A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Citation and peer review of data: moving towards formal data publication

This paper discusses many of the issues associated with formally publishing data in academia, focusing primarily on the structures that need to be put in place for peer review and formal citation of datasets. Data publication is becoming increasingly important to the scientific community, as it will provide a mechanism for those who create data to receive academic credit for their work and will allow the conclusions arising from an analysis to be more readily verifiable, thus promoting transparency in the scientific process. Peer review of data will also provide a mechanism for ensuring the quality of datasets, and we provide suggestions on the types of activities one expects to see in the peer review of data. A simple taxonomy of data publication methodologies is presented and evaluated, and the paper concludes with a discussion of dataset granularity, transience and semantics, along with a recommended human-readable citation syntax

Spatially distributed water-balance and meteorological data from the Wolverton catchment, Sequoia National Park, California

Accurate water-balance measurements in the seasonal, snow-dominated Sierra Nevada are important for forest and downstream water management. However, few sites in the southern Sierra offer detailed records of the spatial and temporal patterns of snowpack and soil-water storage and the fluxes affecting them, i.e., precipitation as rain and snow, snowmelt, evapotranspiration, and runoff. To explore these stores and fluxes we instrumented the Wolverton basin (2180-2750 m) in Sequoia National Park with distributed, continuous sensors. This 2006-2016 record of snow depth, soil moisture and soil temperature, and meteorological data quantifies the hydrologic inputs and storage in a mostly undeveloped catchment. Clustered sensors record lateral differences with regards to aspect and canopy cover at approximately 2250 and 2625 m in elevation, where two meteorological stations are installed. Meteorological stations record air temperature, relative humidity, radiation, precipitation, wind speed and direction, and snow depth. Data are available at hourly intervals by water year (1 October-30 September) in non-proprietary formats from online data repositories (https://doi.org/10.6071/M3S94T)

Ocean data publication cookbook

This cookbook is an outcome of the 5th session of the SCOR/IODE/MBLWHOI Library Workshop on Data Publication and is posted here by permission of UNESCO.Executive summary: This “Cookbook” has been written for data managers and librarians who are interested in assigning a permanent identifier to a dataset for the purposes of publishing that dataset online and for the citation of that dataset within the scientific literature. A formal publishing process adds value to the dataset for the data originators as well as for future users of the data. Value may be added by providing an indication of the scientific quality and importance of the dataset (as measured through a process of peer review), and by ensuring that the dataset is complete, frozen and has enough supporting metadata and other information to allow it to be used by others. Publishing a dataset also implies a commitment to persistence of the data and allows data producers to obtain academic credit for their work in creating the datasets. One form of persistent identifier is the Digital Object Identifier (DOI). A DOI is a character string (a "digital identifier") used to provide a unique identity of an object such as an electronic document. Metadata about the object is stored in association with the DOI name and this metadata may include a location where the object can be found. The DOI for a document is permanent, whereas its location and other metadata may change. Referring to an online document by its DOI provides more stable linking than simply referring to it by its URL, because if its URL changes, the publisher need only update the metadata for the DOI to link to the new URL. A DOI may be obtained for a variety of objects, including documents, data files and images. The assignment of DOIs to peer-reviewed journal articles has become commonplace. This cookbook provides a step-by-step guide to the data publication process and showcases some best practices for data publication

Global dataset on seagrass meadow structure, biomass and production

Seagrass meadows provide valuable socio-ecological ecosystem services, including a key role in climate change mitigation and adaption. Understanding the natural history of seagrass meadows across environmental gradients is crucial to deciphering the role of seagrasses in the global ocean. In this data collation, spatial and temporal patterns in seagrass meadow structure, biomass and production data are presented as a function of biotic and abiotic habitat characteristics. The biological traits compiled include measures of meadow structure (e.g. percent cover and shoot density), biomass (e.g. above-ground biomass) and production (e.g. shoot production). Categorical factors include bioregion, geotype (coastal or estuarine), genera and year of sampling. This dataset contains data extracted from peer-reviewed publications published between 1975 and 2020 based on a Web of Science search and includes 11 data variables across 12 seagrass genera. The dataset excludes data from mesocosm and field experiments, contains 14271 data points extracted from 390 publications and is publicly available on the PANGAEA® data repository (10.1594/PANGAEA.929968; Strydom et al., 2021). The top five most studied genera are Zostera, Thalassia, Cymodocea, Halodule and Halophila (84 % of data), and the least studied genera are Phyllospadix, Amphibolis and Thalassodendron (2.3 % of data). The data hotspot bioregion is the Tropical Indo-Pacific (25 % of data) followed by the Tropical Atlantic (21 %), whereas data for the other four bioregions are evenly spread (ranging between 13 and 15 % of total data within each bioregion). From the data compiled, 57 % related to seagrass biomass and 33 % to seagrass structure, while the least number of data were related to seagrass production (11 % of data). This data collation can inform several research fields beyond seagrass ecology, such as the development of nature-based solutions for climate change mitigation, which include readership interested in blue carbon, engineering, fisheries, global change, conservation and policy

Strategien bei der Veröffentlichung von Forschungsdaten

Forschungsdaten liegen in Abhängigkeit der Disziplinen in vielfältigen Formen und Formaten vor. Sie sind in allen Disziplinen Teil des wissenschaftlichen Erkenntnisprozesses. Als digitales Informationsobjekt sind sie komplex und bislang wenig untersucht. Mit den Möglichkeiten neuer Informationstechnologien werden in den letzten Jahren neue Wege in der Publikation von Forschungsdaten beschritten. Mit Blick auf die Naturwissenschaften werden im Folgenden drei Publikationsmodelle beschrieben: Die Veröffentlichung von Forschungsdaten als eigenständiges Objekt in einem Forschungsdatenrepositorium, die Veröffentlichung von Forschungsdaten mit textueller Dokumentation und die Veröffentlichung von Forschungsdaten als Anreicherung einer interpretativen Text-Publikation.

Implementation of a workflow for publishing citeable environmental data: successes, challenges and opportunities from a data centre perspective

In recent years, the development and implementation of a robust way to cite data have encouraged many previously sceptical environmental researchers to publish the data they create, thus ensuring that more data than ever are now open and available for re-use within and between research communities. Here, we describe a workflow for publishing citeable data in the context of the environmental sciences—an area spanning many domains and generating a vast array of heterogeneous data products. The processes and tools we have developed have enabled rapid publication of quality data products including datasets, models and model outputs which can be accessed, re-used and subsequently cited. However, there are still many challenges that need to be addressed before researchers in the environmental sciences fully accept the notion that datasets are valued outputs and time should be spent in properly describing, storing and citing them. Here, we identify current challenges such as citation of dynamic datasets and issues of recording and presenting citation metrics. In conclusion, whilst data centres may have the infrastructure, tools, resources and processes available to publish citeable datasets, further work is required before large-scale uptake of the services offered is achieved. We believe that once current challenges are met, data resources will be viewed similarly to journal publications as valued outputs in a researcher’s portfolio, and therefore both the quality and quantity of data published will increase