• August 22–24, 2017 | The Brown Palace Hotel & Spa | Denver, CO

Presentations from Wednesday, August 23


Click here for presentations from Thursday, August 24


Session 1 : The Future of Earth Observation



Dr. Walter Scott
DigitalGlobe

Unlocking the Full Potential of Earth Observation
Abstract

Unlocking the Full Potential of Earth Observation

Dr. Walter Scott | DigitalGlobe


Dr. Scott will speak about advances in cloud computing, automation and crowdsourcing that are enabling us to take full advantage of the ever-increasing amount of geospatial data that is becoming available, and making the benefits accessible to a much broader community.

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Lawrie Jordan
Esri

The Power of Simple and Quick
Abstract

The Power of Simple and Quick

Lawrie Jordan - Esri


This presentation will discuss rapidly emerging trends in Earth Observation and remote sensing in the context of a new generation of users and consumers. Specifically, it will address major changes in traditional workflows (i.e. dynamic versus static) as well as the evolving profiles of industry market segments and the personas of the professionals who represent them. This presentation will also investigate the implications of these evolutionary trends on the software tool developers, and the importance of continuous innovation that delivers value and simplicity to an increasingly digitally aware global society with near real-time expectations.

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Nicolas Stussi
Airbus

New Satellite and Airborne Imagery Assets from Airbus
Abstract

New Satellite and Airborne Imagery Assets from Airbus

Nicolas Stussi | Airbus


Airbus is a global leader in aeronautics, space, and related services. In this session, new insights will be discussed on plans to build, launch, and operate a new set of imagery assets (both satellite and airborne platforms) from 2019 and beyond. These unique assets will deliver state-of-the-art capabilities and push the boundaries in terms of monitoring and persistence services to address both commercial and government market segments. Airbus continues to leverage and expand its portfolio to develop cutting-edge technology and services to deliver customized imaging capabilities to its customers.

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Alex Shih
Planet

A Platform Fit for the Scale and Changing Nature of our Planet
Abstract

A Platform Fit for the Scale and Changing Nature of our Planet

Alex Shih | Planet


Planet designs, builds, and operates the world’s largest constellation of Earth-imaging satellites with the mission to image the entire planet, every day, and make global change visible, accessible, and actionable. This year alone, Planet has launched 136 satellites, bringing the total close to 200 satellites. Planet has created a global, automated satellite-to-software platform operation. The Planet Platform today enables a simpler, faster, more powerful approach to handling large volumes of data from Planet’s own satellites and a variety of other imagery providers. This presentation will dive into Planet’s expanding operational capacity and platform capabilities – enabling cloud-first, scalable, machine learning, and computer vision analytics on imagery. Planet’s goal is to enable a community to uncover new insights and actionable information from a unique view of the entire world every single day.

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Session 2 : Commercial Analytic Platforms



Dr. Ursula Benz
CloudEO

CloudEO GeoMarketplace is the One-stop for GeoServices and MicroGeoServices
Abstract

CloudEO GeoMarketplace is the One-stop for GeoServices and MicroGeoServices

Dr. Ursula Benz | CloudEO


It is our passion to not only make GeoServices successful in the market, but also MicroGeoServices, as we believe they both are key to everyone benefitting from the wealth of Earth Observation data – or any type of geodata. Everything starts with professionalism and ends in automation, with API-based access to imagery, analytics to retrieve the information from the images, and accounting, metering, and revenue share with all contributors. This includes profound development of analytics, demand-focused product design, reliable production, and service availability secured through the means of modern software and IT infrastructures. And nothing works without easy access to those services for customers – easy in terms of technical access as well as in terms of legal and pricing models. CloudEO has a 360° view. We help our partners through the entire process from development to successful online sales. We understand the need of individual solutions, of manual steps in the production flow, and the demand of customer and partner consultancy. But, we never stop looking at how we can make things faster and more affordable, both by automation, and by taking away whatever overhead we can through the opportunities of our unique GeoMarketplace.

