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Data Science and Analytics (DEC)

Data science, analytics and decision in the context of spatial-temporal data. Human cognition augmentation. Data Science for Geo: The use of data mining and other functions provided by intelligent systems to facilitate the creation of knowledge.

Title Description

Text and Graph Analytics

Text Analytics refers to the process of deriving high-quality information from text. Applications of this are Natural Language Processing (NLP) and Social Media harvesting. An example is to scan a set of documents written in a natural language and either model the document set for predictive classification purposes or populate a database or search index with the information extracted - (DSTL).

Spatial-Temporal Analytics

Although real-time spatiotemporal data are now being generated by almost ubiquitously and their applications in research and commerce are widespread and rapidly accelerating, the ability to continuously create and interact in real time with this data is a recent phenomenon. This real-time space–time interactive functionality remains today the underlying process generating the current explosion of fused spatiotemporal data, new geographic research initiatives, and myriad mobile geospatial applications in governments, businesses, and society - (NGAC).

Fusion, Conflation analytics

Conflation refers to the act of combining two distinct maps into one new map. It is similar to the practice of image mosaicking. It is usually carried out by registration of an overlapping area. Conflation for digital maps refers to the process of associating real world coordinates to digital ones and it is named Map Matching - (DSTL).

Machine Learning/CNNs on Imagery

Machine learning is the subfield of computer science that gives computers the ability to learn without being explicitly programmed. Deep learning and Convolutional Neural Networks (CNNs) - a sub type of machine learning - consists of multiple hidden layers in an artificial neural network - (Wikipedia).

Modeling, Simulation and prediction

Simulation modeling is the process of creating and analyzing a digital prototype of a physical model to predict its performance in the real world. Models and simulation can be used for analysis and for training.

Trends merged into above or retired

Title Description Roadmap for Data Science Analytics

Uncertainty, Veracity

Uncertainty is a situation which involves imperfect and/or unknown information, including aspects of cognition (the process of acquiring knowledge and understanding through thought, experience and senses) and plays a part in understanding Uncertainty Information. How this information is assessed for data quality is important - (DSTL).

C2/SCADA for GeoIoT

Command and control (C2) a well established ability is the exercise of authority over assigned resources in the accomplishment of a common goal. Supervisory control and data acquisition (SCADA) is a information system architecture for high-level process supervisory management of industrial process plants. Applying C2 and SCADA to IoT environments will reuse existing control system technology in a new communications stack of broader reach.

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