AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases

Sourav S. Bhowmick; Kai Huang; Huey Eng Chua; Zifeng Yuan; Koon Kau Choi; Shuigeng Zhou

doi:10.1145/3318464.3384681

AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases

Sourav S. Bhowmick, Kai Huang, Huey Eng Chua, Zifeng Yuan, Koon Kau Choi, Shuigeng Zhou

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

12 Citations (Scopus)

Abstract

Several commercial and academic frameworks for querying a large collection of small- or medium-sized data graphs (eg. chemical compounds) provide visual graph query interfaces (a.k.a GUI) to facilitate non-programmers to query these sources. However, construction of these visual interfaces is not data-driven. That is, it does not exploit the underlying data graphs to automatically generate the contents of various panels in a GUI. Such data-driven construction has several benefits such as facilitating efficient subgraph query formulation and portability of the interface across different application domains and sources. In this demonstration, we present a novel data-driven visual subgraph query interface construction engine called AURORA. Specifically, given a graph repository D containing a collection of small- or medium-sized data graphs, it automatically generates the GUI for D by populating various components of the interface. We demonstrate various innovative features of AURORA.

Original language	English
Title of host publication	SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
Publisher	Association for Computing Machinery (ACM)
Pages	2689-2692
Number of pages	4
ISBN (Print)	9781450367356
DOIs	https://doi.org/10.1145/3318464.3384681
Publication status	Published - 11 Jun 2020
Event	ACM SIGMOD International Conference on Management of Data, SIGMOD 2020 - Portland, United States Duration: 14 Jun 2020 → 19 Jun 2020 https://dl.acm.org/doi/proceedings/10.1145/3318464

Publication series

Name	Proceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)	0730-8078

Conference

Conference	ACM SIGMOD International Conference on Management of Data, SIGMOD 2020
Country/Territory	United States
City	Portland
Period	14/06/20 → 19/06/20
Internet address	https://dl.acm.org/doi/proceedings/10.1145/3318464

Scopus Subject Areas

Software
Information Systems

User-Defined Keywords

data-driven construction
graph databases
portability
usability
visual graph query interface

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3318464.3384681

Cite this

Bhowmick, S. S., Huang, K., Chua, H. E., Yuan, Z., Choi, K. K., & Zhou, S. (2020). AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases. In SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data (pp. 2689-2692). (Proceedings of the ACM SIGMOD International Conference on Management of Data). Association for Computing Machinery (ACM). https://doi.org/10.1145/3318464.3384681

Bhowmick, Sourav S. ; Huang, Kai ; Chua, Huey Eng et al. / AURORA : Data-driven Construction of Visual Graph Query Interfaces for Graph Databases. SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery (ACM), 2020. pp. 2689-2692 (Proceedings of the ACM SIGMOD International Conference on Management of Data).

@inproceedings{48f08a6a5c9b4621b8a89ec5d7983d61,

title = "AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases",

abstract = "Several commercial and academic frameworks for querying a large collection of small- or medium-sized data graphs (eg. chemical compounds) provide visual graph query interfaces (a.k.a GUI) to facilitate non-programmers to query these sources. However, construction of these visual interfaces is not data-driven. That is, it does not exploit the underlying data graphs to automatically generate the contents of various panels in a GUI. Such data-driven construction has several benefits such as facilitating efficient subgraph query formulation and portability of the interface across different application domains and sources. In this demonstration, we present a novel data-driven visual subgraph query interface construction engine called AURORA. Specifically, given a graph repository D containing a collection of small- or medium-sized data graphs, it automatically generates the GUI for D by populating various components of the interface. We demonstrate various innovative features of AURORA.",

keywords = "data-driven construction, graph databases, portability, usability, visual graph query interface",

author = "Bhowmick, {Sourav S.} and Kai Huang and Chua, {Huey Eng} and Zifeng Yuan and Choi, {Koon Kau} and Shuigeng Zhou",

note = "Funding Information: Acknowledgments. The first four authors are supported by the AcRF Tier-2 Grant MOE2015-T2-1-040. Byron Choi is supported by HKRGC GRF 12201119 and 12201518.; ACM SIGMOD International Conference on Management of Data, SIGMOD 2020 ; Conference date: 14-06-2020 Through 19-06-2020",

year = "2020",

month = jun,

day = "11",

doi = "10.1145/3318464.3384681",

language = "English",

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series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",

publisher = "Association for Computing Machinery (ACM)",

pages = "2689--2692",

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Bhowmick, SS, Huang, K, Chua, HE, Yuan, Z, Choi, KK & Zhou, S 2020, AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases. in SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. Proceedings of the ACM SIGMOD International Conference on Management of Data, Association for Computing Machinery (ACM), pp. 2689-2692, ACM SIGMOD International Conference on Management of Data, SIGMOD 2020, Portland, United States, 14/06/20. https://doi.org/10.1145/3318464.3384681

AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases. / Bhowmick, Sourav S.; Huang, Kai; Chua, Huey Eng et al.
SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery (ACM), 2020. p. 2689-2692 (Proceedings of the ACM SIGMOD International Conference on Management of Data).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AU - Huang, Kai

AU - Chua, Huey Eng

AU - Yuan, Zifeng

AU - Choi, Koon Kau

AU - Zhou, Shuigeng

N1 - Funding Information: Acknowledgments. The first four authors are supported by the AcRF Tier-2 Grant MOE2015-T2-1-040. Byron Choi is supported by HKRGC GRF 12201119 and 12201518.

PY - 2020/6/11

Y1 - 2020/6/11

N2 - Several commercial and academic frameworks for querying a large collection of small- or medium-sized data graphs (eg. chemical compounds) provide visual graph query interfaces (a.k.a GUI) to facilitate non-programmers to query these sources. However, construction of these visual interfaces is not data-driven. That is, it does not exploit the underlying data graphs to automatically generate the contents of various panels in a GUI. Such data-driven construction has several benefits such as facilitating efficient subgraph query formulation and portability of the interface across different application domains and sources. In this demonstration, we present a novel data-driven visual subgraph query interface construction engine called AURORA. Specifically, given a graph repository D containing a collection of small- or medium-sized data graphs, it automatically generates the GUI for D by populating various components of the interface. We demonstrate various innovative features of AURORA.

AB - Several commercial and academic frameworks for querying a large collection of small- or medium-sized data graphs (eg. chemical compounds) provide visual graph query interfaces (a.k.a GUI) to facilitate non-programmers to query these sources. However, construction of these visual interfaces is not data-driven. That is, it does not exploit the underlying data graphs to automatically generate the contents of various panels in a GUI. Such data-driven construction has several benefits such as facilitating efficient subgraph query formulation and portability of the interface across different application domains and sources. In this demonstration, we present a novel data-driven visual subgraph query interface construction engine called AURORA. Specifically, given a graph repository D containing a collection of small- or medium-sized data graphs, it automatically generates the GUI for D by populating various components of the interface. We demonstrate various innovative features of AURORA.

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PB - Association for Computing Machinery (ACM)

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ER -

Bhowmick SS, Huang K, Chua HE, Yuan Z, Choi KK, Zhou S. AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases. In SIGMOD '20 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. Association for Computing Machinery (ACM). 2020. p. 2689-2692. (Proceedings of the ACM SIGMOD International Conference on Management of Data). doi: 10.1145/3318464.3384681

AURORA: Data-driven Construction of Visual Graph Query Interfaces for Graph Databases

Abstract

Publication series

Conference

Scopus Subject Areas

User-Defined Keywords

UN SDGs

Access to Document

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