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Mark Korver
Amazon Web Services

Working with Planetary-Scale Data in a Reproducible Way
Abstract

Working with Planetary-Scale Data in a Reproducible Way

Mark Korver | Amazon Web Services


It’s well known that data must be well-curated to be useful. Getting access to, then preparing data is a taxing part of data science, and is often a majority of the work. We also know that without access to both data and code that underlie scientific discoveries, findings are difficult if not impossible to reproduce. When this work is done on-prem, the same big-data work is done repetitively, and typically stays silo’d, the results remaining inaccessible to others. In contrast, the same work done in the cloud, can be securely provisioned to anybody in the world regardless of their infrastructure. Other than a thin-client, tablet, or notebook, local hardware is not required. In addition, data in the cloud sits right next to any amount of on-demand compute needed to extract value from it. That compute can be run by the data owner, or others that the owner chooses to share data with. This talk will introduce the Earth on AWS collection and take a peek at the simple, serverless methods that were used to process cloud-optimized GeoTIFFs for the USDA NAIP data, supporting in-situ use of CONUS NAIP by anyone.

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John Delay
Harris Geospatial Solutions

The Future Geospatial Data Supply Chain
Abstract

The Future Geospatial Data Supply Chain

John Delay | Harris Geospatial Solutions


As we consider the future of geospatial intelligence, traditional (non-commercial) sensing sources only provide a portion of the intelligence information that is currently available. This is increasing the reliance on commercial data and OSINT providers to fill the void. Getting insights from satellite, aerial, and OSINT data is harder than it should be due to a lack of interoperability. Critical challenges like monitoring threats, food availability, water resources, and sustainable urban and industrial systems depend on a commercial and OSINT data sources. The challenge is that these key data assets are not interoperable making them not easily discoverable or analytics-ready, leaving critical questions unanswered. This session will explore the role of supply chain management as an enabler to the future of automated production.

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Session 3 : The Business of Geospatial Analytics



Dr. Daniela Moody
Descartes Labs

Satellite Imagery Analysis for Automated Global Food Security Forecasting
Abstract

Satellite Imagery Analysis for Automated Global Food Security Forecasting

Dr. Daniela Moody | Descartes Labs


The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We will present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information that scale with the high rate and dimensionality of imagery being collected. We will focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready multi-sensor data platform enables quick prototyping of various satellite imagery analysis algorithms.

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Julie Baker
Ursa Space

Reliable Economic Intelligence for Financial and Energy Sectors
Abstract

Reliable Economic Intelligence for Financial and Energy Sectors

Julie Baker | Ursa Space


Over 80% of countries do not provide any official reporting of economic activity and multiple reports coming out of some countries, such as China, can sometimes imply conflicting results. This talk will cover how remote sensing and geospatial analytics can fill this gap for industry applications in the financial and energy sectors. Through access, aggregation, and analytics, Ursa is the first to deliver reliable weekly reports of 77% of China’s crude oil inventories. Ursa uses synthetic aperture radar (SAR) to deliver its timely reports and has access to all the world’s commercial SAR satellites. Aggregation of multiple satellites gives Ursa the ability to be SAR sensor-agnostic, creating a virtual constellation with a revisit rate of up to twice a day. Ursa’s image processing experts have developed geospatial analytics to work on multiple formats, multiple incidence angles, and multiple resolutions. Additional, proprietary research is incorporated to provide context, such as tank owner and storage type, for analytics results. Example use cases, such as macro-economic analysis, currency, and stock prediction, as well as other financial applications, will be presented. Data sources that provide reliable global economic intelligence are disrupting traditional energy and commodities paradigms.

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Dr. John Corbett
aWhere

Agriculture, Food Security, and the Impact of Increasing Weather Variability
Abstract

Agriculture, Food Security, and the Impact of Increasing Weather Variability

Dr. John Corbett | aWhere


Increased weather variability driven by a warming atmosphere impacts food production. Human security in some areas is already showing resource constraint pressure and this will only grow more intense. Monitoring agricultural production provides detailed localized information suitable to inform crises intervention efforts and optimize and target appropriate interventions.

