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Automatic Spatio-temporal Indexing to Integrate and Analyze the Data of an Organization

Authors:

Craig A. Knoblock,

Aparna R. Joshi,

Abhishek Megotia,

Chelsea UrsanerAuthors Info & Claims

UrbanGIS'17: Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

Article No.: 7, Pages 1 - 8

https://doi.org/10.1145/3152178.3152185

Published: 07 November 2017 Publication History

Abstract

Organizations are awash in data. In many cases, they do not know what data exists within the organization and much information is not available when needed, or worse, information gets recreated from other sources. In this paper, we present an automatic approach to spatio-temporal indexing of the datasets within an organization. The indexing process automatically identifies the spatial and temporal fields, normalizes and cleans those fields, and then loads them into a big data store where the information can be efficiently searched, queried, and analyzed. We evaluated our approach on 600 datasets published by the City of Los Angeles and show that we can automatically process their data and can efficiently access and analyze the indexed data.

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Cited By

Chaturvedi SNagpal T(2022)Efficient Querying and Indexing of Moving Data Objects2022 International Conference on Futuristic Technologies (INCOFT)10.1109/INCOFT55651.2022.10094348(1-6)Online publication date: 25-Nov-2022
https://doi.org/10.1109/INCOFT55651.2022.10094348
Tripathi AAgrawal SGupta R(2022)GeoCloud4SDI: a cloud enabled open framework for development of spatial data infrastructure at city levelEarth Science Informatics10.1007/s12145-022-00893-616:1(481-500)Online publication date: 11-Nov-2022
https://doi.org/10.1007/s12145-022-00893-6
Bartlett RPurves RJones C(2019)Local geographic information storing and querying using ElasticsearchProceedings of the 13th Workshop on Geographic Information Retrieval10.1145/3371140.3371144(1-4)Online publication date: 28-Nov-2019
https://dl.acm.org/doi/10.1145/3371140.3371144
Show More Cited By

Automatic Spatio-temporal Indexing to Integrate and Analyze the Data of an Organization
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
2. Information systems
  1. Information retrieval
  2. Information systems applications

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Published In

cover image ACM Conferences

UrbanGIS'17: Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

November 2017

118 pages

ISBN:9781450354950

DOI:10.1145/3152178

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2017

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SIGSPATIAL'17

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SIGSPATIAL

SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 7 - 10, 2017

CA, Redondo Beach, USA

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Cited By

Chaturvedi SNagpal T(2022)Efficient Querying and Indexing of Moving Data Objects2022 International Conference on Futuristic Technologies (INCOFT)10.1109/INCOFT55651.2022.10094348(1-6)Online publication date: 25-Nov-2022
https://doi.org/10.1109/INCOFT55651.2022.10094348
Tripathi AAgrawal SGupta R(2022)GeoCloud4SDI: a cloud enabled open framework for development of spatial data infrastructure at city levelEarth Science Informatics10.1007/s12145-022-00893-616:1(481-500)Online publication date: 11-Nov-2022
https://doi.org/10.1007/s12145-022-00893-6
Bartlett RPurves RJones C(2019)Local geographic information storing and querying using ElasticsearchProceedings of the 13th Workshop on Geographic Information Retrieval10.1145/3371140.3371144(1-4)Online publication date: 28-Nov-2019
https://dl.acm.org/doi/10.1145/3371140.3371144
Pham MKnoblock CPujara J(2019)Learning Data Transformations with Minimal User Effort2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9006350(657-664)Online publication date: Dec-2019
https://doi.org/10.1109/BigData47090.2019.9006350
McKenney MFrey-Spurlock C(2018)Aging in PlaceProceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities10.1145/3284566.3284567(1-2)Online publication date: 6-Nov-2018
https://dl.acm.org/doi/10.1145/3284566.3284567

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