Streamlining Oceanic Biogeochemical Dataset Assembly in Support of Global Data Products

2020 ◽  
Author(s):  
Eugene Burger ◽  
Benjamin Pfeil ◽  
Kevin O'Brien ◽  
Linus Kamb ◽  
Steve Jones ◽  
...  
Keyword(s):  
Quality Control ◽  
Data Integration ◽  
Scientific Data ◽  
Climate Data ◽  
Science Data ◽  
Metadata Record ◽  
Data Products ◽  
Analysis And Synthesis ◽  
Data Integration System ◽  
Global Data

<p>Data assembly in support of global data products, such as GLODAP, and submission of data to national data centers to support long-term preservation, demands significant effort. This is in addition to the effort required to perform quality control on the data prior to submission. Delays in data assembly can negatively affect the timely production of scientific indicators that are dependent upon these datasets, including products such as GLODAP. What if data submission, metadata assembly and quality control can all be rolled into a single application? To support more streamlined data management processes in the NOAA Ocean Acidification Program (OAP) we are developing such an application.This application has the potential for application towards a broader community.</p><p>This application addresses the need that data contributing to analysis and synthesis products are high quality, well documented, and accessible from the applications scientists prefer to use. The Scientific Data Integration System (SDIS) application developed by the PMEL Science Data Integration Group, allows scientists to submit their data in a number of formats. Submitted data are checked for common errors. Metadata are extracted from the data that can then be complemented with a complete metadata record using the integrated metadata entry tool that collects rich metadata that meets the Carbon science community requirements. Still being developed, quality control for standard biogeochemical parameters will be integrated into the application. The quality control routines will be implemented in close collaboration with colleagues from the Bjerknes Climate Data Centre (BCDC) within the Bjerknes Centre for Climate Research (BCCR).  This presentation will highlight the capabilities that are now available as well as the implementation of the archive automation workflow, and it’s potential use in support of GLODAP data assembly efforts.</p>

Mars and Venus Exploration: A mapping, visualisation, and data analysis application for SPICAM/V high-level science data products

2020 ◽  
Author(s):  
Nick Cox ◽  
Jeronimo Bernard-Salas ◽  
Stephane Ferron ◽  
Jean-Luc Vergely ◽  
Laurent Blanot ◽  
...  
Keyword(s):  
Data Analysis ◽  
European Space Agency ◽  
Space Mission ◽  
Planetary Science ◽  
Scientific Data ◽  
Physical Parameters ◽  
Science Data ◽  
Starting Point ◽  
Data Products ◽  
High Level

<p>In the era of big data and cloud storage and computing, new ways for scientists to approach their research are emerging, which impact directly how science progresses and discoveries are made. This development has led the European Space Agency (ESA) to establish a reference framework for space mission operation and exploitation by scientific communities: the ESA Datalabs (EDL). The guiding principle of the EDL concept is to move the user to the data and tools, and to enable users to publish applications (e.g. processors, codes, pipelines, analysis and visualisation tools) within a trusted environment, close to the scientific data, and permitting the whole scientific community to discover new science products in an open and FAIR approach.</p> <p>In this context we will present a proto-type science application (aka Sci-App) for the exploration and visualization of Mars and Venus using the SPICAM/V Level-2 data available from the ESA Planetary Science Archive (PSA). This demonstrator facilitates the extraction and compilation of scientific data from the PSA and ease their integration with other tools through VO interoperability thus increasing their scientific impact. The tool’s key modular functionalities are 1) interactive data query and retrieval (i.e. search archive metadata), 2) interactive visualisation (i.e. geospatial info of query results, data content display of spectra, atmospheric vertical profiles), 3) data manipulation (i.e. create local maps or data cubes), and 4) data analysis (in combination with other connected VO tools). The application allows users to select, visualise and analyse both Level 2A products, which consist of e.g. transmission and radiance spectra, and level 2B products, which consist of retrieved physical parameters, such as atmospheric aerosol properties and vertical density profiles for (trace) gases in the Martian or Venusian atmosphere.</p> <p>Our goal is to deploy the (containerised) Sci-App to the EDL and similar initiatives for uptake by the space science community. In the future, we expect to incorporate access to other Mars/Venus atmospheric data sets, particularly the measurements obtained with the NOMAD and ACS instruments on the ExoMars Trace Gas Orbiter. The community can also use this application as a starting point for their own tool development for other data products/missions.</p>

scholarly journals Radiometric Performance of the CERES Earth Radiation Budget Climate Record Sensors on the EOS Aqua and Terra Spacecraft through April 2007

2011 ◽  
Vol 28 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Kory J. Priestley ◽  
G. Louis Smith ◽  
Susan Thomas ◽  
Denise Cooper ◽  
Robert B. Lee ◽  
...  
Keyword(s):  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Calibration Data ◽  
Climate Data ◽  
Science Data ◽  
Data Products ◽  
Earth Radiation Budget ◽  
Accuracy And Stability ◽  
Earth Radiation