Presentation PDF

Wade Larson
Urthecast

An Overview of UrtheCast’s Vision for the UrtheDaily and OptiSAR Satellite Constellations
Abstract

An Overview of UrtheCast’s Vision for the UrtheDaily and OptiSAR Satellite Constellations

Wade Larson | Urthecast


Description coming soon.

Presentation coming soon.


Session 4 : Analytic Innovations and Remote Sensing



Erin Wetherley
UC Santa Barbara

Imaging Spectrometry Applications for Characterizing Urban Surface and Climate Variability
Abstract

Imaging Spectrometry Applications for Characterizing Urban Surface and Climate Variability

Erin Wetherley | UC Santa Barbara


The growing concentration of the global human population into cities has coincided with increasingly rich data from smart environments, social sensing, and the Internet of things. Fusing these data with maps of the built environment and urban vegetation has enormous potential to quantify urban energy and water use, improve urban planning, and target public health initiatives. Currently, fine spatial resolution imagery is prized for mapping urban materials because it can identify object edges. Yet this imagery doesn’t have enough spectral bands to discriminate important differences between urban materials, and it doesn’t provide global coverage. Near-future orbital imaging spectrometer missions could revolutionize our understanding of urban environments, measuring hundreds of reflected wavelengths from the visible through the shortwave infrared. However, these platforms will have pixel sizes > 30 meters, which means we need to develop methods to extract urban surface information at sub-pixel scales. I will present new results in which we used airborne imaging spectrometry to extract fractional estimates of key urban surface classes and urban vegetation condition, obtaining robust estimates across spatial scales. When such data become globally available from satellite platforms, there will be increasing opportunities to produce spatially explicit value-added products for utilities, municipalities, and green technologies.

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Dr. Sarah Becker
US Army Corps of Engineers

Forest Indices for Detecting Trees in Multispectral Imagery
Abstract

Forest Indices for Detecting Trees in Multispectral Imagery

Dr. Sarah Becker | US Army Corps of Engineers


Use of automated remote sensing techniques to map forest cover is important when modeling environmental quality. However, identifying forest cover with multispectral imagery (MSI) often results in confusion caused by similar spectral profiles between forest and other vegetation. Previous research in forest mapping has included integration of hyperspectral imagery and LiDAR data for tree detection and use of MSI to distinguish tree crowns from non-vegetated features. Since these sources are not widely available to most practitioners, a method was created to discriminate between forest and other land covers using commercial MSI. This research discusses two indices, Forest Cover Index 1 and Forest Cover Index 2, which were developed to model forest in WorldView-2 satellite imagery of the Beltsville Agricultural Research Center in Maryland. The study site included mixed forest, agriculture, other vegetation, urban features, soil, and water. The tree cover indices exploited the product of either reflectance in red and red edge bands or the product of reflectance in red and near infrared bands. For two classes (trees vs. all other), overall classification accuracy was >85% for the four images that were acquired throughout the year.

Presentation PDF

Dr. Robert Sundberg
Spectral Science

Spectral Image Simulation Under Stressing Illumination Conditions
Abstract

Spectral Image Simulation Under Stressing Illumination Conditions

Dr. Robert Sundberg | Spectral Science


This presentation will discuss recent improvements made to the Monte Carlo Scene (MCScene) code to enable low light situations where the sun is near or below the horizon. MCScene is a high-fidelity model for full optical spectrum (UV through LWIR) hyperspectral image or multispectral image geospatial simulation. MCScene provides an accurate, robust, and efficient means to generate spectral scenes for algorithm validation. MCScene utilizes a Direct Simulation Monte Carlo (DSMC) approach for modeling 3D atmospheric radiative transfer including full treatment of molecular absorption and Rayleigh scattering, aerosol absorption and scattering, and multiple scattering and adjacency effects, as well as scattering from spatially inhomogeneous surfaces, including surface bidirectional reflectance distribution function (BRDF) effects. The model includes treatment of land and ocean surfaces, 3D terrain, 3D surface objects, and effects of finite clouds with surface shadowing. This session will provide a brief overview of how real-time elements are incorporated into the Monte Carlo engine, and will also discuss the recent additional of a polygonal earth cross-section (PEX) model which allows for long atmospheric path simulations such as those found under twilight conditions and highly off-nadir or near horizontal viewing geometries.

