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Merge pull request #26 from DE-RSE/jlinx-patch-1
Start adding missing references
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bibliography.bib

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@@ -517,6 +517,14 @@ @Article{Bird2016
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date = {2016},
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}
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@inproceedings{Blech2022,
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author = {Blech, Christopher and Dreyer, Nils and Friebel, Bj{\"o}rn and R. Jacob, Christoph and Shamil Jassim, Mostafa and Jehl, Leander and Kapitza, R{\"u}diger and Krafczyk, Manfred and K{\"u}rner, Thomas and C. Langer, Sabine and Linxweiler, Jan and Mahhouk, Mohammad and Marcus, Sven and Messadi, Ines and Peters, S{\"o}ren and Pilawa, Jan-Marc and K. Sreekumar, Harikrishnan and Str{\"o}tgen, Robert and Stump, Katrin and Vogel, Arne and Wolter, Mario},
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booktitle = {campusSOURCE Award 2022},
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title = {{SURESOFT}: {Towards} {Sustainable} {Research} {Software}},
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year = {2022},
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}
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@Online{BluefieldIBMBadges,
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author = {{Bluefield State}},
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title = {{B}luefield State College Now Offering {IBM} Badge Certification},
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urldate = {2023-06-14},
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}
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@article{Goble2014,
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author = {Goble, C.},
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journal = {IEEE Internet Computing},
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month = {Sep.},
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number = {5},
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pages = {4-8},
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title = {Better Software, Better Research},
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volume = {18},
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year = {2014}
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}
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@Article{Godoy2022,
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author = {Godoy, William F. and Arora, Ritu and Beattie, Keith and Bernholdt, David E. and Bratt, Sarah E. and Katz, Daniel S. and Laguna, Ignacio and Maji, Amiya K. and Malviya-Thakur, Addi and Mudafort, Rafael M. and Sukhija, Nitin and Rouson, Damian and Rubio-Gonz{\'{a}}lez, Cindy and Vahi, Karan},
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title = {Giving Research Software Engineers a Larger Stage Through the {B}etter {S}cientific {S}oftware {F}ellowship},
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publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
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}
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@dataset{Hettrick2015,
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author = {Hettrick, Simon and Antonioletti, Mario and Carr, Les and Chue Hong, Neil and Crouch, Stephen and De Roure, David and Emsley, Iain and Goble, Carole and Hay, Alexander and Inupakutika, Devasena and Jackson, Mike and Nenadic, Aleksandra and Parkinson, Tim and Parsons, Mark I and Pawlik, Aleksandra and Peru, Giacomo and Proeme, Arno and Robinson, John and Sufi, Shoaib},
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date-modified = {2024-03-03 10:24:03 +0100},
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doi = {10.5281/zenodo.14809},
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month = mar,
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publisher = {Zenodo},
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title = {UK Research Software Survey 2014},
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url = {https://doi.org/10.5281/zenodo.14809},
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year = 2015,
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}
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@Misc{Hettrick2016,
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author = {Hettrick, Simon},
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title = {A not-so-brief history of Research Software Engineers},

paper.tex

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\section{Introduction}
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Research software has been written and used for decades in a range of disciplines.
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It has been established that most research requires research software for its results [REF].
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To solve pressing research challenges, better software is crucial [REF].
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It has been established that most research requires research software for its results~\autocite{Hannay2009, Hettrick2015}.
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To solve pressing research challenges, better software is crucial~\autocite{Goble2014}.
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During the past decade, it gained ever-growing attention and is becoming accepted as a research result on its own.
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%We follow here the definition: “Research Software includes source code files, algorithms, scripts, computational workflows and executables that were created during the research process or for a research purpose”, with full definition and discussion provided in~\autocite{Gruenpeter2021}.
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The number of people developing software in academia is constantly rising [REF].
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The number of people developing software in academia is constantly rising~\autocite{Hannay2009, Hettrick2015}.
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Research Software Engineering are actions necessary to create, adapt or maintain Research Software or train others to do so.
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These actions are very diverse and so are the environments they are performed in.
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This position paper focuses on (groups of) research software engineers and researchers who require RSE for their research.
