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Title: Automated Indexing of Structured Scientific Metadata Using Apache Solr

Abstract

Scientific datasets are continuously growing with the amount of raw data being collected worldwide. This amount of data poses the biggest challenge to web search engines on how to retrieve them efficiently. This paper discusses how major scientific data centers are using popular open-source search platforms such as Solr [1] to retrieve structured data stored in data sources such as relational database management systems using its import handler mechanisms [2]. Additionally, we will also focus on how we can configure Solr to serve advanced full-text, faceted search capabilities, along with its key features, which simplify representing and delivering better performance to the scientific search interfaces.

Authors:
 [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1777737
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: IEEE International Conference on Big Data - Virtual, Georgia, United States of America - 12/10/2020 8:00:00 PM-12/13/2020 5:00:00 AM
Country of Publication:
United States
Language:
English

Citation Formats

Guntupally, Kavya, Dumas, Kyle, Darnell, Wade, Crow, Michael C., Devarakonda, Ranjeet, and Prakash, Giri. Automated Indexing of Structured Scientific Metadata Using Apache Solr. United States: N. p., 2020. Web. doi:10.1109/BigData50022.2020.9378448.
Guntupally, Kavya, Dumas, Kyle, Darnell, Wade, Crow, Michael C., Devarakonda, Ranjeet, & Prakash, Giri. Automated Indexing of Structured Scientific Metadata Using Apache Solr. United States. https://doi.org/10.1109/BigData50022.2020.9378448
Guntupally, Kavya, Dumas, Kyle, Darnell, Wade, Crow, Michael C., Devarakonda, Ranjeet, and Prakash, Giri. 2020. "Automated Indexing of Structured Scientific Metadata Using Apache Solr". United States. https://doi.org/10.1109/BigData50022.2020.9378448. https://www.osti.gov/servlets/purl/1777737.
@article{osti_1777737,
title = {Automated Indexing of Structured Scientific Metadata Using Apache Solr},
author = {Guntupally, Kavya and Dumas, Kyle and Darnell, Wade and Crow, Michael C. and Devarakonda, Ranjeet and Prakash, Giri},
abstractNote = {Scientific datasets are continuously growing with the amount of raw data being collected worldwide. This amount of data poses the biggest challenge to web search engines on how to retrieve them efficiently. This paper discusses how major scientific data centers are using popular open-source search platforms such as Solr [1] to retrieve structured data stored in data sources such as relational database management systems using its import handler mechanisms [2]. Additionally, we will also focus on how we can configure Solr to serve advanced full-text, faceted search capabilities, along with its key features, which simplify representing and delivering better performance to the scientific search interfaces.},
doi = {10.1109/BigData50022.2020.9378448},
url = {https://www.osti.gov/biblio/1777737}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {12}
}

Conference:
Other availability
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