: 223 persons

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Metadata will be made available under licence Creative Commons Attribution 4.0 International Public License

1) AI TRACE Tracking data.rar (Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in .csv format) : Open Access.
2) ekke-1-0062-EN_Codebook.pdf (Codebook of Timing-and-Tracking Datafile of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)") : Open Access.
3) ekke-1-0062-EN_Consent_Form_EN.pdf (Informed Consent Form for the Preparatory Activity of the AI TRACE pilot) : Open Access.
4) ekke-1-0062-EN_M.tab (Questionnaire & Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in SPSS format) : Open Access.
5) ekke-1-0062-EN_TD.tab (Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in SPSS format) : Open Access.
6) ekke-1-0062_EN.tab (Data file of the questionnaire for: Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)) : Open Access.
7) ekke-1-0062_EN_questionnaire.pdf (Digital Arts exhibition visitor questionnaire) : Open Access.

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1) AI TRACE Tracking data.rar (Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in .csv format) : Open Access.---2) ekke-1-0062-EN_Codebook.pdf (Codebook of Timing-and-Tracking Datafile of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)") : Open Access.---3) ekke-1-0062-EN_Consent_Form_EN.pdf (Informed Consent Form for the Preparatory Activity of the AI TRACE pilot) : Open Access.---4) ekke-1-0062-EN_M.tab (Questionnaire & Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in SPSS format) : Open Access.---5) ekke-1-0062-EN_TD.tab (Timing-and-Tracking Data of the data project: "Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)" in SPSS format) : Open Access.---6) ekke-1-0062_EN.tab (Data file of the questionnaire for: Synaesthetic Engagement of Artificial Intelligence with Digital Arts and its Audience (AI TRACE)) : Open Access.---7) ekke-1-0062_EN_questionnaire.pdf (Digital Arts exhibition visitor questionnaire) : Open Access.---
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