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role as an alternative to a traditional research role because they enjoy and wish to focus
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on the development of research software.\\
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\textbf{Researchers:}\\
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We refer by researcher to all others involved in research or in research supporting organizations as \eg libraries,
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We refer by researchers to all others involved in research or in research supporting organizations such as \eg libraries,
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hence those that are at most sporadically performing RSE actions.
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\section{Motivation}
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In this chapter, we provide motivation for dedicated RSE groups in German research organizations.
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In this chapter, we motivate dedicated RSE groups in German research organizations.
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Several stakeholder perspectives are discussed and supported by (inter)national examples, including that of RSEs within RSE groups, RSEs embedded in research groups, Researchers in need of RSE resources, organizational management and that of funders.
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Research Data Management has proved to benefit data quality through training researchers, the reusability through data repositories and to avoid duplication of effort.
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[TODO elaborate parallels to RDM SuccessStory] For over a decade, research funders and organizations made a significant effort to establish RDM and teams around it.
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We assume that research software will follow a similar trajectory.
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\footnote{For arguments why research software is unlike data, see REF .}
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While we focus on Germany here, it is beneficial to review how other countries approach research software.
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In the UK, for example, many universities started initiating dedicated RSE departments about a decade ago [REF].
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In the UK, for example, many universities started initiating dedicated RSE departments about a decade ago~\autocite{Crouch2013}.
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The successful establishment of such staff roles is a role model for similar academic organizations worldwide.
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A range of already-existing departments can be seen in this map: https://society-rse.org/community/rse-groups/
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\subsection{Tasks - Why do central software services make sense?}
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One of the services a centralized RSE department likely will provide is training to improve the often low-quality code developed by beginners [REF low-quality].
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Examples for organizational training efforts are the Helmholtz HIFIS group [https://events.hifis.net/category/4/], the Scientific Software Center in Heidelberg [https://www.ssc.uni-heidelberg.de/en], the Competence Center Digital Research in Jena (zedif: [https://www.zedif.uni-jena.de/en/]), and the SURESOFT workshops series in Braunschweig ~\autocite{SURESOFTLink}.
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Another national pioneer is the Göttingen State and University Library who set up a group of RSEs offering – besides training – services like data modeling and visualization, digital editions, portal development and more. They reported a remarkable increase in software quality, better grant applications, less brain drain and overall employee satisfaction levels~\autocite{schimavoigt2023}.
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Examples of organizational training efforts are the Helmholtz HIFIS group [https://events.hifis.net/category/4/], the Scientific Software Center in Heidelberg [https://www.ssc.uni-heidelberg.de/en], the Competence Center Digital Research in Jena (zedif: [https://www.zedif.uni-jena.de/en/]), and the SURESOFT workshops series in Braunschweig ~\autocite{SURESOFTLink, Blech2022}.
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Another national pioneer is the Göttingen State and University Library which set up a group of RSEs offering – besides training – services like data modeling and visualization, digital editions, portal development and more. They reported a remarkable increase in software quality, better grant applications, less brain drain and overall employee satisfaction levels~\autocite{schimavoigt2023}.
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The demand for such services appears to be ever-increasing.
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Cite for international comparison \autocite{Cosden2022} Princeton RSE group model
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Organisations typically only have limited opportunities to counteract this disadvantage due to binding pay scale systems.
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However, possibilities within those systems are not always used to their full potential, e.g., not always the work of RSEs is categorised as “scientific” and thus, their pay is below that of other researchers.
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The second problem is the severe shortage of people with the skills necessary for a good RSE.
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While this is a problem already now, it is expected to get a lot worse in the future due to both an aging society and an ever-increasing demand for these individuals.
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While this is a problem already today, it is expected to get a lot worse in the future due to both an aging society and an ever-increasing demand for these individuals.
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Thus, it is in the best interest of research organisations to avoid losing the RSEs they employ to industry.
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One of the most under-used possibilities they have is to offer permanent positions.
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RSE departments act as knowledge hubs in a network of academic developers[REF: Dissertation zur Verstetigung von Netzwerken].
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This enables the embedded experts to maintain in-depth knowledge and to assess current trends and developments, both in research as well as technology.
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According to [SUB Goettingen] the employee satisfaction significantly increases with RSE services.
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According to [SUB Goettingen] employee satisfaction significantly increases with RSE services.
