ALBERT

Description: This data was collected as part of the Polarstern PS113 expedition to obtain insights into primary productivity on a latitudinal transect in the Atlantic Ocean. In-situ experiments of stable isotope (13C) uptake were conducted on board in triplicates of 1L pre-acid washed polycarbonate bottles. In detail, samples were spiked with Na13CO3 at a final 13C concentration of 200 µmol L-1. Experiments were terminated after 24h incubation and filter on a 0.7 precombusted polycarbonate filter. Samples were snap fronzen and stored at -80°C while at sea. Prior analysis, samples were acid fumed and dried. Samples were analysed on a PDZ Europa ANCA-GSL elemental analyzer interfaced to a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) by the Isotopic Laboratory at the UC Davis, California campus. This data reflects high-resolution spatial variations in primary productivity.

Description: This data set was collected in support of an investigation of the variability of particulate organic matter content and composition across a high-resoultion latitudinal transect across the Atlantic Ocean during the PS113 expedition. 4L of seawater from the clean ships' underway system were filtered on a 0.7 µm pre-combusted GFF filter. Samples were snap-frozen and stored at -80°C while at sea. Samples were acid fumed and dried before analyses. Particulate organic carbon and particulate nitrogen contents were measured using an Euro EA elemental analyzer (CHNS; EuroVector, Italy). This data reflects high-resolution spatial variabilites in particulate organic carbon and particulate nitrogen concentrations in surface waters accompanied by few samples from higher depths (0 - 400 m).

Description: This data was collected to investigate spatial differences in dissolved inorganic nutrient concentrations in surface waters of the Atlantic Ocean as part of the PS113 expedition. Water samples for dissolved inorganic nutrient concentrations including Nitrate, Silicate and Phosphate were filtered through a 0.2 µm syringe filter and stored at -80°C while at sea. Nutrient concentrations were assayed on an Evolution 3 Alliance Autoanalyser and calibrations were corrected for concentrations using certified reference material (CRM) 7602a (JAMSTEC; JAPAN) and MERCK STD (NIST-Standard). Concentrations were calculated by means of standard colorimetric techniques (Grasshoff, Kremling, & Ehrhardt, 2009).

Description: Samples in this dataset were collected at the long-term ecological research (LTER) site HAUSGARTEN in Fram Strait, and the central Arctic Ocean. On board, the samples were fixed with formalin in a final concentration of 2% for 10 – 12 hours, then filtered onto 0.2 µm polycarbonate Nucleopore Track-Etched filters, and stored at -20°C for further analysis. Cell abundances of the groups Alteromonas, Bacteroidia, Polaribacter, Gammaproteobacteria and the SAR11 clade were asses using CAtalyzed reporter deposition Fluorescence In Situ Hybridization (CARD-FISH) following the protocol established by (Pernthaler et al., 2002). The filters were evaluated microscopically under an automated microscope (Zeder et al., 2011). Cell enumeration was performed with the software Automated Cell Measuring and Enumeration Tool (ACMETool3, 2018-11-09; Zeder et al., 2011). Cells were counted as objects according to manually defined parameters separately for the DAPI and FISH channels.

Description: Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams. Digital technology use in agriculture and agrifood systems research accelerates the production of multidisciplinary data, which spans genetics, environment, agroecology, biology, and socio-economics. Quality labeling of data secures its online findability, reusability, interoperability, and reliable interpretation, through controlled vocabularies organized into meaningful and computer-readable knowledge domains called ontologies. There is currently no full set of recommended ontologies for agricultural research, so data scientists, data managers, and database developers struggle to find validated terminology. The Ontologies Community of Practice of the CGIAR Platform for Big Data in Agriculture harnesses international expertise in knowledge representation and ontology development to produce missing ontologies, identifies best practices, and guides data labeling by teams managing multidisciplinary information platforms to release the FAIR data underpinning the evidence of research impact. The deployment of digital technology in Agriculture and Food Science accelerates the production of large quantities of multidisciplinary data. The Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture harnesses the international ontology expertise that can guide teams managing multidisciplinary agricultural information platforms to increase the data interoperability and reusability. The CoP develops and promotes ontologies to support quality data labeling across domains, e.g., Agronomy Ontology, Crop Ontology, Environment Ontology, Plant Ontology, and Socio-Economic Ontology.

Description: Findable, accessible, interoperable and reusable (FAIR) set principles that determine best practice for managing the dissemination and ensuring longevity of digital resources. The Helmholtz Metadata Collaboration (HMC) provides guidance on metadata and related topics to those working in the Helmholtz ecosystem. Given the complexity - both of the FAIR principles, and the Helmholtz ecosystem - we interpret the principles so they can be directly applicable to the Helmholtz context. In this interpretation we consider managers, tool-developers, data managers, and researchers amongst others; and provide guidance to these disparate roles on applying the FAIR principles in their professional lives.

Description: Versioning of data and metadata is a crucial - but often overlooked - topic in scientific work. Using the wrong version of a (meta)data set can lead to drastically difference outcomes in interpretation, and lead to substantial, propagating downstream errors. At the same time, past versions of (meta)data sets are valuable records of the research process which should be preserved for transparency and complete reproducibility. Further, the final version of (meta)data sets may actually include errors that previous versions did not. Thus, careful version control is the foundation for trust in and broad reusability of research and operational (meta)data. This document provides an introduction to the principles of versioning, technical recommendations on how to manage version histories, and discusses some pitfalls and possible solutions. In the first part of this document, we present examples of change processes that require proper management and introduce popular versioning schemes. Finally, the document presents recommended practices for researchers as well as for infrastructure developers.

