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United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.

Nearly one-half of all construction projects exceed planned costs and schedule, globally [1]. Owners and construction managers can analyze historical project performance data to inform cost and schedule overrun risk-reduction strategies. Though, the majority of open-source project datasets are limit...

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Autores principales: Stout, Tyler, Teston, Adam, Langhals, Brent, Delorit, Justin, Hendrix, Carlton, Schuldt, Steven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452689/
https://www.ncbi.nlm.nih.gov/pubmed/32904451
http://dx.doi.org/10.1016/j.dib.2020.106128
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author Stout, Tyler
Teston, Adam
Langhals, Brent
Delorit, Justin
Hendrix, Carlton
Schuldt, Steven
author_facet Stout, Tyler
Teston, Adam
Langhals, Brent
Delorit, Justin
Hendrix, Carlton
Schuldt, Steven
author_sort Stout, Tyler
collection PubMed
description Nearly one-half of all construction projects exceed planned costs and schedule, globally [1]. Owners and construction managers can analyze historical project performance data to inform cost and schedule overrun risk-reduction strategies. Though, the majority of open-source project datasets are limited by the number of projects, data dimensionality, and location. A significant global customer of the construction industry, the Department of Defense (DoD) maintains a vast database of historical project data that can be used to determine the sources and magnitude of construction schedule and cost overruns for many continental and international locations. The selection of data provided by the authors is a subset of the U.S. Federal Procurement Data System-Next Generation (FPDS-NG), which stores contractual obligations made by the U.S. Federal Government [2]. The data comprises more than ten fiscal years (1 Oct 2009 – 04 June 2020) of construction contract attributes that will enable researchers to investigate spatiotemporal schedule and cost performance by, but not limited to: contract type, construction type, delivery method, award date, and award value. To the knowledge of the authors, this is the most extensive open-source dataset of its kind, as it provides access to the contract data of 132,662 uniquely identified construction projects totaling $865 billion. Because the DoD's facilities and infrastructure construction requirements and use of private construction firms are congruent with the remainder of the public sector and the private sector, results obtained from analyses of this dataset may be appropriate for broader application.
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spelling pubmed-74526892020-09-03 United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020. Stout, Tyler Teston, Adam Langhals, Brent Delorit, Justin Hendrix, Carlton Schuldt, Steven Data Brief Engineering Nearly one-half of all construction projects exceed planned costs and schedule, globally [1]. Owners and construction managers can analyze historical project performance data to inform cost and schedule overrun risk-reduction strategies. Though, the majority of open-source project datasets are limited by the number of projects, data dimensionality, and location. A significant global customer of the construction industry, the Department of Defense (DoD) maintains a vast database of historical project data that can be used to determine the sources and magnitude of construction schedule and cost overruns for many continental and international locations. The selection of data provided by the authors is a subset of the U.S. Federal Procurement Data System-Next Generation (FPDS-NG), which stores contractual obligations made by the U.S. Federal Government [2]. The data comprises more than ten fiscal years (1 Oct 2009 – 04 June 2020) of construction contract attributes that will enable researchers to investigate spatiotemporal schedule and cost performance by, but not limited to: contract type, construction type, delivery method, award date, and award value. To the knowledge of the authors, this is the most extensive open-source dataset of its kind, as it provides access to the contract data of 132,662 uniquely identified construction projects totaling $865 billion. Because the DoD's facilities and infrastructure construction requirements and use of private construction firms are congruent with the remainder of the public sector and the private sector, results obtained from analyses of this dataset may be appropriate for broader application. Elsevier 2020-08-05 /pmc/articles/PMC7452689/ /pubmed/32904451 http://dx.doi.org/10.1016/j.dib.2020.106128 Text en http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Engineering
Stout, Tyler
Teston, Adam
Langhals, Brent
Delorit, Justin
Hendrix, Carlton
Schuldt, Steven
United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title_full United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title_fullStr United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title_full_unstemmed United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title_short United states department of defense (DoD) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
title_sort united states department of defense (dod) real property repair, alterations, maintenance, and construction project contract data: 2009–2020.
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7452689/
https://www.ncbi.nlm.nih.gov/pubmed/32904451
http://dx.doi.org/10.1016/j.dib.2020.106128
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