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Presentations from Thursday, August 24



Session 1 : Advances in GEOINT Tradecraft Geospatial Modeling



VADM Robert B. Murrett (Ret)
Syracuse University

Global Security Challenges and GEOINT
Abstract

Global Security Challenges and GEOINT

Vice Admiral Robert B. Murrett (Ret) | Syracuse University


This presentation deals with global security challenges in the present day, as well as projections for U.S. and allied nations’ responses to ongoing developments throughout the globe. It provides an overview of geographic and transnational trends, including implications for both government and industry. All of this is viewed with an emphasis on GEOINT matters, in response to evolving resource decisions, operations, and strategy.

Presentation PDF

Jesse Piburn
Oak Ridge National Laboratory

Decision Advantage: Predictive Analytics in Geospatial Intelligence and Why Data is Now the Most Valuable Resource in the World
Abstract

Decision Advantage: Predictive Analytics in Geospatial Intelligence and Why Data is Now the Most Valuable Resource in the World

Jesse Piburn | Oak Ridge National Laboratory


The most valuable resource in the world is no longer oil, it’s data. Like oil, data in its raw form is valuable not for what it is, but what we can turn it into. For geospatial intelligence, data and predictive analytics can facilitate an increase in situational awareness and allow analyst to have access to more information than ever before, but it is no panacea. Along with solutions it brings with it new issues we must contend with as a tradecraft. Predictive analytics is an extraordinarily powerful tool to help us find new answers. But, how do make sure we are asking the right questions?

Presentation PDF

Dr. Douglas Way
MDA

Advanced Terrain Analysis: Digital Elevation Model Transforms and Applications
Abstract

Advanced Terrain Analysis: Digital Elevation Model Transforms and Applications

Dr. Douglas Way | MDA


Digital Elevation Models (DEM), regardless of origin and resolution, provide information on terrain elevation, but applications require transforms to support analyses. Dr. Way has developed a suite of terrain concepts and models that can be applied to a wide range of applications from finding Karez features in the Middle East (utilizing 1 meter data), to quantifying the ability of the terrain to “hide” equipment or personnel. This presentation will summarize the geospatial concepts used to determine relative relief, terrain complexity (texture), terrain slope characterization, terrain slope characterization (uplands/lowlands), and terrain slope characterization (valleys), will be presented. A number of applications of these products will be shown including off-road vehicle mobility, generation of soil mapping, identifying potential sources of construction materials, ambush opportunity, and aerial concealment.

Presentation PDF

Dr. Lawrence Buja
NCAR

Next Generation Environmental Modeling and Data Analytics
Abstract

Next Generation Environmental Modeling and Data Analytics

Dr. Lawrence Buja | NCAR


We have become planetary managers of a globally interconnected world. In this big data era, as we evolve from a data-scarce to a data-rich world, remote sensing, modeling and data analytics at scale are transforming how environmental science is used to understand and simulate the world. These models and data don’t stand alone, but rather exist in an environment of human networks, decisions, and events that are critical for understanding the structure & dynamics of our complex coupled human/natural systems. The decades of experience that the science community has with large-scale observational and numerical data analytics sets the stage for a next generation of coupled socieo-enviro-technical models. From the emergence and spread of vector-borne diseases, to assessments of globally networked insurance, commodity and supply-chain risk, to climate forced social instabilities and migration, these next generation models will create the actionable data, information and knowledge products needed for economic, environmental and national security decision making.

Presentation PDF


Session 2 : Machine Learning at Scale



Dr. May Casterline
NVIDIA

AI for Remote Sensing Data
Abstract

AI for Remote Sensing Data

Dr. May Casterline | NVIDIA


The evolution of GPU technology has fueled breakthroughs in artificial intelligence. In particular, deep learning has powered innovations in language translation, image search, and driverless cars. Paired with the development of deep learning frameworks and software providers that integrate with NVIDIA’s CUDA platform, the technology has become more accessible to traditional researchers outside the computer science discipline. The result has been massive gains in automation while reducing the compute footprint and infrastructure. At the heart of deep learning approaches is a data-driven methodology to learning the patterns in large corpuses of information. While remote sensing data has always been ‘big data’, the amount of data that analysts and researchers will need to consume will only grow with the introduction of commercial satellite providers. The traditional exploitation algorithms of remote sensing data have relied on engineered, statistical approaches that require domain expertise to implement and deploy. These techniques have proven effective in the environments for which they were designed, however scale, access to domain expertise, and lack of model transferability remain challenges. The integration of deep learning techniques, and GPUs to power them, into GEOINT exploitation offers an exciting and tractable solution to automating some of the most challenging problems facing the community.