Description: Die Anschlussfähigkeit bestehender Helmholtz-Dateninfrastrukturen an nationale und internationale Initiativen (z.B. NFDI, EOSC und andere), ist ein wichtiges zentren-übergreifendes Ziel der Helmholtz-Gemeinschaft. Dafür ist es entscheidend, die bestehenden Zusammenhänge der Forschungsdaten-erhebenden und -nachnutzenden sowie die Dateninfrastrukturen (DIS) entlang der FAIR-Prinzipien1 zu ordnen. Ziel dieser Erhebung ist es, einen Überblick über bestehende Praktiken und Entwicklungs-stände der Dateninfrastrukturen (DIS) in der Helmholtz Gemeinschaft im Bereich Erde und Umwelt zu erhalten, um eine konsistente Strategie zur Umsetzung eines FAIRen Datenraumes entwickeln zu können. Es stellt sich heraus, dass, den DIS die FAIR-Prinzipien bekannt sind, sie sich mehrheitlich dazu bekennen und bestrebt sind, diese bestmöglich umzusetzen. Dabei wählen sie zum Teil sehr unterschiedliche Umsetzungsstrategien und treffen auf unterschiedliche Herausforderungen und Hindernisse. Dabei wird deutlich, dass die Schwierigkeiten in der Umsetzung mit der Tiefe und organisatorischen Komplexität bei der Implementierung der FAIR-Prinzipien zunehmen. Während beispielsweise einige Kriterien zur Auffindbarkeit (Findability) und Zugriffsmöglichkeit (Accessability) bereits bei vielen DIS z.B. durch den Einsatz von DOIs und Metadatenstandards erfüllt sind, ist es offensichtlich schwieriger, die Interoperabilität (Interoperabilty) und Nachnutzbarkeit (Reusability) der Daten umzusetzen. Der HMC Hub Erde und Umwelt (EuU) kann aus der Erhebung für den Forschungsbereich EuU eine Reihe von Empfehlungen ableiten. Dazu gehört unter anderem die Notwendigkeit eines einheitlichen Verständnisses von FAIR. Innerhalb des Forschungsdatenmanagements (FDM) sollte der Fokus insbesondere auf eine einheitliche Umsetzung persistenter Identifier (PIDs) / Handles, FAIR Digital Objekts (FDOs), semantischer Konzepte und Provenienz gerichtet werden, weil deren Einsatz wichtige Bausteine für die Umsetzung der FAIR-Prinzipien sind. Infolgedessen könnte die Rolle von HMC sein, den einheitlichen Umgang mit Forschungsdaten innerhalb der Helmholtz-Gemeinschaft zu moderieren und zu koordinieren. Dadurch würden Prozesse zu etabliert die es erlauben, dass alle erhobenen Daten in den verschiedenen Forschungsbereichen gefunden, verwendet und einheitlich referenziert werden können. Langfristig gilt es einen Community Co-Design Prozess zu etablieren, der es erlaubt, möglichst konkrete, gemeinschaftlich getragene Vereinbarungen zum Datenaustausch zu treffen und diese in Helmholtz Empfehlungen zum Umgang mit Forschungsdaten, also Policies, umzusetzen. Dadurch würde ein für alle nachvollziehbarer, interoperabler Helmholtz Datenraum geschaffen.

Description: This perspective outlines how authors of ocean methods, guides, and standards can harmonize their work across the scientific community. We reflect on how documentation practices can be linked to modern information technologies to improve discoverability, interlinkages, and thus the evolution of distributed methods into common best practices within the ocean community. To show how our perspectives can be turned into action, we link them to guidance on using the IOC-UNESCO Ocean Best Practice System to support increased collaboration and reproducibility during and beyond the UN Decade of Ocean Sciences for Sustainable Development.

Description: In the marine realm, microorganisms are responsible for the bulk of primary production, thereby sustaining marine life across all trophic levels. Longhurst provinces have distinct microbial fingerprints; however, little is known about how microbial diversity and primary productivity change at finer spatial scales. Here, we sampled the Atlantic Ocean from south to north (~50°S–50°N), every ~0.5° latitude. We conducted measurements of primary productivity, chlorophyll-a and relative abundance of 16S and 18S rRNA genes, alongside analyses of the physicochemical and hydrographic environment. We analysed the diversity of autotrophs, mixotrophs and heterotrophs, and noted distinct patterns among these guilds across provinces with high and low chlorophyll-a conditions. Eukaryotic autotrophs and prokaryotic heterotrophs showed a shared inter-province diversity pattern, distinct from the diversity pattern shared by mixotrophs, cyanobacteria and eukaryotic heterotrophs. Additionally, we calculated samplewise productivity-specific length scales, the potential horizontal displacement of microbial communities by surface currents to an intrinsic biological rate (here, specific primary productivity). This scale provides key context for our trophically disaggregated diversity analysis that we could relate to underlying oceanographic features. We integrate this element to provide more nuanced insights into the mosaic-like nature of microbial provincialism, linking diversity patterns to oceanographic transport through primary production.