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The SUB library department “Software and Digital Services” was founded to support their (research) software needs~\autocite{schimavoigt2023}.
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Soon after, this department received inquiries from the campus at large, showcasing the need for such services [SuccessStory from a university library, \eg ~\autocite{schimavoigt2023}. The Carpentries~\autocite{Carpentries} exemplify a similar success story [REF SuccessStory Carpentries https://carpentries.org/testimonials/]. Requests or suggestions for even more training show the need for such services.
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RSE services which benefit all disciplines/departments may represent a unique selling point for organizations competing for the brightest minds.
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[SuccessStory from industry provided by Bernhard Rumpe TODO REF?!]
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Most academic research organizations have established centralized tooling, e.g. storage or HPC, but only a few consider software development consultancy a relevant service.
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Selected research institutions in the UK have long been the role model for RSE deployment into research projects [REF].
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Selected research institutions in the UK have long been role models for RSE deployment into research projects [REF].
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There, grant applications (almost always) include software development in their budget.
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This allocated money can then be utilized to delegate/dispatch a central RSE person or group into a research project for a few weeks or months as necessary.
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Coming back to RDM again for comparison: The most recent funding guidelines suggest “data stewards” in data-driven research.
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Coming back to RDM again for comparison: The most recent funding guidelines suggest “data stewards” in data-driven research.
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Such experts are to be employed in advanced research projects like “Collaborative Research Centers” (CRC)[Footnote Sonderforschungsbereich (SFB)] or “Clusters of Excellence”
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\footnote{Cluster der Exzellenzinitiative}.
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These data experts support research projects in several aspects including DMPlans, grant applications, data availability for journal publications, compliance, FAIRification and more.
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A few journals started asking for code submission [REF CHORUS? Nature?].
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The rather complex assessment of FAIRness [REF apples to apples] has widened from data to software~\autocite{fair_data_maturity_model_working_group_2020}.
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A decentralized RSE will provide training, improve software, support research publications, in close relationship with the local research team.
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A decentralized RSE will provide training, improve software, and support research publications, in close relationship with the local research team.
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An RSE deployed into a research project for a certain amount of time will be a very cost-efficient way of utilizing expert knowledge in selecting appropriate frameworks, APIs and libraries.
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These experts are able to establish collaborative coding environments and may even write (or refactor) specialized source code, \eg for HPC application.
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These experts are able to establish collaborative coding environments and may even write (or refactor) specialized source code, \eg for HPC applications.
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This is the most efficient utilization of RSEs in/as centralized knowledge hubs - avoiding duplication of effort in acquiring such expertise in/for each and every short-term project.
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While the industry aims for faster-to-market products, academia is often competing for the fastest publication.
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\subsection{Measures}
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Publication effort for better software will increase discoverability which in turn will decrease duplication of effort.
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Publication efforts for better software will increase discoverability which in turn will decrease duplication of effort.
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Scarce resources like professional staff, time and money are not put to waste. Instead, better software (publications) will lead to outstanding reputation.
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A professionalization in software development and management can be expected to lead from research project prototypes to software products to the benefit of everyone.
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\section{Vision}
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\label{sec:vision}
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In this chapter we describe a vision of central RSE departments of research institutions in Germany.
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In this chapter, we describe a vision of central RSE departments of research institutions in Germany.
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As these institutions include universities, other colleges, as well as large associations like Max-Planck, Helmholtz, Fraunhofer or Leibniz,
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they show a wide variety in organizational structure as well as internal scientific diversity.
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Thus, there can be no single optimal concept of such a department for all research institutions in Germany.
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Thus, we instead describe modular components that can be mixed and matched based on the respective local environment.
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These nine modules comprise the core services of an RSE department.
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Not all, and probably not even most of the RSE departments will deliver all nine, and different RSE departments will put focus on different modules.
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These suggested nine modules comprise the core services of an RSE department.
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Not all, and probably not even most of the RSE departments will deliver all nine, and different RSE departments will focus on different modules.
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Thus, it is likely that no two departments will be, or should be, alike.
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However, these nine modules together with assumed weights for each are part of a simple model of an RSE group which provides both a quick overview of an individual group as well as a way to compare groups.
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The nine modules are defined as follows:

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