The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers

Stephen M. Mattingly; Julie M. Gregg; Pino Audia; Ayse Elvan Bayraktaroglu; Andrew T. Campbell; Nitesh V. Chawla; Vedant Das Swain; Munmun De Choudhury; Sidney K. D'Mello; Anind K. Dey; Ge Gao; Krithika Jagannath; Kaifeng Jiang; Suwen Lin; Qiang Liu; Gloria Mark; Gonzalo J. Martinez; Kizito Masaba; Shayan Mirjafari; Edward Moskal; Raghu Mulukutla; Kari Nies; Manikanta D. Reddy; Pablo Robles-Granda; Koustuv Saha; Anusha Sirigiri; Aaron Striegel

doi:10.1145/3290607.3299041

The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers

Stephen M. Mattingly^*
, Julie M. Gregg
, Pino Audia
, Ayse Elvan Bayraktaroglu
, Andrew T. Campbell
, Nitesh V. Chawla
, Vedant Das Swain
, Munmun De Choudhury
, Sidney K. D'Mello
, Anind K. Dey
, Ge Gao
, Krithika Jagannath
, Kaifeng Jiang
, Suwen Lin
, Qiang Liu
, Gloria Mark
, Gonzalo J. Martinez
, Kizito Masaba
, Shayan Mirjafari
, Edward Moskal

Raghu Mulukutla, Kari Nies, Manikanta D. Reddy, Pablo Robles-Granda, Koustuv Saha, Anusha Sirigiri, Aaron Striegel

^*Bu çalışma için yazışmadan sorumlu yazar

University of Notre Dame
University of Colorado Boulder
Dartmouth College
University of California at Irvine
Georgia Institute of Technology
University of Washington
Ohio State University
University of Texas at Austin
Carnegie Mellon University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

67 Atıf (Scopus)

Özet

The Tesserae project investigates how a suite of sensors can measure workplace performance (e.g., organizational citizenship behavior), psychological traits (e.g., personality, affect), and physical characteristics (e.g., sleep, activity) over one year. We enrolled 757 information workers across the U.S. and measure heart rate, physical activity, sleep, social context, and other aspects through smartwatches, a phone agent, beacons, and social media. We report challenges that we faced with enrollment, privacy, and incentive structures while setting up such a long-term multimodal large-scale sensor study. We discuss the tradeoffs of remote versus in-person enrollment, and showed that directly paid, in-person enrolled participants are more compliant overall compared to remotely-enrolled participants. We find that providing detailed information regarding privacy concerns up-front is highly beneficial. We believe that our experiences can benefit other large sensor projects as this field grows.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
Yayınlayan	Association for Computing Machinery
ISBN (Elektronik)	9781450359719
DOI'lar	https://doi.org/10.1145/3290607.3299041
Yayın durumu	Yayınlandı - 2 May 2019
Harici olarak yayınlandı	Evet
Etkinlik	2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 - Glasgow, United Kingdom Süre: 4 May 2019 → 9 May 2019

Yayın serisi

Adı	Conference on Human Factors in Computing Systems - Proceedings

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
Ülke/Bölge	United Kingdom
Şehir	Glasgow
Periyot	4/05/19 → 9/05/19

Bibliyografik not

Publisher Copyright:
© 2019 Copyright held by the owner/author(s). ACM

Finansman

This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via IARPA Contract No. 2017-17042800007. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein.

Finansörler	Finansör numarası
Intelligence Advanced Research Projects Activity	2017-17042800007

Belgeye Erişim

10.1145/3290607.3299041

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Mattingly, S. M., Gregg, J. M., Audia, P., Bayraktaroglu, A. E., Campbell, A. T., Chawla, N. V., Swain, V. D., De Choudhury, M., D'Mello, S. K., Dey, A. K., Gao, G., Jagannath, K., Jiang, K., Lin, S., Liu, Q., Mark, G., Martinez, G. J., Masaba, K., Mirjafari, S., ... Striegel, A. (2019). The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers. In CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems Makale 3299041 (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3290607.3299041

Mattingly, Stephen M. ; Gregg, Julie M. ; Audia, Pino et al. / The Tesserae project : Large-scale, longitudinal, in situ, multimodal sensing of information workers. CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2019. (Conference on Human Factors in Computing Systems - Proceedings).

@inproceedings{fa1db2a89d444fba8ab2653952be6ac6,

title = "The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers",

abstract = "The Tesserae project investigates how a suite of sensors can measure workplace performance (e.g., organizational citizenship behavior), psychological traits (e.g., personality, affect), and physical characteristics (e.g., sleep, activity) over one year. We enrolled 757 information workers across the U.S. and measure heart rate, physical activity, sleep, social context, and other aspects through smartwatches, a phone agent, beacons, and social media. We report challenges that we faced with enrollment, privacy, and incentive structures while setting up such a long-term multimodal large-scale sensor study. We discuss the tradeoffs of remote versus in-person enrollment, and showed that directly paid, in-person enrolled participants are more compliant overall compared to remotely-enrolled participants. We find that providing detailed information regarding privacy concerns up-front is highly beneficial. We believe that our experiences can benefit other large sensor projects as this field grows.",

