Image: “StEmp-Tool Anhalt-Bitterfeld-Wittenberg“ © Reiner Lemoine Institut | CC BY 4.0 Cite as: DOI 10.25815/63vz-v811 Citation format: The Chicago Manual of Style, 17th Edition



Hülk, Ludwig. ‘Open Science, Collaboration and Participation in Energy System Research’, 2019. https://doi.org/10.25815/63vz-v811.

Open Energy Modelling has been built up as a research community over the last ten years aiming to bring transparency to the field using an array of Open Science methods for the planning of energy systems. The role of collaboration in the research cycle used by scientists in this engineering community is now an established Open Science practice. Similar practices of collaboration and participation outside of academia involving the public are still in their infancy. Harnessing public participation in energy planning and policy development is likely change as the energy sector is undergoing rapid changes due to its large contribution to greenhouse gases and the consequent demands for transparency and innovation to tackle climate change.

Climate and energy system modelling

The ongoing debate on Climate Change and worldwide protests led by the younger generations show the urgent need to reduce worldwide greenhouse gas emissions (Ritchie and Roser 2017). The core scientific instruments in the study of Climate Change are climate models of the earth’s atmosphere designed to simulate the current state and potential future effects of greenhouse gases on this complex global system. Methods, assumptions, results, and conclusions of the analyses conducted with these models are documented, published and discussed, for example in the IPCC Assessment Reports and peer-reviewed articles. A great amount of underlying and resulting data is freely available on the Internet and can be easily accessed using search engines. Often the data is visualized as charts, plots, maps, and often with animations (Misra 2016).

The sectoral emission shares reveal that the greatest emitters are energy supply, transport, and industry (European Environment Agency 2016). Depending on the categorisation, the energy sector comprises the supply of electricity, heat and gas. For example, the fuel consumption of a diesel car is included in transport, but the electricity consumption of an electric car is part of the electricity sector. Assignments can therefore be ambiguous and shift over time. To investigate the components and their relationships, different energy system models are developed. Energy systems models are used to cover the planning and impact of technological implementations. They encompass the provision of energy to end-users, including generation, storage, transmission, and use. This area of research is referred to as energy system modelling and, like climate modelling, is a computational science involving, above all, people in front of the computer.

Open science in energy system research

„Open Science” © Reiner Lemoine Institut | CC BY 4.0

Inspired by the open source movement, more and more research groups started to cooperate and decided to publish source code, data and results under suitable open licenses. Open Science practices have been taken on board, as Robbie Morrison described in his contribution to GenR (Morrisson 2019). A new generation of energy scientists is demanding more transparency and greater openness (Pfenninger 2017) (Hülk et al. 2018). Open Energy System Modelling has become an active driver for change in research with the aim of improving and putting energy system research to wider use and uptake in different sectors. Carbon based energy systems, like the current one using oil, coal, lignite, and gas, are mostly operated by corporations and states. The installation of renewable energies increases the number of participants in this existing network. At this point, the concepts of Open Science can provide useful methods and tools to bridge the gap between science, policy making and societal transformations.

Open Science can be useful to scientist by reducing double work and increasing the reuse of existing materials. Open licenses on (digital) research materials allow and encourage copying and adaptation. In practice, scientific work and open source development have many similarities. A good example is that commonly used permissive licenses demand proper attribution of the copyright holder while good scientific practice demands citation of the original author. In theory, these principles allow the complete traceability and reproducibility of scientific investigations and are therefore worth striving for. The formulation of scenarios, the preparation of input data sets and initialisation and calibration of an energy system model is often conducted in large research teams, often from different institutes and universities. So suitable communication channels and tools for collaboration are necessary.

Collaborative research

The current workflows and tools now have a firm footing and foundation in the interactions and daily lives of researchers, especially in the field of Open Energy System Modelling. At this point it is worth taking a look at the different definitions of working together:

Cooperation: purposeful interaction. Results and conclusions are exchanged.

purposeful interaction. Results and conclusions are exchanged. Teamwork: analogous, spatially and temporally limited cooperation

analogous, spatially and temporally limited cooperation Collaboration: simultaneous, interactive and purposeful collaboration

simultaneous, interactive and purposeful collaboration E-Collaboration: jointly designed and negotiated, computer-mediated context using shared resources (Stoller-Schai 2003)

E-Collaboration is based on software that allows the frictionless sharing and editing of documents. The most famous tools are (Ether-)Pads, web pages for text sharing, and Overleaf for LaTeX documents. The scientific use-cases are the creation of documents (e.g., project applications, reports or articles), minutes (e.g., meetings, web conferences, workshops) and data collections (e.g., literature research, parameter collections).

