Research data management in agricultural sciences in Germany: We are not yet where we want to be

To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond

Data Steward Service Center (DSSC): FAIRagro RDM-Expertise Hub

The Data Steward Service Center (DSSC) is the central institution within FAIRagro to develop data management tools based on the needs of the scientific community. The DSSC organizes the continuous exchange of RDM knowledge and experience with other institutions, channels user requests from the community, and transfers knowledge from the FAIRagro task areas to the FAIRagro data stewards. FAIRagro data stewards are experts in the field of RDM for agrosystems research supervising and will train data curators in our community. Data stewards have core competencies in research data management (e.g., cross-scale from genes, phenomics, management to region; sensitive data, remote sensing, time series, plant, soil and related FAIRagro data). Knowledge and expertise is pooled to provide the full range of expertise to the community in one place to foster the coalescence of the community. The DSSC is headed by a coordinator and will house five data stewards, who are active in the community e.g. train data curators, give legal support. In the course of the project, further institutional or project data stewards will be integrated and the pool of experts will be further expanded. The network to the other NFDI consortia is continuously growing

N-Umsatz und Spurengasemissionen typischer Biomassefruchtfolgen zur Biogaserzeugung in Norddeutschland

Im Rahmen des Verbundprojektes Biogas-Expert an der CAU-Kiel wurden an zwei Standorten Schleswig-Holsteins veschiedene Fruchtfolgen zur Bereitstellung von Biogassubstraten unter Verwendung von Biogasgüllen als N-Dünger durchgeführt. Maismonokultur wies die höchsten Trockenmasseerträge auf, wobei keine signifikanten Unterschiede in den Erträgen zwischen Biogasgärresten, organischen N-Düngern und mineralischen Düngern ermittelt wurden. Während in Bezug auf die N-Düngeform bei N2O- und Nitratauswaschungsverlusten kein Einfluss der N-Form auf die Höhe der Verluste festgestellt wurde, war die Düngung mit Biogasgüllen mit signifikant erhöhten NH3-Verlusten verknüpft. Eine abschließende Bewertung der Produktionssysteme ist erst durch Analyse der experimentellen Ergebnisse mit einem Systemmodell möglich

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

FAIRagro: Ein Konsortium in der Nationalen Forschungsdateninfrastruktur (NFDI) für Forschungsdaten in der Agrosystemforschung : Herausforderungen und Lösungsansätze für den Aufbau einer FAIRen Forschungsdateninfrastruktur

FAIRagro ist ein Konsortium in der Nationalen Forschungsdateninfrastruktur (NFDI) in Deutschland um Forschungsdaten der Agrosystemforschung FAIR – d. h. auffindbar (F), zugänglich (A), interoperabel (I) und für andere Forschende domänenübergreifend nachnutzbar (R) zu machen. In der deutschen Forschungslandschaft rund um nachhaltige Agrosysteme werden heterogene Forschungsdaten erhoben und nur zum Teil in existierenden Forschungsdatenrepositorien veröffentlicht. Das Spektrum der Datenformate erstreckt sich beispielsweise von Laborergebnissen, über Satellitenbilder bis hin zu qualitativen Interviews mit Landwirt:innen. Um diese Daten zukünftig für Forschende verschiedener Disziplinen besser auffindbar und nachnutzbar zu machen, wird FAIRagro eine Forschungsdateninfrastruktur (FDI) für die Agrosystemforschung einrichten, in der disziplinäre Dateninfrastrukturen miteinander verknüpft werden. Spezifische Herausforderungen im Forschungsdatenmanagement (FDM) fachlicher Disziplinen wie Pflanzenzüchtung, integrierter Pflanzenschutz oder Agrarrobotik werden als Use Cases in FAIRagro adressiert und für diese Lösungen entwickelt. Darüber hinaus wird FAIRagro ein Netzwerk aus direkten Ansprechpersonen für Fragen zum Forschungsdatenmanagement in der Agrosystem-Community bereitstellen. In Übereinstimmung mit den Zielsetzungen der NFDI und der European Open Science Cloud ist FAIRagro aktiv an der konzeptionellen Implementierung eines interoperablen Datenraums beteiligt

Rainfed winter wheat cultivation in the North German Plain will be water limited under climate change until 2070

Background: We analysed regionalised ECHAM6 climate data for the North German Plains (NGP) in two time slots from 1981 to 2010 and 2041 to 2070. - Results: The annual mean temperature will increase significantly (by about 2 °C) that will result in shorter growing periods since the sum of degree days until harvest will be reached earlier. Even if the amount of total precipitation does not change there appears to be a shift towards increased winter precipitation and thus noticeable reduced summer precipitation. - Conclusions: Through the example of winter wheat we show a future limitation of water availability if yields are to be maintained or even increase

Abundance of adverse environmental conditions during critical stages of crop production in Northern Germany

BACKGROUND: Understanding the abundance of adverse environmental conditions e.g. frost, drought, and heat during critical crop growth stages, which are assumed to be altered by climate change, is crucial for an accurate risk assessment for cropping systems. While a lengthening of the vegetation period may be beneficial, higher frequencies of heat or frost events and drought spells are generally regarded as harmful. The objective of the present study was to quantify shifts in maize and wheat phenology and the occurrence of adverse environmental conditions during critical growth stages for four regions located in the North German Plain. First, a statistical analysis of phenological development was conducted based on recent data (1981–2010). Next, these data were used to calibrate the DSSAT-CERES wheat and maize models, which were then used to run three climate projections representing the maximum, intermediate and minimum courses of climate development within the RCP 8.5 continuum during the years 2021–2050. By means of model simulation runs and statistical analysis, the climate data were evaluated for the abundance of adverse environmental conditions during critical development stages, i.e. the stages of early crop development, anthesis, sowing and harvest. RESULTS: Proxies for adverse environmental conditions included thresholds of low and high temperatures as well as soil moisture. The comparison of the baseline climate and future climate projections showed a significant increase in the abundance of adverse environmental conditions during critical growth stages in the future. The lengthening of the vegetation period in spring did not compensate for the increased abundance of high temperatures, e.g. during anthesis. CONCLUSIONS: The results of this study indicate the need to develop adaptation strategies, such as implementing changes in cropping calendars. An increase in frost risk during early development, however, reveals the limited feasibility of early sowing as a mitigation strategy. In addition, the abundance of low soil water contents that hamper important production processes such as sowing and harvest were found to increase locally

Technical components supporting publication of research data.

Technical components supporting publication of research data.</p

Searching for research data.

a) How often do data providers and users use different available search tools to search for relevant data and literature publications (N = 149–153; Q37)? b) Respondents’ assessment of how they rate the formulation of clear and sensitive search terms when searching for relevant data and articles, especially in interdisciplinary context (N = 160; Q38).</p

Incentives to encourage researchers to publish data more frequently at their institution.

Incentives to encourage researchers to publish data more frequently at their institution.</p