keywords = "Phone agent, Privacy, Sensors, Smartwatches, Social media, Stress",

author = "Mattingly, \{Stephen M.\} and Gregg, \{Julie M.\} and Pino Audia and Bayraktaroglu, \{Ayse Elvan\} and Campbell, \{Andrew T.\} and Chawla, \{Nitesh V.\} and Swain, \{Vedant Das\} and \{De Choudhury\}, Munmun and D'Mello, \{Sidney K.\} and Dey, \{Anind K.\} and Ge Gao and Krithika Jagannath and Kaifeng Jiang and Suwen Lin and Qiang Liu and Gloria Mark and Martinez, \{Gonzalo J.\} and Kizito Masaba and Shayan Mirjafari and Edward Moskal and Raghu Mulukutla and Kari Nies and Reddy, \{Manikanta D.\} and Pablo Robles-Granda and Koustuv Saha and Anusha Sirigiri and Aaron Striegel",

note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). ACM; 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 ; Conference date: 04-05-2019 Through 09-05-2019",

year = "2019",

month = may,

day = "2",

doi = "10.1145/3290607.3299041",

language = "English",

series = "Conference on Human Factors in Computing Systems - Proceedings",

publisher = "Association for Computing Machinery",

booktitle = "CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems",

}

Mattingly, SM, Gregg, JM, Audia, P, Bayraktaroglu, AE, Campbell, AT, Chawla, NV, Swain, VD, De Choudhury, M, D'Mello, SK, Dey, AK, Gao, G, Jagannath, K, Jiang, K, Lin, S, Liu, Q, Mark, G, Martinez, GJ, Masaba, K, Mirjafari, S, Moskal, E, Mulukutla, R, Nies, K, Reddy, MD, Robles-Granda, P, Saha, K, Sirigiri, A & Striegel, A 2019, The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers. in CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems., 3299041, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019, Glasgow, United Kingdom, 4/05/19. https://doi.org/10.1145/3290607.3299041

The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers. / Mattingly, Stephen M.; Gregg, Julie M.; Audia, Pino et al.
CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2019. 3299041 (Conference on Human Factors in Computing Systems - Proceedings).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - The Tesserae project

T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019

AU - Mattingly, Stephen M.

AU - Gregg, Julie M.

AU - Audia, Pino

AU - Bayraktaroglu, Ayse Elvan

AU - Campbell, Andrew T.

AU - Chawla, Nitesh V.

AU - Swain, Vedant Das

AU - De Choudhury, Munmun

AU - D'Mello, Sidney K.

AU - Dey, Anind K.

AU - Gao, Ge

AU - Jagannath, Krithika

AU - Jiang, Kaifeng

AU - Lin, Suwen

AU - Liu, Qiang

AU - Mark, Gloria

AU - Martinez, Gonzalo J.

AU - Masaba, Kizito

AU - Mirjafari, Shayan

AU - Moskal, Edward

AU - Mulukutla, Raghu

AU - Nies, Kari

AU - Reddy, Manikanta D.

AU - Robles-Granda, Pablo

AU - Saha, Koustuv

AU - Sirigiri, Anusha

AU - Striegel, Aaron

PY - 2019/5/2

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N2 - The Tesserae project investigates how a suite of sensors can measure workplace performance (e.g., organizational citizenship behavior), psychological traits (e.g., personality, affect), and physical characteristics (e.g., sleep, activity) over one year. We enrolled 757 information workers across the U.S. and measure heart rate, physical activity, sleep, social context, and other aspects through smartwatches, a phone agent, beacons, and social media. We report challenges that we faced with enrollment, privacy, and incentive structures while setting up such a long-term multimodal large-scale sensor study. We discuss the tradeoffs of remote versus in-person enrollment, and showed that directly paid, in-person enrolled participants are more compliant overall compared to remotely-enrolled participants. We find that providing detailed information regarding privacy concerns up-front is highly beneficial. We believe that our experiences can benefit other large sensor projects as this field grows.

AB - The Tesserae project investigates how a suite of sensors can measure workplace performance (e.g., organizational citizenship behavior), psychological traits (e.g., personality, affect), and physical characteristics (e.g., sleep, activity) over one year. We enrolled 757 information workers across the U.S. and measure heart rate, physical activity, sleep, social context, and other aspects through smartwatches, a phone agent, beacons, and social media. We report challenges that we faced with enrollment, privacy, and incentive structures while setting up such a long-term multimodal large-scale sensor study. We discuss the tradeoffs of remote versus in-person enrollment, and showed that directly paid, in-person enrolled participants are more compliant overall compared to remotely-enrolled participants. We find that providing detailed information regarding privacy concerns up-front is highly beneficial. We believe that our experiences can benefit other large sensor projects as this field grows.

KW - Phone agent

KW - Privacy

KW - Sensors

KW - Smartwatches

KW - Social media

KW - Stress

UR - https://www.scopus.com/pages/publications/85067275122

U2 - 10.1145/3290607.3299041

DO - 10.1145/3290607.3299041

M3 - Conference contribution

AN - SCOPUS:85067275122

T3 - Conference on Human Factors in Computing Systems - Proceedings

BT - CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

Y2 - 4 May 2019 through 9 May 2019

ER -

Mattingly SM, Gregg JM, Audia P, Bayraktaroglu AE, Campbell AT, Chawla NV et al. The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers. In CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2019. 3299041. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3290607.3299041

The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

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