Rights statement: © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in DIS '19 Proceedings of the 2019 on Designing Interactive Systems Conference, 2019 https://dl.acm.org/citation.cfm?id=3322303
Accepted author manuscript, 2.26 MB, PDF document
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Roam-IO
T2 - Engaging With People Tracking Data through an Interactive Physical Data Installation
AU - Houben, Steven
AU - Bengler, Ben
AU - Gavrilov, Daniel
AU - Gallacher, Sarah
AU - Nisi, Valentina
AU - Nunes, Nuno Jardim
AU - Capra, Licia
AU - Rogers, Yvonne
N1 - © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in DIS '19 Proceedings of the 2019 on Designing Interactive Systems Conference, 2019 https://dl.acm.org/citation.cfm?id=3322303
PY - 2019/6/23
Y1 - 2019/6/23
N2 - Newly emerging urban IoT infrastructures are enabling novel ways of sensing how urban spaces are being used. However, the data produced by these systems are largely context-agnostic, making it difficult to discern what patterns and anomalies in the data mean. We propose a hybrid data approach that combines the quantitative data collected from an urban IoT sensing infrastructure with qualitative data contributed by people answering specific kinds of questions in situ. We developed a public installation, Roam-io, to entice and encourage the public to walk-up and answer questions to suggest what the data might represent and enrich it with subjective observations. The findings from an in the wild study on the island of Madeira showed that many passers-by stopped and interacted with Roam-io and attempted to make sense of the data and contribute in situ observations.
AB - Newly emerging urban IoT infrastructures are enabling novel ways of sensing how urban spaces are being used. However, the data produced by these systems are largely context-agnostic, making it difficult to discern what patterns and anomalies in the data mean. We propose a hybrid data approach that combines the quantitative data collected from an urban IoT sensing infrastructure with qualitative data contributed by people answering specific kinds of questions in situ. We developed a public installation, Roam-io, to entice and encourage the public to walk-up and answer questions to suggest what the data might represent and enrich it with subjective observations. The findings from an in the wild study on the island of Madeira showed that many passers-by stopped and interacted with Roam-io and attempted to make sense of the data and contribute in situ observations.
U2 - 10.1145/3322276.3322303
DO - 10.1145/3322276.3322303
M3 - Conference contribution/Paper
SN - 9781450358507
SP - 1157
EP - 1169
BT - DIS '19 Proceedings of the 2019 on Designing Interactive Systems Conference
PB - ACM
CY - New York
ER -