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) flight models 1 through 4 instruments were launched aboard NASA’s Earth Observing System (EOS) Terra and Aqua spacecraft into 705-km sun-synchronous orbits with 10:30 p.m. and 1:30 a.m. local time equatorial crossing times. With these instruments CERES provides state-of-the-art observations and products related to the earth’s radiation budget at the top of the atmosphere (TOA). The archived CERES science data products consist of geolocated and calibrated instantaneous filtered and unfiltered radiances through temporally and spatially averaged TOA, surface, and atmospheric fluxes. CERES-filtered radiance measurements cover three spectral bands: shortwave (0.3–5 μm), total (0.3>100 μm), and an atmospheric window channel (8–12 μm). CERES climate data products realize a factor of 2–4 improvement in calibration accuracy and stability over the previotus Earth Radiation Budget Experiment (ERBE) products. To achieve this improvement there are three editions of data products. Edition 1 generates data products using gain coefficients derived from ground calibrations. After a minimum of four months, the calibration data are examined to remove drifts in the calibration. The data are then reprocessed to produce the edition 2 data products. These products are available for science investigations for which an accuracy of 2% is sufficient. Also, a validation protocol is applied to these products to find problems and develop solutions, after which edition 3 data products will be computed, for which the objectives are calibration stability of better than 0.2% and calibration traceability from ground to flight of 0.25%. This paper reports the status of the radiometric accuracy and stability of the CERES edition 2 instrument data products through April 2007.

scholarly journals Graph-based sequence annotation using a data integration approach

2008 ◽  
Vol 5 (2) ◽  
Author(s):  
Robert Pesch ◽  
Artem Lysenko ◽  
Matthew Hindle ◽  
Keywan Hassani-Pak ◽  
Ralf Thiele ◽  
...  
Keyword(s):  
Data Integration ◽  
Gene Function ◽  
High Throughput Sequencing ◽  
Prediction Method ◽  
Function Prediction ◽  
Function Annotation ◽  
Automated Annotation ◽  
Data Integration System ◽  
Reference Databases ◽  
Function Assignment

SummaryThe automated annotation of data from high throughput sequencing and genomics experiments is a significant challenge for bioinformatics. Most current approaches rely on sequential pipelines of gene finding and gene function prediction methods that annotate a gene with information from different reference data sources. Each function prediction method contributes evidence supporting a functional assignment. Such approaches generally ignore the links between the information in the reference datasets. These links, however, are valuable for assessing the plausibility of a function assignment and can be used to evaluate the confidence in a prediction. We are working towards a novel annotation system that uses the network of information supporting the function assignment to enrich the annotation process for use by expert curators and predicting the function of previously unannotated genes. In this paper we describe our success in the first stages of this development. We present the data integration steps that are needed to create the core database of integrated reference databases (UniProt, PFAM, PDB, GO and the pathway database Ara- Cyc) which has been established in the ONDEX data integration system. We also present a comparison between different methods for integration of GO terms as part of the function assignment pipeline and discuss the consequences of this analysis for improving the accuracy of gene function annotation.The methods and algorithms presented in this publication are an integral part of the ONDEX system which is freely available from http://ondex.sf.net/.

scholarly journals The Orbiting Carbon Observatory-2: first 18 months of science data products

2017 ◽  
Vol 10 (2) ◽  
pp. 549-563 ◽  
Author(s):  
Annmarie Eldering ◽  
Chris W. O'Dell ◽  
Paul O. Wennberg ◽  
David Crisp ◽  
Michael R. Gunson ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Carbon Dioxide ◽  
Eastern China ◽  
Regional Scale ◽  
Central Africa ◽  
Retrieval Algorithm ◽  
Science Data ◽  
The North ◽  
Data Products ◽  
Atmospheric Carbon

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO2) with the accuracy, resolution, and coverage needed to quantify CO2 fluxes (sources and sinks) on regional scales. OCO-2 was successfully launched on 2 July 2014 and has gathered more than 2 years of observations. The v7/v7r operational data products from September 2014 to January 2016 are discussed here. On monthly timescales, 7 to 12 % of these measurements are sufficiently cloud and aerosol free to yield estimates of the column-averaged atmospheric CO2 dry air mole fraction, XCO2, that pass all quality tests. During the first year of operations, the observing strategy, instrument calibration, and retrieval algorithm were optimized to improve both the data yield and the accuracy of the products. With these changes, global maps of XCO2 derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes XCO2 enhancements co-located with intense fossil fuel emissions in eastern US and eastern China, which are most obvious between October and December, when the north–south XCO2 gradient is small. Enhanced XCO2 coincident with biomass burning in the Amazon, central Africa, and Indonesia is also evident in this season. In May and June, when the north–south XCO2 gradient is largest, these sources are less apparent in global maps. During this part of the year, OCO-2 maps show a more than 10 ppm reduction in XCO2 across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO2. As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart XCO2 changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset.

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