Managing the academic data lifecycle: A case study of HPCC

Michael E. Payne; Linh B. Ngo; Flavio Villanustre; Amy W. Apon

doi:10.1109/BigData.2014.7004348

Managing the academic data lifecycle: A case study of HPCC

Michael E. Payne, Linh B. Ngo, Flavio Villanustre, Amy W. Apon

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

5 Scopus citations

Abstract

Academic data can be classified into multiple categories and come from a large number of sources. Many research areas require combining data from different sources into a unified set on which analytical techniques can be applied. In this research paper the authors introduce the High Performance Computing Cluster (HPCC) as a platform to streamline the process of ingesting, curating, integrating and transforming scholarly data from multiple sources and in varying formats, particularly when several of these datasets lack common attributes to support the integration process.

Original language	English
Title of host publication	Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014
Editors	Jimmy Lin, Jian Pei, Xiaohua Tony Hu, Wo Chang, Raghunath Nambiar, Charu Aggarwal, Nick Cercone, Vasant Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	22-30
Number of pages	9
ISBN (Electronic)	9781479956654
DOIs	https://doi.org/10.1109/BigData.2014.7004348
State	Published - 2014
Externally published	Yes
Event	2nd IEEE International Conference on Big Data, Big Data 2014 - Washington, United States Duration: Oct 27 2014 → Oct 30 2014

Publication series

Name	Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

Conference

Conference	2nd IEEE International Conference on Big Data, Big Data 2014
Country/Territory	United States
City	Washington
Period	10/27/14 → 10/30/14

Keywords

Academic research
Big data
Data integration
HPCC
Scalable platform

Access to Document

10.1109/BigData.2014.7004348

Cite this

Payne, M. E., Ngo, L. B., Villanustre, F., & Apon, A. W. (2014). Managing the academic data lifecycle: A case study of HPCC. In J. Lin, J. Pei, X. T. Hu, W. Chang, R. Nambiar, C. Aggarwal, N. Cercone, V. Honavar, J. Huan, B. Mobasher, & S. Pyne (Eds.), Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014 (pp. 22-30). Article 7004348 (Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2014.7004348

Payne, Michael E. ; Ngo, Linh B. ; Villanustre, Flavio et al. / Managing the academic data lifecycle : A case study of HPCC. Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014. editor / Jimmy Lin ; Jian Pei ; Xiaohua Tony Hu ; Wo Chang ; Raghunath Nambiar ; Charu Aggarwal ; Nick Cercone ; Vasant Honavar ; Jun Huan ; Bamshad Mobasher ; Saumyadipta Pyne. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 22-30 (Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014).

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abstract = "Academic data can be classified into multiple categories and come from a large number of sources. Many research areas require combining data from different sources into a unified set on which analytical techniques can be applied. In this research paper the authors introduce the High Performance Computing Cluster (HPCC) as a platform to streamline the process of ingesting, curating, integrating and transforming scholarly data from multiple sources and in varying formats, particularly when several of these datasets lack common attributes to support the integration process.",

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author = "Payne, \{Michael E.\} and Ngo, \{Linh B.\} and Flavio Villanustre and Apon, \{Amy W.\}",

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year = "2014",

doi = "10.1109/BigData.2014.7004348",

language = "Ingl{\'e}s",

series = "Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014",

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

pages = "22--30",

editor = "Jimmy Lin and Jian Pei and Hu, \{Xiaohua Tony\} and Wo Chang and Raghunath Nambiar and Charu Aggarwal and Nick Cercone and Vasant Honavar and Jun Huan and Bamshad Mobasher and Saumyadipta Pyne",

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Payne, ME, Ngo, LB, Villanustre, F & Apon, AW 2014, Managing the academic data lifecycle: A case study of HPCC. in J Lin, J Pei, XT Hu, W Chang, R Nambiar, C Aggarwal, N Cercone, V Honavar, J Huan, B Mobasher & S Pyne (eds), Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014., 7004348, Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014, Institute of Electrical and Electronics Engineers Inc., pp. 22-30, 2nd IEEE International Conference on Big Data, Big Data 2014, Washington, United States, 10/27/14. https://doi.org/10.1109/BigData.2014.7004348

Managing the academic data lifecycle: A case study of HPCC. / Payne, Michael E.; Ngo, Linh B.; Villanustre, Flavio et al.
Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014. ed. / Jimmy Lin; Jian Pei; Xiaohua Tony Hu; Wo Chang; Raghunath Nambiar; Charu Aggarwal; Nick Cercone; Vasant Honavar; Jun Huan; Bamshad Mobasher; Saumyadipta Pyne. Institute of Electrical and Electronics Engineers Inc., 2014. p. 22-30 7004348 (Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014).

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

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T1 - Managing the academic data lifecycle

T2 - 2nd IEEE International Conference on Big Data, Big Data 2014

AU - Payne, Michael E.

AU - Ngo, Linh B.

AU - Villanustre, Flavio

AU - Apon, Amy W.

PY - 2014

Y1 - 2014

N2 - Academic data can be classified into multiple categories and come from a large number of sources. Many research areas require combining data from different sources into a unified set on which analytical techniques can be applied. In this research paper the authors introduce the High Performance Computing Cluster (HPCC) as a platform to streamline the process of ingesting, curating, integrating and transforming scholarly data from multiple sources and in varying formats, particularly when several of these datasets lack common attributes to support the integration process.

AB - Academic data can be classified into multiple categories and come from a large number of sources. Many research areas require combining data from different sources into a unified set on which analytical techniques can be applied. In this research paper the authors introduce the High Performance Computing Cluster (HPCC) as a platform to streamline the process of ingesting, curating, integrating and transforming scholarly data from multiple sources and in varying formats, particularly when several of these datasets lack common attributes to support the integration process.

KW - Academic research

KW - Big data

KW - Data integration

KW - HPCC

KW - Scalable platform

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DO - 10.1109/BigData.2014.7004348

M3 - Contribución a la conferencia

AN - SCOPUS:84988306343

T3 - Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014

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BT - Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014

A2 - Lin, Jimmy

A2 - Pei, Jian

A2 - Hu, Xiaohua Tony

A2 - Chang, Wo

A2 - Nambiar, Raghunath

A2 - Aggarwal, Charu

A2 - Cercone, Nick

A2 - Honavar, Vasant

A2 - Huan, Jun

A2 - Mobasher, Bamshad

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 27 October 2014 through 30 October 2014

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Payne ME, Ngo LB, Villanustre F, Apon AW. Managing the academic data lifecycle: A case study of HPCC. In Lin J, Pei J, Hu XT, Chang W, Nambiar R, Aggarwal C, Cercone N, Honavar V, Huan J, Mobasher B, Pyne S, editors, Proceedings - 2014 IEEE International Conference on Big Data, Big Data 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 22-30. 7004348. (Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014). doi: 10.1109/BigData.2014.7004348

Managing the academic data lifecycle: A case study of HPCC

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