Challenges and trends about smart big geospatial data: A position paper

Victor Saquicela; Luis M. Vilches-Blazquez; Andres Tello

doi:10.1109/BigData.2017.8258335

Challenges and trends about smart big geospatial data: A position paper

Victor Saquicela, Luis M. Vilches-Blazquez, Andres Tello

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

Currently, we are witnessing an exponential growth in the amount of data being generated and captured at multiple locations. This trend will continue over the next years. Hence, we have envisioned a scenario in which many objects will be referencing to or generating location information. Thus, the need for appropriately managing geospatial data is evident. In this paper, we present our vision for an integral Geo Linked Data platform; pointing out the current limitations and challenges in the GeoRDFization, Storage, Query Federation, and Visualization of data with an inherent spatial context.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Editors	Jian-Yun Nie, Zoran Obradovic, Toyotaro Suzumura, Rumi Ghosh, Raghunath Nambiar, Chonggang Wang, Hui Zang, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Xiaohua Hu, Jeremy Kepner, Alfredo Cuzzocrea, Jian Tang, Masashi Toyoda
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3471-3475
Number of pages	5
ISBN (Electronic)	9781538627143
DOIs	https://doi.org/10.1109/BigData.2017.8258335
Publication status	Published - 1-Jul-2017
Externally published	Yes
Event	5th IEEE International Conference on Big Data, Big Data 2017 - Boston, United States Duration: 11-Dec-2017 → 14-Dec-2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
Volume	2018-January

Conference

Conference	5th IEEE International Conference on Big Data, Big Data 2017
Country/Territory	United States
City	Boston
Period	11/12/2017 → 14/12/2017

Keywords

federated queries
GeoRDFization
GeoSPARQL

Access to Document

10.1109/BigData.2017.8258335

Handle.net

Persistent link

Cite this

Saquicela, V., Vilches-Blazquez, L. M., & Tello, A. (2017). Challenges and trends about smart big geospatial data: A position paper. In J.-Y. Nie, Z. Obradovic, T. Suzumura, R. Ghosh, R. Nambiar, C. Wang, H. Zang, R. Baeza-Yates, R. Baeza-Yates, X. Hu, J. Kepner, A. Cuzzocrea, J. Tang, & M. Toyoda (Eds.), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017 (pp. 3471-3475). (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2017.8258335

Saquicela, Victor ; Vilches-Blazquez, Luis M. ; Tello, Andres. / Challenges and trends about smart big geospatial data : A position paper. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. editor / Jian-Yun Nie ; Zoran Obradovic ; Toyotaro Suzumura ; Rumi Ghosh ; Raghunath Nambiar ; Chonggang Wang ; Hui Zang ; Ricardo Baeza-Yates ; Ricardo Baeza-Yates ; Xiaohua Hu ; Jeremy Kepner ; Alfredo Cuzzocrea ; Jian Tang ; Masashi Toyoda. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 3471-3475 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017).

@inproceedings{0540c2ada2834951915edb1e833f42df,

title = "Challenges and trends about smart big geospatial data: A position paper",

abstract = "Currently, we are witnessing an exponential growth in the amount of data being generated and captured at multiple locations. This trend will continue over the next years. Hence, we have envisioned a scenario in which many objects will be referencing to or generating location information. Thus, the need for appropriately managing geospatial data is evident. In this paper, we present our vision for an integral Geo Linked Data platform; pointing out the current limitations and challenges in the GeoRDFization, Storage, Query Federation, and Visualization of data with an inherent spatial context.",

keywords = "federated queries, GeoRDFization, GeoSPARQL",

author = "Victor Saquicela and Vilches-Blazquez, {Luis M.} and Andres Tello",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 5th IEEE International Conference on Big Data, Big Data 2017 ; Conference date: 11-12-2017 Through 14-12-2017",

year = "2017",

month = jul,

day = "1",

doi = "10.1109/BigData.2017.8258335",

language = "English",

series = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3471--3475",

editor = "Jian-Yun Nie and Zoran Obradovic and Toyotaro Suzumura and Rumi Ghosh and Raghunath Nambiar and Chonggang Wang and Hui Zang and Ricardo Baeza-Yates and Ricardo Baeza-Yates and Xiaohua Hu and Jeremy Kepner and Alfredo Cuzzocrea and Jian Tang and Masashi Toyoda",

