Description: Der Report des Helmholtz Open Science Workshops „Zugang zu und Nachnutzung von wissenschaftlicher Software“ #hgfos16 behandelt die Themen Standards und Qualitätssicherung; Reproduzierbarkeit; Lizenzierung und weitere rechtliche Aspekte; Zitation und Anerkennung; Sichtbarkeit und Modularität; Geschäftsmodelle; Personal, Ausbildung, Karrierewege. Diese Themen sind eng miteinander verzahnt. Für jeden Themenbereich werden jeweils die Relevanz, Fragestellungen, Herausforderungen, mögliche Lösungsansätze und Handlungsempfehlungen betrachtet.

Description: In Geosciences – like in most other communities – scientific work strongly depends on software. For big data analysis, existing (closed or open source) program packages are often mixed with newly developed codes. Different versions of software components and varying configurations can influence the result of data analysis. This often makes reproducibility of results and reuse of codes very difficult. Policies for publication and documentation of used and newly developed software, along with best practices, can help tackle this problem. Within the Helmholtz Association a Task Group “Access to and Re-use of scientific software” was implemented by the Open ScienceWorking Group in 2016. The aim of the Task Group is to foster the discussion about scientific software in the Open Science context and to formulate recommendations for the production and publication of scientific software, ensuring open access to it. As a first step, a workshop gathered interested scientists from institutions across Germany. The workshop brought together various existing initiatives from different scientific communities to analyse current problems, share established best practices and come up with possible solutions. The subjects in the working groups covered a broad range of themes, including technical infrastructures, standards and quality assurance, citation of software and reproducibility. Initial recommendations are presented and discussed in the talk. They are the foundation for further discussions in the Helmholtz Association and the Priority Initiative “Digital Information” of the Alliance of Science Organisations in Germany. The talk aims to inform about the activities and to link with other initiatives on the national or international level.

Description: In this paper we present general recommendations for dealing with research software. We discuss incentives and metrics, software development and documentation, accessibility, publication and transfer strategies, infrastructures, quality assurance, licensing and other legal topics, education and training, as well as policies and guidelines. We consider research software, alongside text and data, as an essential element of open science. We argue that research software should be treated and acknowledged as a discrete product of the research process.

Description: This open access book presents the results of three years collaboration between earth scientists and data scientists, in developing and applying data science methods for scientific discovery. The book will be highly beneficial for other researchers at senior and graduate level, interested in applying visual data exploration, computational approaches and scientifc workflows.

Description: Modern digital scientific workflows - often implying Big Data challenges - require data infrastructures and innovative data science methods across disciplines and technologies. Diverse activities within and outside HGF deal with these challenges, on all levels. The series of Data Science Symposia fosters knowledge exchange and collaboration in the Earth and Environment research community. We invited contributions to the overarching topics of data management, data science and data infrastructures. The series of Data Science Symposia is a joint initiative by the three Helmholtz Centers HZG, AWI and GEOMAR Organization: Hela Mehrtens and Daniela Henkel (GEOMAR)

Description: Earth System Science (ESS) relies on the availability of data from varying resources and ranging over different disciplines. Hence, data sources are rich and diverse, including observatories, satellites, measuring campaigns, model simulations, case studies, laboratory experiments as well as citizen science etc. At the same time, practices of professional research data management (RDM) are differing significantly among various disciplines. There are many well-known challenges in enabling a free flow of data in the sense of the FAIR criteria. Such are data quality assurance, unique digital identifiers, access to and integration of data repositories, just to mention a few. The Helmholtz DataHub Earth&Environment is addressing digitalization in ESS by developing a federated data infrastructure. Existing RDM practices at seven centers of the Helmholtz Association working together in a joint research program within the Research Field Earth and Environment (RF E&E) are harmonized and integrated in a comprehensive way. The vision is to establish a digital research ecosystem fostering digitalization in geosciences and environmental sciences. Hereby, issues of common metadata standards, digital object identifiers for samples, instruments and datasets, defined role models for data sharing certainly play a central role. The various data generating infrastructures are registered digitally in order to collect metadata as early as possible and enrich them along the flow of the research cycle. Joint RDM bridging several institutions relies on professional practices of distributed software development. Apart from operating cross-center software development teams, the solutions rely on concepts of modular software design. For example, a generic framework has been developed to allow for quick development of tools for domain specific data exploration in a distributed manner. Other tools incorporate automated quality control in data streams. Software is being developed following guiding principles of open and reusable research software development. A suite of views is being provided, allowing for varying user perspectives, monitoring data flows from sensor to archive, or publishing data in quality assured repositories. Furthermore, high-level data products are being provided for stakeholders and knowledge transfer (for examples see https://datahub.erde-und-umwelt.de). Furthermore, tools for integrated data analysis, e.g. using AI approaches for marine litter detection can be implemented on top of the existing software stack. Of course, this initiative does not exist in isolation. It is part of a long-term strategy being embedded within national (e.g. NFDI) and international (e.g. EOSC, RDA) initiatives.

