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.

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Acting on time-critical events by processing ever growing social media, news or cyber data streams is a major technical challenge. Many of these data sources can be modeled as multi-relational graphs. Mining and searching for subgraph patterns in a continuous setting requires an efficient approach to incremental graph search. The goal of our work is to enable real-time search capabilities for graph databases. This demonstration will present a dynamic graph query system that leverages the structural and semantic characteristics of the underlying multi-relational graph.

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