@inproceedings{53bf8127bef74081aa72e02c4f5abe28,
title = "Managing the academic data lifecycle: A case study of HPCC",
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.",
keywords = "Academic research, Big data, Data integration, HPCC, Scalable platform",
author = "Payne, {Michael E.} and Ngo, {Linh B.} and Flavio Villanustre and Apon, {Amy W.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2nd IEEE International Conference on Big Data, IEEE Big Data 2014 ; Conference date: 27-10-2014 Through 30-10-2014",
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 = "Wo Chang and Jun Huan and Nick Cercone and Saumyadipta Pyne and Vasant Honavar and Jimmy Lin and Hu, {Xiaohua Tony} and Charu Aggarwal and Bamshad Mobasher and Jian Pei and Raghunath Nambiar",
booktitle = "Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014",
}