general
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* To foster wider use of ML technologies in data driven space research, demonstrate ML capabilities and generate a wider discussion on further possible applications of ML | * To foster wider use of ML technologies in data driven space research, demonstrate ML capabilities and generate a wider discussion on further possible applications of ML | ||
- | The goal is to build a multipurpose toolset for ML-based data analysis that will be applicable to a range of scientific research questions in planetary science with minor or easily-achievable customization efforts. | + | The goal is to build a multipurpose toolset for ML-based data analysis that will be applicable to a range of scientific research questions in planetary science with minor or easily-achievable customization efforts. We provide both, trained models as well as ML code, all of which are free to use and to be adapted by the user. The term "ML tool" refers in our case to [[https:// |
- | The tools will be shared and made accessible to the wider planetary science community through this webpage, the ML Portal. The ML work package | + | The tools are shared and made accessible to the wider planetary science community through this webpage, the ML Portal, and our [[https:// |
===== Methodology ===== | ===== Methodology ===== | ||
- | In order to reach our goal of building versatile ML based tools for data analysis in planetary science, we pursue a bottom up approach, i.e., building tools that solve a diverse set of specific problems in planetary science with the aim of generalizing the solutions as much as possible. To achieve this, the community was asked to provide scientific use cases during the proposal phase of the project. Out of these proposed cases, a representative set of science cases was selected and the respective institutes were included as beneficiaries. | + | In order to reach our goal of building versatile ML based tools for data analysis in planetary science, we pursue a bottom up approach, i.e., building tools that solve a diverse set of specific problems in planetary science with the aim of generalizing the solutions as much as possible. To achieve this, the community was asked to provide scientific use cases during the proposal phase of the project. Out of these proposed cases, a representative set of [[: |
The idea is that the technical partners (KNOW, Uni-Passau and ACRI-ST) will closely collaborate with the scientific partners of our WP to build tools that solve “real life” scientific problems and at the same time provide the flexibility necessary to adapt the resulting toolset to other related problems in planetary science with passable effort. | The idea is that the technical partners (KNOW, Uni-Passau and ACRI-ST) will closely collaborate with the scientific partners of our WP to build tools that solve “real life” scientific problems and at the same time provide the flexibility necessary to adapt the resulting toolset to other related problems in planetary science with passable effort. | ||
- | A careful assessment of these science cases provided a solid basis to determine the technologies that would be best fitted to build the tools. It turned out that ML tools to classify, filter and search time series data as well as Deep Learning (DL) based classifiers of 2D (e.g., surface images or spectra) and video data, such as Convolutional Neural Networks (CNNs) and Deep Neural Networks (DNNs) in general as well as other techniques (as e.g., Self Organizing Maps) will be applied. Supervised as well as unsupervised approaches, with the latter also being able to leverage unlabelled data, are the technologies expected to benefit the community the most. | + | A careful assessment of these [[: |
- | Furthermore, | + | Furthermore, |
- | ===== Work Package Beneficiaries and Partners | + | ===== Timeline |
- | | \\ **Work Package Beneficiaries | + | We plan to have applicable |
- | | \\ ACRI-ST| \\ ACRI-ST, France| | + | |
- | | \\ AOP| \\ Armagh Observatory and Planetarium, | + | |
- | | \\ DLR| \\ Deutsches Zentrum für Luft- und Raumfahrt, Germany| | + | |
- | | \\ KNOW| \\ Know-Center GmbH, Austria| | + | |
- | | \\ IAP-CAS| \\ Institute | + | |
- | | \\ INAF| \\ National Institute for Astrophysics, Italy| | + | |
- | | \\ IWF-OEAW| \\ Space Research Institute, Austrian Academy of Sciences, Austria| | + | |
- | | \\ LMSU| \\ M.V. Lomonosov Moscow State University, Russia| | + | |
- | | \\ UNIPASSAU| \\ University of Passau, Germany| | + | |
- | ===== Science Cases ===== | + | The integration of the data sets and the data products |
- | + | ||
- | During | + | |
- | + | ||
- | ^Proposer | + | |
- | |IAP-CAS | + | |
- | | ::: |[[: | + | |
- | |INAF |[[: | + | |
- | |DLR |[[: | + | |
- | |AOP |[[: | + | |
- | |GMAP |[[: | + | |
- | |IWF-OEAW | + | |
- | |LMSU |[[: | + | |
general.1614156769.txt.gz · Last modified: 2021/02/24 09:52 by admin