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.

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

EXPRESS: The Role of Patient Satisfaction in Hospitals’ Medicare Reimbursements

2020 ◽  
pp. 074391562098472
Author(s):  
Lu Liu ◽  
Dinesh K. Gauri ◽  
Rupinder P. Jindal
Keyword(s):  
Patient Satisfaction ◽  
Pain Management ◽  
Hospital Care ◽  
Pay For Performance ◽  
Data Sources ◽  
Satisfaction Survey ◽  
The Us ◽  
Performance System ◽  
Diverse Data

Medicare uses a pay-for-performance program to reimburse hospitals. One of the key input measures in the performance formula is patient satisfaction with their hospital care. Physicians and hospitals, however, have raised concerns especially about questions related to patient satisfaction with pain management during hospitalization. They report feeling pressured to prescribe opioids to alleviate pain and boost satisfaction survey scores for higher reimbursements. This over-prescription of opioids has been cited as a cause of current opioid crisis in the US. Due to these concerns, Medicare stopped using pain management questions as inputs in its payment formula. We collected multi-year data from six diverse data sources, employed propensity score matching to obtain comparable groups, and estimated difference-in-difference models to show that, in fact, pain management was the only measure to improve in response to pay-for-performance system. No other input measure showed significant improvement. Thus, removing pain management from the formula may weaken the effectiveness of HVBP program at improving patient satisfaction, which is one of the key goals of the program. We suggest two divergent paths for Medicare to make the program more effective.

scholarly journals Exascale applications: skin in the game

2020 ◽  
Vol 378 (2166) ◽  
pp. 20190056 ◽  
Author(s):  
Francis Alexander ◽  
Ann Almgren ◽  
John Bell ◽  
Amitava Bhattacharjee ◽  
Jacqueline Chen ◽  
...  
Keyword(s):  
High Performance ◽  
Data Science ◽  
Scientific Discovery ◽  
Numerical Algorithms ◽  
Department Of Energy ◽  
High Confidence ◽  
The Us ◽  
The Usa ◽  
Critical Problems ◽  
Performance Computing

As noted in Wikipedia, skin in the game refers to having ‘incurred risk by being involved in achieving a goal’, where ‘ skin is a synecdoche for the person involved, and game is the metaphor for actions on the field of play under discussion’. For exascale applications under development in the US Department of Energy Exascale Computing Project, nothing could be more apt, with the skin being exascale applications and the game being delivering comprehensive science-based computational applications that effectively exploit exascale high-performance computing technologies to provide breakthrough modelling and simulation and data science solutions. These solutions will yield high-confidence insights and answers to the most critical problems and challenges for the USA in scientific discovery, national security, energy assurance, economic competitiveness and advanced healthcare. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

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.

scholarly journals Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations

2021 ◽  
Vol 21 (6) ◽  
pp. 4637-4657
Author(s):  
Xiao Lu ◽  
Daniel J. Jacob ◽  
Yuzhong Zhang ◽  
Joannes D. Maasakkers ◽  
Melissa P. Sulprizio ◽  
...  
Keyword(s):  
Information Content ◽  
Oil And Gas ◽  
Joint Inversion ◽  
Gas Emissions ◽  
In Situ Data ◽  
Methane Budget ◽  
The Us ◽  
In Situ Observations ◽  
Methane Sink

Abstract. We use satellite (GOSAT) and in situ (GLOBALVIEWplus CH4 ObsPack) observations of atmospheric methane in a joint global inversion of methane sources, sinks, and trends for the 2010–2017 period. The inversion is done by analytical solution to the Bayesian optimization problem, yielding closed-form estimates of information content to assess the consistency and complementarity (or redundancy) of the satellite and in situ data sets. We find that GOSAT and in situ observations are to a large extent complementary, with GOSAT providing a stronger overall constraint on the global methane distributions, but in situ observations being more important for northern midlatitudes and for relaxing global error correlations between methane emissions and the main methane sink (oxidation by OH radicals). The in-situ-only and the GOSAT-only inversions alone achieve 113 and 212 respective independent pieces of information (DOFS) for quantifying mean 2010–2017 anthropogenic emissions on 1009 global model grid elements, and respective DOFS of 67 and 122 for 2010–2017 emission trends. The joint GOSAT+ in situ inversion achieves DOFS of 262 and 161 for mean emissions and trends, respectively. Thus, the in situ data increase the global information content from the GOSAT-only inversion by 20 %–30 %. The in-situ-only and GOSAT-only inversions show consistent corrections to regional methane emissions but are less consistent in optimizing the global methane budget. The joint inversion finds that oil and gas emissions in the US and Canada are underestimated relative to the values reported by these countries to the United Nations Framework Convention on Climate Change (UNFCCC) and used here as prior estimates, whereas coal emissions in China are overestimated. Wetland emissions in North America are much lower than in the mean WetCHARTs inventory used as a prior estimate. Oil and gas emissions in the US increase over the 2010–2017 period but decrease in Canada and Europe. The joint inversion yields a global methane emission of 551 Tg a−1 averaged over 2010–2017 and a methane lifetime of 11.2 years against oxidation by tropospheric OH (86 % of the methane sink).

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