ORCID Profile
0000-0002-1506-4299
Current Organisation
German Climate Computing Centre
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Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-12560
Abstract: & & The perceived community demand for research data repositories to provide services ensuring that stored data comply with the FAIR principles requires transparent evaluation of such services. In previous work, the long term archiving service WDCC& sup& & /sup& (World Data Centre for Climate) at DKRZ (German Climate Computing Center, Hamburg) underwent an even-handed self-assessment along the published FAIR principles and the results are published on the DKRZ homepage& sup& & /sup& .& & & & Here, we present results of an overhaul of the previous WDCC FAIRness-assessment by subjecting datasets archived in WDCC to a number of now available objective FAIR assessment approaches which are available as questionnaires or fully-automated web applications& sup& ,4,5& /sup& . In these approaches, FAIRness is assessed using so-called metrics or maturity indicators. While the terminology is more a choice of the test provider - e.g. the term & #8216 metric& #8217 may be off-putting for some - both give quantitative results. First tests show that (meta)data archived in WDCC seem to attain a higher level of FAIRness when evaluated using questionnaires compared to the results obtained from fully-automated applications. Further work is needed to substantiate this finding.& & & & We learn that while neither one of the two evaluation approaches is ideal, they both show merit. Questionnaires & #8211 answered by knowledgeable repository staff & #8211 capture domain- and repository-specific aspects of FAIRness, like the use of controlled vocabularies in the datasets, granularity of archived datasets, reuse documentation or clear assessment of local data access protocols. However, the human-performed evaluation does not capture machine-actionability in terms of FAIR. This aspect is & #8211 naturally & #8211 very well assessed by automatic evaluation approaches, but the results strongly depend on the way the tests for FAIR metrics/maturity indicators are implemented. However, automatic tests often only assess metadata FAIRness, lack domain-specific& & & & FAIRness indicators or yield failed tests if a repositories& #8217 technical properties, e.g. the specification of authentication procedures for data access, are not compatible with what an automatic procedure is built to test for.& & & & Therefore, since WDCC has an over 30 year long history of preserving climate-science related data with a focus on reusability by the community (and beyond), FAIRness evaluations based on human-actionable questionnaires show a high degree of FAIRness. We further learn that there is an urgent need for specifically-designed automatic FAIR testing approaches taking into account domain-specific data standards and structures. Especially the availability of atmospheric and climate science related FAIR metrics/maturity indicators is very limited. We thus recommend compilations of the latter and we will aim at contributing to this effort.& & & & In our contribution, we specifically showcase strong as well as weak aspects of the WDCC service in terms of FAIRness and report on our measures to increase domain-specific FAIRness of WDCC and present recommendations for establishing FAIR indicators for (meta)data common to the Earth System Science community. We will make the results of our assessment openly available on the WDCC homepage as well as produce a corresponding Open Access peer-reviewed publication.& & & & & & & & & References:& & & & & sup& & /sup& cera-www.dkrz.de& & & & & sup& & /sup& cera-www.dkrz.de/WDCC/ui/cerasearch/info?site=fairness& & & & & sup& & /sup& ode/60731/outputs& & & & & & sup& & /sup& fairsharing.github.io/FAIR-Evaluator-FrontEnd/#!/& & & & & & sup& & /sup& www.fairsfair.eu/f-uji-automated-fair-data-assessment-tool& &
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-15391
Abstract: German climate research initiative PalMod phase II (www.palmod.de) is presented here as an exclusive ex le where the project end-product is unique, scientific paleo-climate data. PalMod-II data products include output from three state-of-the-art coupled climate models of varying complexity and spatial resolutions simulating the climate of the past 130,000 years. In addition to the long time series of modeling data, a comprehensive compilation of paleo-observation data is prepared to facilitate model-model and model-proxy intercomparison and evaluation. Being a large multidisciplinary project, a dedicated RDM (Research Data Management) approach is applied within the cross-cutting working group for PalMod-II. The DMP (Data Management Plan), as a living document, is used for documenting the data-workflow framework that defines the details of paleo-climate data life-cycle. The workflow containing the organisation, storage, preservation, sharing and long-term curation of the data is defined and tested.& In order to make the modeling data inter-comparable across the PalMod-II models and easily analyzable by the global paleo-climate community, model data standardization (CMORization) workflows are defined for in idual PalMod models and their sub-models. The CMORization workflows contain setup, definition, and quality assurance testing of CMIP61 based standardization processes adapted to PalMod-II model simulation output requirements with a final aim of data publication via ESGF2. PalMod-II data publication via ESGF makes the paleo-climate data an asset which is (re-)usable beyond the project life-time.The PalMod-II RDM infrastructure enables common research data management according to the FAIR3 data principles across all the working groups of PalMod-II using common workflows for the exchange of data and information along the process chain. Applying data management planning within PalMod-II made sure that all the data related workflows were defined, continuously updated if needed and made available to the project stakeholders. End products of PalMod-II which consist of unique long term scientific paleo-climate data (model as well as paleo-proxy data) are made available for re-use via the paleo-climate research community as well as other research disciplines (e.g., land-use, socio-economic studies etc.).1. Coupled Model Intercomparison Project phase 6 (gcm-cmip/wgcm-cmip6)2. Earth System Grid Federation (esgf.llnl.gov)3. Findable, Accessible, Interoperable, Reusable