Description: 〈jats:p〉Human activities, such as global warming and nutrient pollution, are posing significant threats to the ecological interactions and biodiversity in aquatic environments [1]. The German Bight, a highly dynamic coastal region of the North Sea, has been subject to considerable warming and nutrient fluctuations over recent decades. These changes have had profound impacts on the plankton communities in this area, leading to a swift reorganization of both phyto- [2] and zooplankton functional structures [3]. While the effects of these changes on individual phyto- and zooplankton levels have been well-documented, our understanding of how plankton interactions respond to these environmental stressors remains limited. In this study, we hypothesize that the synergy of warming and nutrient limitation will alter plankton network interactions, resulting in a shift towards consumers being controlled by resources. We approach this hypothesis from the perspective of Gunderson and Holling’s adaptive cycle metaphor [4]. The metaphor describes ecosystem development as alternating phases of stability and reorganization, being shaped by three systemic properties: the system’s potential available for future change, the connectedness among its internal variables, and its resilience in the light of perturbations. For the quantification of the adaptive cycle, we use a method developed by zu Castell and Schrenk [5,6]. Based on the most comprehensive timeseries available in marine environments, we infer a dynamic network of information transfer, which allows us to study the evolving interaction pattern between phyto-and zooplankton. We discuss this pattern in the context of the adaptive cycle phases and alternative measures of system resilience. To our knowledge, our study is the first to provide a holistic analysis of plankton network interactions in marine environments, considering both phyto- and zooplankton species. This approach offers a deeper understanding of how human-induced impacts affect the foundation of marine food webs.   [1] E. Merz, E. Saberski, L. J. Gilarranz, P. D. F. Isles, G. Sugihara, C. Berger, and F. Pomati, Disruption of ecological networks in lakes by climate change and nutrient fluctuations, Nature Climate Change (2023). [2] J. Di Pane, K. H. Wiltshire, M. McLean, M. Boersma, and C. L. Meunier, Environmentally induced functional shifts in phytoplankton and their potential consequences for ecosystem functioning. Global Change Biology, 28, 2804–2819 (2022). [3] M. M. Deschamps, M. Boersma, C. L. Meunier, I. V. Kirstein, K. H. Wiltshire, and J. Di Pane, Major shift in the copepod functional community of the southern North Sea and potential environmental drivers. ICES Journal of Marine Science, 0, 1–13 (2023). [4] L. H. Gunderson and C. S. Holling. Panarchy: understanding transformations in human and natural systems (Island, Washington, D.C., 2002). [5] W. zu Castell, and H. Schrenk, Computing the adaptive cycle, Scientific Reports 2020(10):18175 (2020). [6] H. Schrenk, C. Garcia-Perez, N. Schreiber, and W. zu Castell, QtAC: an R-package for analyzing complex systems development in the framework of the adaptive cycle metaphor, Ecological Modelling 466:109860 (2022).〈/jats:p〉

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉The Digital Earth project aimed for the integration of data science and Earth science. Here, we reflect on the main lessons learned that include the need for interdisciplinary collaboration, thinking out of the box, the concept of ‘thinking in workflows’ and models for the sustainable implementation of scientific software, data infrastructure and policies.〈/jats:p〉

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉Data-driven science has turned into a fourth fundamental paradigm of performing research. Earth System Science, following a holistic approach in unraveling the complex network of processes and interactions shaping system Earth, particularly profits from embracing data-driven approaches next to observation and modeling. At the end, increasing digitalization of Earth sciences will lead to cultural transformation towards a Digital Earth Culture.〈/jats:p〉

Description: 〈jats:title〉Abstract〈/jats:title〉〈jats:p〉Digital Earth is a project funded by the German Helmholtz Association with all centers of the research field Earth and Environment involved. The main goal of the Digital Earth project is to develop and bundle data science methods in extendable and maintainable scientific workflows that enable natural scientists in collaboration with data scientists to achieve a deeper understanding of the Earth system. This has been achieved by developing solutions for data analysis and exploration with visual and computational approaches with data obtained in a SMART monitoring approach and modeling studies, accompanied by a continuous evaluation of the collaboration processes. In this chapter, the history, setup, and focus of the Digital Earth project are described.〈/jats:p〉