ADaM: a data mining toolkit for scientists and engineers

Rushing, John; Ramachandran, Rahul; Nair, U. S.; Graves, Sara; Welch, Ronald W.; Lin, Hong

doi:10.1016/j.cageo.2004.11.009

Cited by 57 publications

(28 citation statements)

References 4 publications

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“…Other applications of formal semantics in technical architectures, similar to those we have implemented for virtual observatories include work on workflow systems (Gil et al 2006, Ludaescher et al 2005, in grid computational settings (DeRoure et al 2005) and in frameworks for Earth and space science data mining (Rushing et al 2005). Basic knowledge representation and reasoning can support both computer-to-computer and computer-to-researcher interfaces that find, access and use data in a more effective, robust and reliable way.…”

Section: Semantic Web Methodologymentioning

confidence: 99%

Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience

Fox

McGuinness

Cinquini

et al. 2009

Computers & Geosciences

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We have developed a semantic data framework that supports interdisciplinary virtual observatory projects across the fields of solar physics, space physics and solar-terrestrial physics.This work required a formal, machine understandable representation for concepts, relations and attributes of physical quantities in the domains of interest as well as their underlying data representations. To fulfill this need we developed a set of solar-terrestrial ontologies as formal encodings of the knowledge in the Ontology Web Language -Description Logic (OWL-DL) format.We present our knowledge representation and reasoning needs motivated by the context of Virtual Observatories, from fields spanning upper atmospheric terrestrial physics to solar physics, whose intent is to provide access to observational datasets. The resulting data framework is built upon semantic web methodologies and technologies and provides virtual access to distributed and heterogeneous sets of data as if all resources appear to be organized, stored and retrieved from a local environment. . Our conclusion is that the combination of use case-driven small and modular ontology development, coupled with free and open-source software tools and languages provides sufficient expressiveness and capabilities for an initial production implementation and sets the stage for a more complete semantic-enablement of future frameworks.

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Section: Semantic Web Methodologymentioning

confidence: 99%

Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience

Fox

McGuinness

Cinquini

et al. 2009

Computers & Geosciences

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“…-WRF model (Michalakes et al 2000;Skamarock et al 2007), a next-generation atmospheric prediction and simulation model that runs on single or multiple processors at grid spacings ranging from metres to hundreds of kilometres. -Algorithm development and mining (ADaM; Rushing et al 2005), a powerful suite of tools for mining observational data, assimilated datasets and model output. -Integrated data viewer (IDV; Murray et al 2003), a widely used desktop application for visualizing, in an integrated manner, a broad array of multidimensional geophysical data in one, two and three dimensions.…”

Section: The Lead Service-oriented Architecturementioning

confidence: 99%

“…Metadata, output and other information are stored automatically in the MYLEAD catalogue (figure 5; Plale et al 2004Plale et al , 2007, which is a personal workspace for each user that accommodates sharing across a variety of domains. Users may visualize forecast output using the Unidata IDV (Murray et al 2003) and apply a variety of post-processing tools including the ADaM data mining environment (Rushing et al 2005). …”

mentioning

confidence: 99%

Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation

Droegemeier

2008

Phil. Trans. R. Soc. A.

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Mesoscale weather, such as convective systems, intense local rainfall resulting in flash floods and lake effect snows, frequently is characterized by unpredictable rapid onset and evolution, heterogeneity and spatial and temporal intermittency. Ironically, most of the technologies used to observe the atmosphere, predict its evolution and compute, transmit or store information about it, operate in a static pre-scheduled framework that is fundamentally inconsistent with, and does not accommodate, the dynamic behaviour of mesoscale weather. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This paper describes a new cyberinfrastructure framework, in which remote and in situ atmospheric sensors, data acquisition and storage systems, assimilation and prediction codes, data mining and visualization engines, and the information technology frameworks within which they operate, can change configuration automatically, in response to evolving weather. Such dynamic adaptation is designed to allow system components to achieve greater overall effectiveness, relative to their static counterparts, for any given situation.The associated service-oriented architecture, known as Linked Environments for Atmospheric Discovery (LEAD), makes advanced meteorological and cyber tools as easy to use as ordering a book on the web. LEAD has been applied in a variety of settings, including experimental forecasting by the US National Weather Service, and allows users to focus much more attention on the problem at hand and less on the nuances of data formats, communication protocols and job execution environments.

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“…• Counter-Strike game: a 3-D tactical shooting game pitting terrorist versus counter-terrorist; • SimBionic AI authoring tool: a visual behavior authoring and execution engine developed at Stottler Henke (Fu and Houlette, 2002); and • ADaM data mining tool suite: machine learning software developed at the University of Alabama in Huntsville (Rushing et al, 2005).…”

Section: Testbed Descriptionmentioning

confidence: 99%

An Agent Populated Testbed for C2 Experimentation

Davis¹,

Fu²,

Rushing³

2007

Self Cite

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. i ABSTRACT Recent concepts in the field of command and control (C2), such as Power to the Edge and Network-Centric Warfare, have indicated the need for a testbed for experimentation. We describe a gaming testbed, populated by realistic synthetic agents, for modeling the complex human interactions comprising C2 structures, and for exploring the effectiveness of C2 concepts in a variety of tactical circumstances. SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)AFRLA testbed for experimentation with C2 concepts must be capable of reproducing the complex, rapid, dynamic, and unpredictable unfolding of events in battle. Scenarios can be carefully limited, and realism diluted to a practical level, but enough of the complex interactions of individual and collective behavior must be preserved to capture the essentially human nature of C2. Experimentation involves the correlation of tactical events and outcomes with a host of variable parameters, such as C2 structure, communication patterns and reliability, and implementation of commander's intent.This report describes the details of our testbed and experiment design and implementation, in addition to findings and lessons learned. Our approach included the integration and extension of three existing platforms: Counter-Strike, a multiplayer firstperson tactical shooter; SimBionic, a visual behavior authoring and execution engine developed at Stottler Henke; and ADaM, a data mining tool suite developed at the University of Alabama, Huntsville. The testbed produced by this integration allows for the planning and execution of missions by human or synthetic agents, including specifications of different C2 structures, and the mining of experimental data for the effectiveness of the C2 concepts. We discuss the applicability of our findings to other echelons, as well as its contribution to the evaluation of new C2 concepts.ii

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ADaM: a data mining toolkit for scientists and engineers

Cited by 57 publications

References 4 publications

Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience

Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience

Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation

An Agent Populated Testbed for C2 Experimentation

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