The requirements for the use of these tools cover technical, legal and social criteria. There is operating system independence, version control and reproducibility, access and user management. Other constraints are the server location, type of service (online-service or self-hosted) and usability (interfaces). Collaborating tools help researchers to produce open materials in a joint manner. Improvements can directly be added to a document; a merging of different versions can be reduced. One precondition is the selection of a suitable open license and the track of authorship. In the near future, these tools will play a growing role in the daily work of researchers.

Participation, stakeholder empowering and future collaboration

What are the (new) contexts and requirements for scientific work in the year 2020? In addition to fact-based results and well considered recommendations for policy making, the questions of science communication and participation arise. If we look at the findings and results of the past decade, it becomes apparent that science has foreseen the current problems, but has not sufficiently exploited the possible room for manoeuvre.

Unlike collaboration between researchers the tools and working methods are not yet established for supporting wider collaborative participation with many stakeholders groups outside of academia: as professionals, interest groups and from the general public. What is clear is that this challenge for scientists of new form of Open Science and E-collaboration is coming down the line. It is fair to speculate that energy system modelling is one such frontline discipline on the cusp of facing this challenge as there is a noticeable push from the public in terms of climate protests and an immanent technology disruption taking place in, such as in green new deal policies. Both of these drivers will lead to a need for much greater levels of participation and transparency as new policies and society wide transformation are ‘Very Likely’ to use an IPCC aphorism.

Looking at what is already in place in scientific practice and E-collaboration it can be seen that the following will be building blocks of this next generation participatory collaboration:

Energy modelling is a discipline that is put to work as science based policy making and as such can only be strengthened and help make more robust policies by the added combination of Open Science and E-Collaboration.

Overall questions and specific problems can be analysed and visualized interactively. What is additionally useful here is to combine the visualisation to speedy and verifiable access to the data and calculations used as is done with Jupyter Notebooks.

Accessible and comprehensible online tools visualise energy system models [WAM]. These are already being used for experts and for access by the public to help understand patterns of energy supply and demand.

The complexity of climate change needs collaboration between everybody. Although the scientific efforts of the IPCC can only be applauded, it has to be seen that a main role they have is to review and sort the scientific literature and there is still a herculean task of further communication of climate sciences.

Societal transformations and energy system transformation are supported by collaborative Open Science in the research cycle and as is being pointed to here in reaffirming trust in knowledge institutions via collaborative participation.

To conclude what might be called Citizen Science in other disciplines has a new core relevance in a policy orientated fields facing complex and large scale technological and societal questions. This is especially true when new generations have woken up to climate change and there is a demand for answers and action that it would seem ‘collaborative participation’ needs to be developed and scaled to the level that it is now at with internal academic collaborative research working practices — what could be called an Open Science for all.

References

Ritchie, Hannah, and Max Roser. ‘CO₂ and Greenhouse Gas Emissions’. Our World in Data, 11 May 2017. https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions.

Misra, Ria. ‘One of the Most Convincing Climate Change Visualizations We’ve Ever Seen’. Gizmodo, 2016. https://gizmodo.com/one-of-the-most-convincing-climate-change-visualization-1775743779.

European Environment Agency. ‘Sectoral Greenhouse Gas Emissions by IPCC Sector’. Data Visualization. European Environment Agency, 2016. https://www.eea.europa.eu/data-and-maps/daviz/change-of-co2-eq-emissions-2.

Morrison, Robbie. ‘An Open Energy System Modeling Community’. Generation Research, 20 November 2019. https://doi.org/10.25815/ff3b-d154.

Pfenninger, Stefan. ‘Energy Scientists Must Show Their Workings’. Nature, 2017. https://www.pfenninger.org/publications-pdf/2017%20-%20Pfenninger%20-%20Energy%20scientists%20must%20show%20their%20workings.pdf.

Hülk, Ludwig, Berit Müller, Martin Glauer, Elisa Förster, and Birgit Schachler. ‘Transparency, Reproducibility, and Quality of Energy System Analyses – A Process to Improve Scientific Work’. Energy Strategy Reviews 22 (1 November 2018): 264–69. https://doi.org/10/ggd35k.

Stoller-Schai, Daniel. ‘E-Collaboration: The Design of Internet based Collaborative Activities’, 2003. https://www1.unisg.ch/www/edis.nsf/SysLkpByIdentifier/2767/.