GeoWave: How Space Filling Curves accelerate ingest and query of Geospatial data

GeoWave: How Space Filling Curves accelerate ingest and query of Geospatial data

by Eric Robertson (Booze Allen Hamilton)
GeoWave is an open source project that bridges the gap between geospatial software and distributed compute systems. This presentation will primarily focus on the theory that enables the core functionality of GeoWave.
GeoWave was developed at the National Geospatial-Intelligence Agency (NGA) in collaboration with Booz Allen Hamilton and RadiantBlue Technologies. GeoWave leverages a distributed key-value store to manage terabytes of raster and vector data, serving as an enterprise level geospatial data store. To efficiently index geospatial data and answer queries with geospatial constraints, GeoWave employs a space filling curve to form bidirectional mappings between multi-dimensional data and sorted keys. Space filling curves provide an efficient locality sensitive indexing scheme for proximal data. Beyond initial indexing, as a complete offering, Geowave leverages the space filling curve for optimizations to render interactive maps, to compute uniform sized map-reduce input splits, and partition locality sensitive data for near neighbors class of algorithms.
Working with large ranges of numeric data, multidimensional mapping onto a space filling curve carries with it several key challenges. Indexing on a numeric range of data, such as a bounding box or a period of time, can exhibit a large number of duplicates when applied to a highly granular space filling curve. Furthermore, queries over large ranges can result in the decomposition of many independent ranges over the space filling curve. We introduce several techniques to solve these problems.
GeoGig: A Git-Like Approach To Geospatial

GeoGig: A Git-Like Approach To Geospatial

by Joe Allnut (Ordnance Survey)
In the talk Joe will: 
Explain how to get up and running with GeoGig
Work through how to manage changing datasets
Demonstrate the QGIS GeoGig Plugin
Run through using GeoGig to work with example open data
Walk through a scenario with multiple distributed contributors
Talk through the findings of TechLab's work with GeoGig so far

Geo(Mesa/Wave/Trellis/Jinni): Processing Geospatial Data at Scale @locationtech

LocationTech is a working group inside of Eclipse Foundation that a set of 4 open source projects dealing with large geospatial datasets call home: GeoTrellis, GeoWave, GeoMesa, and GeoJinni (sense a pattern?).

These projects were created to solve the type of problems that we are seeing more and more of: how do we ask very large geospatial data questions concerning location? In this talk, I will give an introduction to those four projects, and talk about how each project approaches processing geospatial data at scale.

This talk covers the basics, such as:
- what does "processing geospatial data at scale" mean exactly?
- a introduction and history of Hadoop, Spark, and Accumulo
- What are GeoTrellis, GeoMesa, GeoWave, and GeoJinni? How are they different?

If your new to distributed processing, you should leave this talk with a better sense of the field, and if you're a veteran, you should leave with a better idea which of these project might fit your distributed geospatial processing needs.


GeoMesa as a Distributed Spatio-Temporal Database and Computational Framework

by Jim Hughes
GeoMesa builds on the Hadoop and Accumulo ecosystem to scale up indexing billions of spatio-temporal data. This presentation will showcase and discuss some of GeoMesa's existing distributed computational capabilities such as K-nearest neighbor queries, and then move on to highlight relevant work by the fall 2014 Facebook Open Academy (FOA) students. The FOA students have created a Web Processing Service (WPS) process to get back aggregate time series data for an Extended Common Query Language (ECQL) query. Examples and illustrations will use the open Global Database of Events, Language, and Tone (GDELT) dataset. The conclusion will include ideas for future work in distributed database computation touching on leveraging Spark and Tez. This presentation will be of interest to data scientists, geospatial systems developers, and users of massive Spatio-Temporal datasets.

Real-time Raster Processing with GeoTrellis

Rob Emanuele (Azavea) introduces the GeoTrellis project.

Map Tools for Mobile Devices

by Steve Gifford from Mousebird Consulting.
Mobile devices, such as Android and iOS tablets and phones are everywhere. We use them for maps, of course, but they can also be used for interactive geodata display.
mousebird consulting makes the open source WhirlyGlobe-Maply toolkit which is used in a variety of apps, from the serious to the simply fun. We also make WhirlyViz, an app used for Javascript based interactive data visualization.
This talk will discuss the toolkits at a high level and what it takes to do geospatial data visualization on these devices. We'll have a number of interesting examples drawn from our own work as well as that of our users.

Scotty I need data in 3 minutes or we're all dead!

Technology change has created an inflection point for geodata. Mobile devices, social media, retail transactions, and more generate a tremendous amount of data. The volume, variety, and velocity of data is ever increasing. What do we do about it?

Technology change has created an inflection point for geodata. Mobile devices, social media, retail transactions, and more generate a tremendous amount of data. The volume, variety, and velocity of data is increasing. New technologies are being developed to handle the huge amounts of data. The problem is more complex than simply having a big relational database. This talk will present an overview of open source geospatial technologies which enable big geodata on the server and little geodata on devices and other clients to make it useful with the right context at the right time. More than technology for technology's sake, use it to do something meaningful.

Developing applications with Mobile Map Tools

Mobile Map Tools is an open source framework and library for writing mobile mapping applications, founded by Glob3 Mobile. The Mobile Map Tools users have a common API to develop amazing map apps on their preferred platform. It offers high performance visualization implemented natively on each platform such as Android, iOS, and Web.

This presentation by Diego Gomez Deck, CTO of Glob3 Mobile, will provide an introduction and overview of the features Mobile Map Tools offers.

Redefining Geospatial data versioning: The GeoGit approach

Every organization working with geospatial data eventually faces the problem of managing its information and assets as they change over time. Versioning of geospatial data has been an issue for any workflow that involves more than one individual. Questions like who changed what and when become hard to answer, and while versioning approaches have existed for a while, they are cumbersome to use and utilize old paradigms. GeoGit takes concepts and lessons learned from the open source programming world and applies them to management of geospatial information, allowing better and decentralized management of versioned data and enabling new and innovative workflows for collaboration.