Open Science and Open Source @EGU - Interesting Sessions and Debates
Dee Kay
Compiled by Riccardo Rigon:
EOS4.3 The evolving open-science landscape in geosciences: open data, software, publications and community initiatives
In recent years, the geoscience community has been making strides towards making our science more open, inclusive, and accessible, driven both by individual- or community-led initiatives. Open-source software, accessible codebases and open online collaboration resources (such as GitHub, VHub, etc.) are becoming the norm in many disciplines. The open-access publishing landscape has been changing too: several geoscience journals have defined data availability policies, and many publishers have introduced green and gold open-access options to their journal collections. Pre-print servers and grassroots diamond open-access journals are changing the readiness with which scholarly content can be accessed beyond the traditional paywall model.
However, good scientific practice requires research results to be reproducible, experiments to be repeatable and methods to be reusable. This can be a challenge in geosciences, with available data sets that are becoming more complex and constantly superseded by new, improved releases. Similarly, new models and computational tools keep emerging in different versions and programming languages, with a large variability in the quality of the documentation. Moreover, how data and models are linked together towards scientific output is very rarely documented in a reproducible way. As a result, very few published results are reproducible for the general reader.
This session is designed to gain a community overview of the current open-science landscape and how this is expected to evolve in the future. It aims to foster a debate on open science, lower the bar for engaging in open science and showcase examples, including software and other instruments for assisting open research. This may include software and tools, open science dissemination platforms (such as pre-print servers and journals), the teams driving the development of open-science resources and practices, and the regulatory moves towards standardising open access in the scientific community and what those policies mean in practice. This session should advance the discussion on open and reproducible science, highlight its advantages and also provide the means to bring this into practice.
Share:https://meetingorganizer.copernicus.org/EGU22/session/43037
Convener: Remko C. NijzinkECS| Co-conveners: Riccardo Rigon, Stan Schymanski
SC3.13 Open science beyond open-access publications: how can we share our code and data?
Knowledge sharing in academia has been considered indispensable and is becoming a priority in most European funding schemes. Although we are already quite familiar with the different possibilities to publish our results in open-access journals, open science means way more than that. Open science aims at opening up research processes and granting access to research outputs to researchers, professionals and amateur scientists. There are different ways to ensure the storage and reusability of our data, making it available to other scientists. Furthermore, most of the scientific disciplines migrate their analyses to open-source environments (e.g., R, Phyton). However, tons of code produced remain stored in our personal computers either because we do not know the appropriate tools to share them with our colleagues or because we believe that it is not well structured.
In this short course, you would learn how to establish links between publications, data, software and methods. Hence, we will discuss with our experts: i) the options to share our data and code with other peers, ii) obtain some tips to better organize our scripts, and iii) uncover potential barriers to sharing research and discuss possible solutions.
Convener: Elisabet Martinez-Sancho| Co-convener: Layla Márquez San Emeterio
GDB3- https://meetingorganizer.copernicus.org/EGU22/session/42789
Great Debate on Open Science - This is an open debate. Participate!
Convener: Francesca Pianosi| Co-conveners: Leonardo UiedaECS, Jamie FarquharsonECS
Open Science represents research that is collaborative, transparent, and accessible. This includes providing open access to all scientific outputs, such as publications, data, methods, software, and more. Open Science practices are intended to improve transparency, reproducibility, and dissemination of new knowledge. By enabling greater usability of data and methods, it has the potential to improve the productivity of the research community.
Despite best intentions by the scientific community, several barriers often prevent making data, software, and publications fully open and accessible to all. For example, sharing of data may be constrained by confidentiality issues or protective data policies by private and public organisations. Furthermore, storing and sharing large datasets comes with technical challenges and costs that may be difficult to face for individuals and organisations. Similarly, sharing methods and software in a format accessible to others may require additional effort, for instance the application of software engineering best practices, that researchers may be reluctant to undertake due to lack of adequate reward, incentives, or recognition. The drive towards Open Science may also be met with reticence or resistance by individuals or organisations that are currently well-served by the status quo.
In this Great Debate we invite our panel members and the audience from all geosciences to reflect on the following questions:
* How can universities, funding bodies, and publishers promote Open Science?
* What more can structural initiatives such as Plan S or DORA do to support Open Science?
* What are some successful examples and barriers yet to be overcome?
* How can researchers and administration help remove those barriers?
* Are individual researchers primarily responsible for advancing Open Science, or should institutions, publishers and funding agencies take main responsibility?
* How can we align the goals of individual researchers (i.e. careers/publishing) and the scientific community (i.e. gaining knowledge but also avoiding duplication of efforts)?
* What are the priorities to bring Open Science into practice (e.g. open access to articles, data, code, workflows)?
* How does commitment to Open Science impact science-industry collaborations and translation of science into practice?
* What are pitfalls in Open Science? Are there disadvantages?
