Collaboration, peer review and open source software

Johnson, Justin P.

doi:10.1016/j.infoecopol.2006.07.001

Cited by 71 publications

(33 citation statements)

References 36 publications

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“…Detecting bugs is particularly vital in energy system modelling, as small errors may have great impact on the results. Johnson [69] highlights that peer-reviewed open source software has significant advantages related to bug findings. Besides this, Ndenga et al [70] point out that the size of a community, i.e.…”

Section: Scientific Standardsmentioning

confidence: 99%

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Hilpert¹,

Günther²,

Kaldemeyer³

et al. 2017

Preprint

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These authors contributed equally to this work. AbstractThe process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult.In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities.Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

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Section: Scientific Standardsmentioning

confidence: 99%

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Hilpert¹,

Günther²,

Kaldemeyer³

et al. 2017

Preprint

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show abstract

“…14 The contributed R packages are available at the Comprehensive R Archive Network (CRAN), accessed on March 19, 2009. programming code is only available to a limited number of individuals namely company employees who are more likely to focus on bugs and enhancements that make commercial sense. Moreover, as Johnson (2006) argues, career concerns can lead paid programmers to collide and avoid revealing flaws in each others' code. Such principal agent problems do not affect FLOSS, which is based on a large group of people from within the economics profession coming together to study, understand, and improve the software without a direct monetary concern.…”

Section: The Reliability Of Open Source Softwarementioning

confidence: 99%

Should Economists Use Open Source Software for Doing Research?

Yalta

2010

Comput Econ

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“…This may be a view that is advantageous and even promoted by some proprietary software interests, but many of the significant open source software projects have paid, well-trained core workers, and many of the rest have such people contributing on a part-time basis. Indeed, the motivations for contributing to and using open source projects have begun to be better understood, with business or enterprise models and economic arguments to back them up [3,5,[11][12][13]15,[17][18][19][20]25,26].…”

Section: History and Motivationsmentioning

confidence: 99%

Directions for open source software over the next decade

Nash

2010

Futures

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Collaboration, peer review and open source software

Cited by 71 publications

References 36 publications

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Addressing Energy System Modelling Challenges: The Contribution of the Open Energy Modelling Framework (oemof)

Should Economists Use Open Source Software for Doing Research?

Directions for open source software over the next decade

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