"Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.

In research portfolio planning contexts, an estimate of research policy and project synergies/tradeoffs (i.e. covariances) is essential to the optimal leveraging of institution resources. The data by which to make such estimates generally do not exist. Research institutions may often draw on domain...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autor principal: Benjamin Schiek
Formato: article
Lenguaje:EN
Publicado: Public Library of Science (PLoS) 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/8bf790c855e84920aff35ccaf387c7b1
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:8bf790c855e84920aff35ccaf387c7b1
record_format dspace
spelling oai:doaj.org-article:8bf790c855e84920aff35ccaf387c7b12021-12-02T20:13:12Z"Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.1932-620310.1371/journal.pone.0259734https://doaj.org/article/8bf790c855e84920aff35ccaf387c7b12021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0259734https://doaj.org/toc/1932-6203In research portfolio planning contexts, an estimate of research policy and project synergies/tradeoffs (i.e. covariances) is essential to the optimal leveraging of institution resources. The data by which to make such estimates generally do not exist. Research institutions may often draw on domain expertise to fill this gap, but it is not clear how such ad hoc information can be quantified and fed into an optimal resource allocation workflow. Drawing on principal components analysis, I propose a method for "reverse engineering" synergies/tradeoffs from domain expertise at both the policy and project level. I discuss extensions to other problems and detail how the method can be fed into a research portfolio optimization workflow. I also briefly discuss the relevance of the proposed method in the context of the currently toxic relations between research communities and the donors that fund them.Benjamin SchiekPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0259734 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Benjamin Schiek
"Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
description In research portfolio planning contexts, an estimate of research policy and project synergies/tradeoffs (i.e. covariances) is essential to the optimal leveraging of institution resources. The data by which to make such estimates generally do not exist. Research institutions may often draw on domain expertise to fill this gap, but it is not clear how such ad hoc information can be quantified and fed into an optimal resource allocation workflow. Drawing on principal components analysis, I propose a method for "reverse engineering" synergies/tradeoffs from domain expertise at both the policy and project level. I discuss extensions to other problems and detail how the method can be fed into a research portfolio optimization workflow. I also briefly discuss the relevance of the proposed method in the context of the currently toxic relations between research communities and the donors that fund them.
format article
author Benjamin Schiek
author_facet Benjamin Schiek
author_sort Benjamin Schiek
title "Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
title_short "Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
title_full "Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
title_fullStr "Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
title_full_unstemmed "Reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
title_sort "reverse engineering" research portfolio synergies and tradeoffs from domain expertise in minimum data contexts.
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/8bf790c855e84920aff35ccaf387c7b1
work_keys_str_mv AT benjaminschiek reverseengineeringresearchportfoliosynergiesandtradeoffsfromdomainexpertiseinminimumdatacontexts
_version_ 1718374836674232320