ESSI2.9 -Open SourceSoftware Tools in Geospatial Research
In recent decades, the advent in geoinformation technology has played an increasingly important role in determining various parameters that characterize the Earth's environment. This session invites contributions focusing on modern open-source software tools developed to facilitate the analysis of mainly geospatial data in any branch of geosciences for the purpose of better understanding Earth’s natural environment. We encourage the contribution of any kind of open source tools, including those that are built on top of global used commercial GIS solutions. Potential topics for the session include the presentation of software tools developed for displaying, processing and analysing geospatial data and modern cloud webGIS platforms and services used for geographical data analysis and cartographic purposes. We also welcome contributions that focus on presenting tools that make use of parallel processing on high performance computers (HPC) and graphic processing units (GPUs) and also on simulation process models applied in any field of geosciences.
Share:https://meetingorganizer.copernicus.org/EGU22/session/42425
Convener: George P. Petropoulos| Co-conveners: Ionut Cosmin Sandric, Prashant Kumar Srivastava, Konstantinos BischiniotisECS, Daniela Silva-FuzzoECS
Rapid, reproducible, and robust hydrosystem modeling for decision support: worked examples and open-source software tools | Virtual PICO
To provide support for resource management decision making, computational modeling workflows in hydrosystem simulation need to be efficient, reproducible, and robust with regard to the risk of unwanted outcomes. Unfortunately, each of these three attributes is difficult to achieve in practice; aspirations to simultaneously achieve all of them are truly lofty. Too often, modeling analyses are inefficient, the workflow is largely opaque and unknown, and the important simulated outcomes lack the context of uncertainty and/or risk.
This session calls for submissions that demonstrate rapid, reproducible and/or robust modeling through worked examples and software tools (a preference for open source). The worked examples should demonstrate how the researcher aspired to be rapid, reproducible, and robust; we are interested in the process and approach as much as the results. We aim to stimulate discussion based on lessons learned and results presented, for other researchers and practitioners to build on. We particularly welcome descriptions of trials and tribulations: What was difficult? What didn’t work? How were these issues overcome?
Software tools may include:
• techniques to automate modeling workflow elements or increase efficiency, reproducibility, robustness of decision-support modeling elements.
• frameworks to build models from original data in flexible ways that may enable hypothesis testing in the form of changing discretization, process representation, and other modeling decisions.
• multi-model frameworks such as Bayesian-model selection/combination, as well as frameworks to accommodate model structural error.
• Methods for uncertainty analysis, data assimilation, and management optimization under uncertainty in the decision-support context.
• machine-learning approaches for decision support analyses.
Share:https://meetingorganizer.copernicus.org/EGU22/session/43407
Convener: Anneli GuthkeECS Co-conveners: Jeremy White, Michael Fienen, Catherine Moore
ITS3.1/SSS1.2
https://www.egu.eu/news/689/egu-announces-new-edi-logo-for-the-2021-general-assembly/
Participatory Citizen Science and Open Science as a new era of environmental observation for society
Citizen science (the involvement of the public in scientific processes) is gaining momentum across multiple disciplines, increasing multi-scale data production on Earth Sciences that is extending the frontiers of knowledge. Successful participatory science enterprises and citizen observatories can potentially be scaled-up in order to contribute to larger policy strategies and actions (e.g. the European Earth Observation monitoring systems), for example to be integrated in GEOSS and Copernicus. Making credible contributions to science can empower citizens to actively participate as citizen stewards in decision making, helping to bridge scientific disciplines and promote vibrant, liveable and sustainable environments for inhabitants across rural and urban localities.
Often, citizen science is seen in the context of Open Science, which is a broad movement embracing Open Data, Open Technology, Open Access, Open Educational Resources, Open Source, Open Methodology, and Open Peer Review. Before 2003, the term Open Access was related only to free access to peer-reviewed literature (e.g., Budapest Open Access Initiative, 2002). In 2003 and during the “Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities”, the definition was considered to have a wider scope that includes raw research data, metadata, source materials, and scholarly multimedia material. Increasingly, access to research data has become a core issue in the advance of science. Both open science and citizen science pose great challenges for researchers to facilitate effective participatory science, yet they are of critical importance to modern research and decision-makers.
We want to ask and find answers to the following questions:
Which approaches and tools can be used in Earth and planetary observation?
What are the biggest challenges in bridging between scientific disciplines and how to overcome them?
What kind of participatory citizen scientist involvement (e.g. how are citizen scientists involved in research, which kind of groups are involved) and open science strategies exist?
How to ensure transparency in project results and analyses?
What kind of critical perspectives on the limitations, challenges, and ethical considerations exist?
How can citizen science and open science approaches and initiatives be supported on different levels (e.g. institutional, organizational, national)?
Share:https://meetingorganizer.copernicus.org/EGU22/session/43571
Co-organized by BG2/CL3.2/ERE1/ESSI3/GM12/GMPV1/HS12/NH9/OS4/SM1/SSP1
Convener: Taru Sandén| Co-conveners: Daniel DörlerECS, Florian HeiglECS, Dilek FraislECS, Tamer Abu-Alam