TY - JOUR A1 - Pfenninger, Stefan A1 - DeCarolis, Joseph A1 - Hirth, Lion A1 - Quoilin, Sylvain A1 - Staffell, Iain T1 - The importance of open data and software: Is energy research lagging behind? JF - Energy Policy N2 - Energy policy often builds on insights gained from quantitative energy models and their underlying data. As climate change mitigation and economic concerns drive a sustained transformation of the energy sector, transparent and well-founded analyses are more important than ever. We assert that models and their associated data must be openly available to facilitate higher quality science, greater productivity through less duplicated effort, and a more effective science-policy boundary. There are also valid reasons why data and code are not open: ethical and security concerns, unwanted exposure, additional workload, and institutional or personal inertia. Overall, energy policy research ostensibly lags behind other fields in promoting more open and reproducible science. We take stock of the status quo and propose actionable steps forward for the energy research community to ensure that it can better engage with decision-makers and continues to deliver robust policy advice in a transparent and reproducible way. KW - Modelling KW - Data KW - Open source KW - Open data KW - Transparency KW - Reproducibility Y1 - 2016 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b1570-opus4-22791 U6 - https://doi.org/10.1016/j.enpol.2016.11.046 SN - 0301-4215 VL - 101 SP - 211 EP - 215 PB - Elsevier Ltd ER - TY - JOUR A1 - Stefan, Pfenninger A1 - Hirth, Lion A1 - Schlecht, et. al., Ingmar T1 - Opening the black box of energy modelling: Strategies and lessons learned JF - Energy Strategy Reviews N2 - The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research. Y1 - 2018 U6 - https://doi.org/10.1016/j.esr.2017.12.002 VL - 19 SP - 63 EP - 71 ER -