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How people visually represent discrete constraint problems

Research output: Contribution to journalArticle

Standard

How people visually represent discrete constraint problems. / Zhu, Xu; Nacenta, Miguel; Akgün, Özgür; Nightingale, Peter William.

In: IEEE Transactions on Visualization and Computer Graphics, Vol. Early Access, 24.01.2019.

Research output: Contribution to journalArticle

Harvard

Zhu, X, Nacenta, M, Akgün, Ö & Nightingale, PW 2019, 'How people visually represent discrete constraint problems' IEEE Transactions on Visualization and Computer Graphics, vol. Early Access. https://doi.org/10.1109/TVCG.2019.2895085

APA

Zhu, X., Nacenta, M., Akgün, Ö., & Nightingale, P. W. (2019). How people visually represent discrete constraint problems. IEEE Transactions on Visualization and Computer Graphics, Early Access. https://doi.org/10.1109/TVCG.2019.2895085

Vancouver

Zhu X, Nacenta M, Akgün Ö, Nightingale PW. How people visually represent discrete constraint problems. IEEE Transactions on Visualization and Computer Graphics. 2019 Jan 24;Early Access. https://doi.org/10.1109/TVCG.2019.2895085

Author

Zhu, Xu ; Nacenta, Miguel ; Akgün, Özgür ; Nightingale, Peter William. / How people visually represent discrete constraint problems. In: IEEE Transactions on Visualization and Computer Graphics. 2019 ; Vol. Early Access.

Bibtex - Download

@article{4b54ed2e79924712bcf8e6fea3211d72,
title = "How people visually represent discrete constraint problems",
abstract = "Problems such as timetabling or personnel allocation can be modeled and solved using discrete constraint programming languages. However, while existing constraint solving software solves such problems quickly in many cases, these systems involve specialized languages that require significant time and effort to learn and apply. These languages are typically text-based and often difficult to interpret and understand quickly, especially for people without engineering or mathematics backgrounds. Visualization could provide an alternative way to model and understand such problems. Although many visual programming languages exist for procedural languages, visual encoding of problem specifications has not received much attention. Future problem visualization languages could represent problem elements and their constraints unambiguously, but without unnecessary cognitive burdens for those needing to translate their problem's mental representation into diagrams. As a first step towards such languages, we executed a study that catalogs how people represent constraint problems graphically. We studied three groups with different expertise: non-computer scientists, computer scientists and constraint programmers and analyzed their marks on paper (e.g., arrows), gestures (e.g., pointing) and the mappings to problem concepts (e.g., containers, sets). We provide foundations to guide future tool designs allowing people to effectively grasp, model and solve problems through visual representations.",
keywords = "Problem visualization, Problem modeling, Problem solving, Constraint programming, Visual programming languages",
author = "Xu Zhu and Miguel Nacenta and {\"O}zg{\"u}r Akg{\"u}n and Nightingale, {Peter William}",
note = "Funding: This work is supported by EPSRC grants DTG1796157 and EP/P015638/1.",
year = "2019",
month = "1",
day = "24",
doi = "10.1109/TVCG.2019.2895085",
language = "English",
volume = "Early Access",
journal = "IEEE Transactions on Visualization and Computer Graphics",
issn = "1077-2626",
publisher = "IEEE Computer Society",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - How people visually represent discrete constraint problems

AU - Zhu, Xu

AU - Nacenta, Miguel

AU - Akgün, Özgür

AU - Nightingale, Peter William

N1 - Funding: This work is supported by EPSRC grants DTG1796157 and EP/P015638/1.

PY - 2019/1/24

Y1 - 2019/1/24

N2 - Problems such as timetabling or personnel allocation can be modeled and solved using discrete constraint programming languages. However, while existing constraint solving software solves such problems quickly in many cases, these systems involve specialized languages that require significant time and effort to learn and apply. These languages are typically text-based and often difficult to interpret and understand quickly, especially for people without engineering or mathematics backgrounds. Visualization could provide an alternative way to model and understand such problems. Although many visual programming languages exist for procedural languages, visual encoding of problem specifications has not received much attention. Future problem visualization languages could represent problem elements and their constraints unambiguously, but without unnecessary cognitive burdens for those needing to translate their problem's mental representation into diagrams. As a first step towards such languages, we executed a study that catalogs how people represent constraint problems graphically. We studied three groups with different expertise: non-computer scientists, computer scientists and constraint programmers and analyzed their marks on paper (e.g., arrows), gestures (e.g., pointing) and the mappings to problem concepts (e.g., containers, sets). We provide foundations to guide future tool designs allowing people to effectively grasp, model and solve problems through visual representations.

AB - Problems such as timetabling or personnel allocation can be modeled and solved using discrete constraint programming languages. However, while existing constraint solving software solves such problems quickly in many cases, these systems involve specialized languages that require significant time and effort to learn and apply. These languages are typically text-based and often difficult to interpret and understand quickly, especially for people without engineering or mathematics backgrounds. Visualization could provide an alternative way to model and understand such problems. Although many visual programming languages exist for procedural languages, visual encoding of problem specifications has not received much attention. Future problem visualization languages could represent problem elements and their constraints unambiguously, but without unnecessary cognitive burdens for those needing to translate their problem's mental representation into diagrams. As a first step towards such languages, we executed a study that catalogs how people represent constraint problems graphically. We studied three groups with different expertise: non-computer scientists, computer scientists and constraint programmers and analyzed their marks on paper (e.g., arrows), gestures (e.g., pointing) and the mappings to problem concepts (e.g., containers, sets). We provide foundations to guide future tool designs allowing people to effectively grasp, model and solve problems through visual representations.

KW - Problem visualization

KW - Problem modeling

KW - Problem solving

KW - Constraint programming

KW - Visual programming languages

U2 - 10.1109/TVCG.2019.2895085

DO - 10.1109/TVCG.2019.2895085

M3 - Article

VL - Early Access

JO - IEEE Transactions on Visualization and Computer Graphics

T2 - IEEE Transactions on Visualization and Computer Graphics

JF - IEEE Transactions on Visualization and Computer Graphics

SN - 1077-2626

ER -

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ID: 257478580