TY - JOUR
T1 - CompanionViz
T2 - Mediated platform for gauging canine health and enhancing human–pet interactions
AU - Nelson, Jonathan K.
AU - Shih, Patrick C.
N1 - Funding Information:
We are grateful to the pet owner and dog participants for their time and invaluable feedback on our study. We also thank the Penn State Department of Information Systems Technology for providing fitbit devices for use in the study. This work was supported by the National Science Foundation under IGERT Award #DGE-1144860, Big Data Social Science, and Pennsylvania State University.
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2017/2/1
Y1 - 2017/2/1
N2 - Advancements in personal data collection and visualization – commonly referred to as the quantified self (QS) movement – allow individuals to self-track health and other attributes. We extend quantified self (QS) concepts to the quantified other (QO) to explore how the use of technology, collection of data on one's pet dog, and personal visualization affect pet owners' understandings of, and relationships with, their pets. We introduce the term Human–pet–computer interaction (HPCI) as the study of how technology can be designed and used to advance human–pet companionships. As an example, we describe CompanionViz, a personal information visualization prototype designed to inform pet owners on their dogs’ caloric inputs/outputs, as well as exercise and movement habits. We present a user study of CompanionViz featuring a twelve-participant survey and one field study, consisting of three unique use cases, and show that by providing pet owners with quantifiable awareness of their dogs’ health and exercise habits using personal visual representations, pet owner–dog bonds can benefit.
AB - Advancements in personal data collection and visualization – commonly referred to as the quantified self (QS) movement – allow individuals to self-track health and other attributes. We extend quantified self (QS) concepts to the quantified other (QO) to explore how the use of technology, collection of data on one's pet dog, and personal visualization affect pet owners' understandings of, and relationships with, their pets. We introduce the term Human–pet–computer interaction (HPCI) as the study of how technology can be designed and used to advance human–pet companionships. As an example, we describe CompanionViz, a personal information visualization prototype designed to inform pet owners on their dogs’ caloric inputs/outputs, as well as exercise and movement habits. We present a user study of CompanionViz featuring a twelve-participant survey and one field study, consisting of three unique use cases, and show that by providing pet owners with quantifiable awareness of their dogs’ health and exercise habits using personal visual representations, pet owner–dog bonds can benefit.
UR - http://www.scopus.com/inward/record.url?scp=84977671240&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84977671240&partnerID=8YFLogxK
U2 - 10.1016/j.ijhcs.2016.04.002
DO - 10.1016/j.ijhcs.2016.04.002
M3 - Article
AN - SCOPUS:84977671240
SN - 1071-5819
VL - 98
SP - 169
EP - 178
JO - International Journal of Human Computer Studies
JF - International Journal of Human Computer Studies
ER -