Presentation PDF

Michael Ehrlich
Harris Geospatial Solutions

MEGA – An Innovative Approach to Deep Learning for Remotely Sensed Data
Abstract

MEGA – An Innovative Approach to Deep Learning for Remotely Sensed Data

Michael Ehrlich | Harris Geospatial Solutions


Harris Geospatial has long been recognized as a leader in the remote sensing industry and on the forefront of innovation in imagery analytics. A new deep learning initiative at Harris called “MEGA”, continues that tradition. This presentation introduces MEGA and describes why it is a unique and innovative approach to applying deep learning to remotely sensed data. An overview of the problem space being addressed and focus areas for MEGA will be presented, along with a summary of the next set of challenges and opportunities. Finally, Harris’ strategy and vision for evolving deep learning as a critical solution for GEOINT analysis will be shared.

Presentation PDF

Pedro Rodriguez
Harris Geospatial Solutions

Automated Object Detection from GEOINT Data Using MEGA
Abstract

Automated Object Detection from GEOINT Data Using MEGA

Pedro Rodriguez | Harris Geospatial Solutions


This presentation will review the application of deep learning technology and techniques to automatically extract objects and features from geospatial intelligence data sources including high-resolution RGB and Pan imagery, high revisit rate imagery, LiDAR point clouds and products, mosaics from drone imagery, and full motion video.

Presentation PDF


Session 3 : Industry Solutions and Geospatial Analytics



Peter Benbow
UK Ministry of Defence

Automated Rule-based Image Analytics for the UK Ministry of Defence
Abstract

Automated Rule-based Image Analytics for the UK Ministry of Defence

Peter Benbow | UK Ministry of Defence


A key challenge for all defence operations is the provision of timely and accurate intelligence to support decision making and improve situational awareness. With the availability of Intelligence, Surveillance, Target, Acquisition and Reconnaissance (ISTAR) assets growing, there are increasing volumes of data being collected. Today, the extraction of imagery intelligence (IMINT) still relies largely on its manual inspection by experienced analysts. This has led to the problem of data deluge where the flow of imagery can often overwhelm the capacity of the analysts. In this talk we will describe the work done by the UK Defence Science and Technology Laboratory (DSTL) and Harris in developing an enterprise framework to extract content (geometries, objects and states) from multi-source image data. With Harris’ Geospatial Services Framework (GSF) at its core, the system will record these observations, allowing analysts to easily assess and visualise activities, changes over time, patterns and anomalies relating to targets of interest.

Presentation PDF

Carolyn Hall
Aerovironment

Condition-Based Maintenance for Utilities Infrastructure Using Drones
Abstract

Condition-Based Maintenance for Utilities Infrastructure Using Drones

Carolyn Hall | Aerovironment


Operating with the highest levels of efficiency, reliability, and safety is a top priority for utilities. The growth of distributed generation and diversification of power sources bring operational system challenges, and an aging infrastructure and workforce is driving the need for asset renewal prioritization and knowledge capture. Using the combination of condition-based maintenance and predictive maintenance, utilities can effectively overcome these challenges and remain relevant in the changing energy marketplace. Incorporating the use of drones in an intelligent, condition-based, asset management program will provide utilities with the information needed to operate more efficiently, effectively, and safely, consequently allowing them to overcome some of these disruptive obstacles. Utilizing data collected from drones will lead to reduced truck roll outs and ensure the right assets and skill sets are deployed. Additionally, predictive maintenance utilizing drones ensures assets remain in working order, reducing failures in the grid, especially where a potential asset failure could result in significant damage. The addition of drone data in the utilities industry has the potential to revolutionize the industry.