booktitle = "Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017",

}

Saquicela, V, Vilches-Blazquez, LM & Tello, A 2017, Challenges and trends about smart big geospatial data: A position paper. in J-Y Nie, Z Obradovic, T Suzumura, R Ghosh, R Nambiar, C Wang, H Zang, R Baeza-Yates, R Baeza-Yates, X Hu, J Kepner, A Cuzzocrea, J Tang & M Toyoda (eds), Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 3471-3475, 5th IEEE International Conference on Big Data, Big Data 2017, Boston, United States, 11/12/2017. https://doi.org/10.1109/BigData.2017.8258335

Challenges and trends about smart big geospatial data: A position paper. / Saquicela, Victor; Vilches-Blazquez, Luis M.; Tello, Andres.
Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. ed. / Jian-Yun Nie; Zoran Obradovic; Toyotaro Suzumura; Rumi Ghosh; Raghunath Nambiar; Chonggang Wang; Hui Zang; Ricardo Baeza-Yates; Ricardo Baeza-Yates; Xiaohua Hu; Jeremy Kepner; Alfredo Cuzzocrea; Jian Tang; Masashi Toyoda. Institute of Electrical and Electronics Engineers Inc., 2017. p. 3471-3475 (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Challenges and trends about smart big geospatial data

T2 - 5th IEEE International Conference on Big Data, Big Data 2017

AU - Saquicela, Victor

AU - Vilches-Blazquez, Luis M.

AU - Tello, Andres

PY - 2017/7/1

Y1 - 2017/7/1

N2 - Currently, we are witnessing an exponential growth in the amount of data being generated and captured at multiple locations. This trend will continue over the next years. Hence, we have envisioned a scenario in which many objects will be referencing to or generating location information. Thus, the need for appropriately managing geospatial data is evident. In this paper, we present our vision for an integral Geo Linked Data platform; pointing out the current limitations and challenges in the GeoRDFization, Storage, Query Federation, and Visualization of data with an inherent spatial context.

AB - Currently, we are witnessing an exponential growth in the amount of data being generated and captured at multiple locations. This trend will continue over the next years. Hence, we have envisioned a scenario in which many objects will be referencing to or generating location information. Thus, the need for appropriately managing geospatial data is evident. In this paper, we present our vision for an integral Geo Linked Data platform; pointing out the current limitations and challenges in the GeoRDFization, Storage, Query Federation, and Visualization of data with an inherent spatial context.

KW - federated queries

KW - GeoRDFization

KW - GeoSPARQL

UR - http://www.scopus.com/inward/record.url?scp=85047817601&partnerID=8YFLogxK

U2 - 10.1109/BigData.2017.8258335

DO - 10.1109/BigData.2017.8258335

M3 - Conference contribution

AN - SCOPUS:85047817601

T3 - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017

SP - 3471

EP - 3475

BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017

A2 - Nie, Jian-Yun

A2 - Obradovic, Zoran

A2 - Suzumura, Toyotaro

A2 - Ghosh, Rumi

A2 - Nambiar, Raghunath

A2 - Wang, Chonggang

A2 - Zang, Hui

A2 - Baeza-Yates, Ricardo

A2 - Hu, Xiaohua

A2 - Kepner, Jeremy

A2 - Cuzzocrea, Alfredo

A2 - Tang, Jian

A2 - Toyoda, Masashi

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 11 December 2017 through 14 December 2017

ER -

Saquicela V, Vilches-Blazquez LM, Tello A. Challenges and trends about smart big geospatial data: A position paper. In Nie JY, Obradovic Z, Suzumura T, Ghosh R, Nambiar R, Wang C, Zang H, Baeza-Yates R, Baeza-Yates R, Hu X, Kepner J, Cuzzocrea A, Tang J, Toyoda M, editors, Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 3471-3475. (Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017). doi: 10.1109/BigData.2017.8258335

Challenges and trends about smart big geospatial data: A position paper

Abstract

Publication series

Conference

Keywords

Access to Document

Handle.net

Other files and links

Embargoed Document

Fingerprint

Cite this