A scientific data processing framework for time series NetCDF data
The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, fle...
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          | Published in | Environmental modelling & software : with environment data news Vol. 60; pp. 241 - 249 | 
|---|---|
| Main Authors | , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Oxford
          Elsevier Ltd
    
        01.10.2014
     Elsevier  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1364-8152 | 
| DOI | 10.1016/j.envsoft.2014.06.005 | 
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| Abstract | The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, flexible framework that simplifies software development, and supports a data integration workflow. Algorithm and model input data, preprocessing, and output data specifications are defined through a graphical interface. ADI includes a library of software modules to support the workflow, and a source code generator that produces C, IDL®, and Python™ templates to jump start development. While developed for processing climate data, ADI can be applied to any time-series data. This paper discusses the ADI framework, and how ADI's capabilities can decrease the time and cost of implementing scientific algorithms allowing modelers and scientists to focus their efforts on their research rather than preparing and packaging data.
•ARM Data Integrator (ADI) is a framework to streamline the development of algorithms that analyze time-series data.•ADI can improve the consistency of output data products by checking for adherence to data standards as products are defined.•ADI automates the process of retrieving and preparing data for analysis.•Provides a modular, flexible software development architecture.•The input data, preprocessing, and output data specifications are defined through a graphical interface. | 
    
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| AbstractList | The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, flexible framework that simplifies software development, and supports a data integration workflow. Algorithm and model input data, preprocessing, and output data specifications are defined through a graphical interface. ADI includes a library of software modules to support the workflow, and a source code generator that produces C, IDL®, and Python™ templates to jump start development. While developed for processing climate data, ADI can be applied to any time-series data. This paper discusses the ADI framework, and how ADI's capabilities can decrease the time and cost of implementing scientific algorithms allowing modelers and scientists to focus their efforts on their research rather than preparing and packaging data. The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, flexible framework that simplifies software development, and supports a data integration workflow. Algorithm and model input data, preprocessing, and output data specifications are defined through a graphical interface. ADI includes a library of software modules to support the workflow, and a source code generator that produces C, IDL registered , and Python(TM) templates to jump start development. While developed for processing climate data, ADI can be applied to any time-series data. This paper discusses the ADI framework, and how ADI's capabilities can decrease the time and cost of implementing scientific algorithms allowing modelers and scientists to focus their efforts on their research rather than preparing and packaging data. The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, flexible framework that simplifies software development, and supports a data integration workflow. Algorithm and model input data, preprocessing, and output data specifications are defined through a graphical interface. ADI includes a library of software modules to support the workflow, and a source code generator that produces C, IDL®, and Python™ templates to jump start development. While developed for processing climate data, ADI can be applied to any time-series data. This paper discusses the ADI framework, and how ADI's capabilities can decrease the time and cost of implementing scientific algorithms allowing modelers and scientists to focus their efforts on their research rather than preparing and packaging data. •ARM Data Integrator (ADI) is a framework to streamline the development of algorithms that analyze time-series data.•ADI can improve the consistency of output data products by checking for adherence to data standards as products are defined.•ADI automates the process of retrieving and preparing data for analysis.•Provides a modular, flexible software development architecture.•The input data, preprocessing, and output data specifications are defined through a graphical interface.  | 
    
| Author | Gaustad, Krista Shippert, Tim Borsholm, Atle Fox, Kevin Ermold, Brian Daily, Jeff Beus, Sherman  | 
    
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| Keywords | Atmospheric science Data management Scientific data analysis NetCDF Time-series Observation data Scientific workflow Data analysis Sciences Time series Data processing  | 
    
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| SubjectTerms | Algorithms Animal, plant and microbial ecology Atmospheric science Automation Biological and medical sciences Computer programs computer software Data management environmental models Fundamental and applied biological sciences. Psychology General aspects. Techniques meteorological data Methods and techniques (sampling, tagging, trapping, modelling...) Modular NetCDF Nodular iron Observation data packaging Scientific data analysis Scientific workflow scientists Software Source code time series analysis Time-series Workflow  | 
    
| Title | A scientific data processing framework for time series NetCDF data | 
    
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