scholarly journals ASCR Workshop on In Situ Data Management: Enabling Scientific Discovery from Diverse Data Sources

2019 ◽  
Author(s):  
Tom Peterka ◽  
Deborah Bard ◽  
Janine Bennett ◽  
E. Wes Bethel ◽  
Ron Oldfield ◽  
...  
Keyword(s):  
Data Management ◽  
Scientific Discovery ◽  
Data Sources ◽  
In Situ Data ◽  
Diverse Data

Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources

2020 ◽  
Vol 34 (4) ◽  
pp. 409-427
Author(s):  
Tom Peterka ◽  
Deborah Bard ◽  
Janine C Bennett ◽  
E Wes Bethel ◽  
Ron A Oldfield ◽  
...  
Keyword(s):  
Data Management ◽  
Scientific Discovery ◽  
Department Of Energy ◽  
Data Sources ◽  
Research Directions ◽  
In Situ Data ◽  
The Us ◽  
Diverse Data ◽  
Do So

In January 2019, the US Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions (PRDs) for in situ data management (ISDM). A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery. This article describes six PRDs identified by the workshop, which highlight the components and capabilities needed for ISDM to be successful for a wide variety of applications—making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

An Advanced Quality Control System for the CEOP/CAMP In-Situ Data Management

2008 ◽  
Vol 2 (3) ◽  
pp. 406-413 ◽  
Author(s):  
K. Tamagawa ◽  
M. Kitsuregawa ◽  
E. Ikoma ◽  
T. Ohta ◽  
S. Williams ◽  
...  
Keyword(s):  
Quality Control ◽  
Control System ◽  
Data Management ◽  
Quality Control System ◽  
In Situ Data

scholarly journals Brochure on In Situ Data Management

2019 ◽  
Author(s):  
Tom Peterka ◽  
Deborah Bard ◽  
Janine Bennett ◽  
E. Wes Bethel ◽  
Ron Oldfield ◽  
...  
Keyword(s):  
Data Management ◽  
In Situ Data

scholarly journals Accessing Diverse Data Comprehensively – CODM the COSYNA Data Portal

2016 ◽  
Author(s):  
Gisbert Breitbach ◽  
Hajo Krasemann ◽  
Daniel Behr ◽  
Steffen Beringer ◽  
Uwe Lange ◽  
...  
Keyword(s):  
Web Services ◽  
Data Management ◽  
Data Sources ◽  
Observation System ◽  
Coastal System ◽  
Data Usage ◽  
Comprehensive View ◽  
Observation Methods ◽  
Data Portal ◽  
Diverse Data

Abstract. The coastal observation system COSYNA aims to describe the physical and biogeochemical state of a regional coastal system. The COSYNA data management is the link between observations, model results and data usage. The challenge for the COSYNA data management CODM is the integration of diverse data sources in terms of parameters, dimensionality and observation methods to gain a comprehensive view of the observations. This is achieved by describing the data using metadata in a generic way and by making all gathered data available for different analyses and visualisations in an interrelated way, independent of data dimensionality. Different parameter names for the same observed property are mapped to the corresponding CF standard name leading to standardised and comparable metadata. These metadata together with standardised web services are the base for the data portal.

Deepwater Current Profile Data Sources for Riser Engineering Offshore Brazil

2012 ◽  
Author(s):  
Gus Jeans ◽  
Marc Prevosto ◽  
Liam Harrington-Missin ◽  
Christophe Maisondieu ◽  
Christelle Herry ◽  
...  
Keyword(s):  
Numerical Model ◽  
Primary Source ◽  
Current Data ◽  
Data Sources ◽  
Model Data ◽  
Current Profile ◽  
Profile Data ◽  
Site Specific ◽  
In Situ Data

A variety of current profile data sources are compared for a deepwater site offshore Brazil. These data were gathered for consideration as part of the Worldwide Approximations of Current Profiles (WACUP) Joint Industry Project, described separately in OMAE2012-83348. The primary source of data for current profile characterisation is site specific full water column measurement. Sufficiently high vertical and temporal resolutions are required to capture the dominant oceanographic processes. Such in-situ data are generally expensive and time consuming to collect, so there is an increasing tendency for numerical model current data to be considered for engineering applications. In addition to being relatively inexpensive and quick to obtain, model data are also typically of much longer duration. This potentially allows inter-annual variability and rare extreme events to be captured. However, the accuracy and reliability of numerical model data remains questionable, or unproven, in many deepwater development regions. This paper explores the suitability of such models to represent a deepwater site offshore Brazil, in relation to the key oceanographic processes revealed within the in-situ data.

Current Profile Data Sources for Engineering Design West of Shetlands

2014 ◽  
Author(s):  
Gus Jeans ◽  
Joe Fox ◽  
Claire Channelliere
Keyword(s):  
Numerical Model ◽  
Engineering Design ◽  
Current Data ◽  
Data Sources ◽  
Model Data ◽  
Current Profile ◽  
Profile Data ◽  
Field Development ◽  
In Situ Data

Current profile data sources considered for derivation of engineering design criteria West of Shetland are described. The region is impacted by a variety of oceanographic processes that combine to produce a complex current regime. Reliable quantification of the resulting current profiles is required for safe and cost effective offshore exploration and field development. A key challenge to all offshore developments is acquisition of appropriate data. Site specific measurement remains the primary current profile data source for engineering applications, with full water column coverage at sufficient resolution required for riser design. Such in-situ data are generally expensive and time consuming to collect, so there is an increasing tendency for numerical model current data to be considered. Model data are often relatively quick and inexpensive to obtain, with the added benefit of a much longer duration, potentially allowing inter-annual variability and extreme events to be captured. However, the accuracy and reliability of numerical model data remains questionable, or unproven, in many deepwater development regions. This paper describes a recent study in which in-situ data remained the primary source for derivation of current profile criteria for engineering design. Short duration proprietary data were supplemented by additional public domain data from nearby sites in a regional synthesis, with critical results. The performance and benefits of readily available model data are also considered.

scholarly journals ASCR Workshop on In Situ Data Management.

2019 ◽  
Author(s):  
Tom Peterka ◽  
Deborah Bard ◽  
Janine Camille Bennett ◽  
E. Wes Bethel ◽  
Ron A. Oldfield ◽  
...  
Keyword(s):  
Data Management ◽  
In Situ Data
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