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-13285
Abstract: & & In 2019 the Universit& #228 t& Hamburg was awarded funding for 4 clusters of excellence in the Excellence Strategy of the Federal and State Governments. One of these clusters funded by the German Research Foundation (DFG) is & #8220 CliCCS & #8211 Climate, Climatic Change, and Society& #8221 .& The scientific objectives of CliCCS are achieved within three intertwined research themes, on the Sensitivity and Variability in the Climate System, Climate-Related Dynamics of Social Systems, and Sustainable Adaption Scenarios. Each theme is structured into multiple projects addressing sub-objectives of each theme. More than 200 researchers the Hamburg University, but also other connected research centers and partner institutions & are involved and almost all of them are using but mainly produce new data.& & & & Research data is produced with great effort and is therefore one of the valuable assets of scientific institutions. It is part of good scientific practice to make research data freely accessible and available in the long term as a transparent basis for scientific statements.& & & & Within the interdisciplinary cluster of excellence CliCCS, the type of research data is very different. The data range from results from physically dynamic ocean and atmosphere models, to measurement data in the coastal area, to survey and interview data in the field of sociology.& & & & & The German Climate Computing Center (DKRZ) is taking care on the Research Data Management and supports the researchers in creating data management plans, keeping naming conventions or simply finding the optimal repository to publish the data. The goal is to store and long-term archiving of the data, but also to ensure the quality of the data and thus to facilitate potential reuse.& &
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-5965
Abstract: & & Large scale transient climate simulations and their intercomparison with paleo data within the German initiative PalMod (www.palmod.de, currently in phase II) provides an exclusive ex le of applying a Data Management Plan (DMP) to conceptualise& data workflows within and outside a large multidisciplinary project. PalMod-II data products include output of three state-of-the-art climate models with various coupling complexities and spatial resolutions& simulating the climate of the past 130,000 years. Additional to the long time series of model data, a comprehensive compilation of paleo-observation data (including a model-observation-comparison toolbox, Baudouin et al, 2021 EGU-CL1.2) is envisaged for validation.& & & & & Owing to the enormous amount of data coming from models and observations, produced and handled by different groups of scientists spread across various institutions, a dedicated DMP as a living document provides a data-workflow framework for exchange and sharing of data within and outside the PalMod community. The DMP covers the data life cycle within the project starting from its generation (data formats and standards), analysis (intercomparison with models and observations), publication (usage, licences), dissemination (standardised, via ESGF) and finally archiving after the project lifetime. As an active and continually updated document, the DMP ensures the ownership and responsibilities of data subsets of various working groups along with their data sharing/reuse regulations within the working groups in order to ensure a sustained progress towards the project goals.& & & & & This contribution discusses the current status and challenges of the DMP for PalMod-II which covers the details of data produced within various working groups, project-wide workflow strategy for sharing and exchange of data, as well as a definition of a PalMod-II variable list for ESGF standard publication. The FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles play a central role and are proposed for the entire life cycle of PalMod-II data products (model and proxy paleo data) for sharing/reuse during and after the project lifetime.& & & & & br& & br& & &
Publisher: Copernicus GmbH
Date: 04-03-2021
DOI: 10.5194/EGUSPHERE-EGU21-8903
Abstract: & & Since few years Research Data Management is becoming an increasingly important part of scientific projects regardless of the number of topics or subjects, researchers or institutions involved. The bigger the project, the more are the data organization and data management requirements in order to assure the best outcome of the project. Despite this, projects rarely have clear structures or responsibilities for data management. The importance of clearly defining data management and also budgeting for it is often underestimated and/or neglected. A rather scarce number of reports and documentations explaining the research data management in certain projects and detailing best practice ex les can be found in the current literature. & Additionally, these are often mixed up with topics of the general project management. Furthermore, these ex les are very focused on the certain issues of the described projects and thus, a transferability (or general application) of provided methods is very difficult.& & & & This contribution presents generic concepts of research data management with an effort to separate them from general project management tasks. Project size, details among the ersity of topics and the involved researcher, play an important role in shaping data management and determining which methods of data management can add value to the outcome of a project. We especially focus on different organisation types, including roles and responsibilities for data management in projects of different sizes. Additionally, we show how and when also education should be included, but also how important agreements in a project are.& &
Publisher: Ubiquity Press, Ltd.
Date: 2022
DOI: 10.5334/DSJ-2022-007
No related grants have been discovered for Andrea Lammert.