Presentation PDF

Dr. Brian Curtiss
ASD

Quantitative Spectroscopy from Space
Abstract

Quantitative Spectroscopy from Space

Dr. Brian Curtiss | ASD


We will demonstrate how to use field reflectance spectra, collected for materials such as vegetation, as input into calibration models that can be applied to map quantitative information in hyperspectral images. For example, quantitative results from using this technique for vegetation can provide information about leaf chemical properties like canopy nitrogen and lignin content. The resulting calibrations for vegetation properties produced using this method can then be mapped to hyperspectral images. Indices like NDVI are useful, but they lack the ability to give detailed information on physiological processes, so this technique takes image analysis a step further. This type of analysis can be very important in many different applications in areas like precision agriculture, forestry, environmental monitoring, mining and defense and intelligence.

Presentation PDF

Mark Romano
Harris Geospatial Solutions

Breakthroughs in 3D Data Products with Geiger-mode LiDAR
Abstract

Breakthroughs in 3D Data Products with Geiger-mode LiDAR

Mark Romano | Harris Geospatial Solutions


This session will look at how commercial Geiger-mode technology differs from existing LiDAR systems and what it means to the future of our industry. The presentation will include a technology overview with current and future applications as well as real project examples.

Presentation PDF


Session 4 : Adding the Temporal Dimension to Geospatial Analytics



Paolo Pasquali
sarmap

From On-demand to Always-on: SAR for Building Real-life Services
Abstract

From On-demand to Always-on: SAR for Building Real-life Services

Paolo Pasquali | sarmap


The possibility of providing, for any time and location in the world, operational services based on Earth Observation (EO) data very often faces very simple but fundamental issues data availability in an affordable, timely, and consistent manner. The Sentinel-1 constellation represents a solution. First, because SAR technology ensures all-time and all-weather acquisition capabilities, the Sentinal-1 has been designed to guarantee consistent coverage for any location in the world, with an average repeat between 6 and 12 days. Next, Sentinel-1 data are downloadable free of charge via a web interface and API. These data are hence ideal to build services that can be operated not only on-demand but on a routinely basis, for mapping as well as monitoring. Examples will be shown of different operational applications and services based on Sentinel-1 data, built on enterprise-level COTS software tools interfacing directly with the data archive. Finally, the complementarity of a Sentinel-1 based approach with data from other (very high-resolution) SAR as well as optical missions will also be discussed.

Presentation PDF

Ian Spence
SpaceMetric

Public Satellite Imagery for Effective Activity Planning
Abstract

Public Satellite Imagery for Effective Activity Planning

Ian Spence | SpaceMetric


Easy access to a regular supply of free satellite imagery is enabling a range of new services based on monitoring and change detection. We will describe how generic products from Sentinel-2 are being used to plan follow-up actions for more detailed data (satellite and UAV) and on-site inspection in local government and forestry organizations. We will also explain how satellite imagery is made analytics-ready through the creation of Precision Datacubes; stacks of accurately co-registered data that provide quality change information with minimal artifacts that allow limited resources to be used in an optimal way by significantly reducing false alarms.

Presentation PDF

Pieter Decker
Harris Corporation

Automated Integrated Predictive Data Models
Abstract

Automated Integrated Predictive Data Models

Pieter Decker | Harris Corporation


Data integration and reduction is the biggest technical challenge and opportunity of our age. Our approach to consumption and integration is almost entirely manual, forcing people to find, analyze, and correlate data. Unstructured data offers the biggest challenge and must be indexed automatically, at scale, when created, and at machine speeds. Probabilistic data modeling enables us to leverage low-specificity/low-sensitivity indicators to produce high-specificity/high-sensitivity insights by linking large volumes of data from multiple sources. There are five basic steps needed to achieve automated integrated predictive data models: Automatically index the content of all data; correlate data sources; develop models; develop conditional responses to collection, action, and analysis; and, evolve. The tools to do this exist today, are ready for use, and can help us begin to understand and use our data to its fullest potential. The culmination will be entirely new approaches to data.

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