Turning Data Into Information with Geo Ontologies Justin

Turning Data Into Information with Geo. Ontologies Justin Lewis - @jmapping - Terra. Frame

A bit about us

Some Basic Requirements Remote data collection (no internet) � Data syncing across systems � Data manipulation & analysis � Dynamic data mapping & charting � Report generation � Complex domain models � Mapping data with NO geometries � Expansive configuration �. . . �

Not Easy

Some Common Challenges 1. Disparate data sources 1. Limited organizational resources (no GIS staff) 1. A lack of quality GIS data 1. Need for robust data + vis manipulation tools

DATA

Turn messy & incomplete data into useful data

How do we meet these needs?

FOSS + 4 G Community And many others

A Different Approach A method for modeling data as ontologies that can help turn messy and/or incomplete data into useful data.

Ontology Crash Course

Ontologies | User Data

What are ontologies? A style of programming that allows you to define human-like inferences about data objects.

To Elaborate Ontology Geo-Ontology <justin> is a <person> <justin> has a <brain> <colorado> is a <state> <colorado> located in <usa>

An Ontology Model for Geo Universal A collection of geographic locations representing a common political hierarchy. Ex: Countries Geo. Entity A single geographic entity within a Universal collection. Ex: South Korea

Geo. Entity

Universal

Purpose of Universals / Geo. Entities Provide a central geographic context for the system

Strengths Of This Approach 1. Well defined spatial and non-spatial relationships 1. No dependency on geometries (less GIS)

Ontologies in the OPEN Runway. SDK An ontology based data engine. Geo. Dashboard A visualization layer that sits on top of Runway. SDK.

What about user data?

User Data Is Different User data can maintain relationships to Geo. Entities and Universals giving user data spatial context.

JSON { "sales": [ {"product": "widget 1", "amount": "2", "loc": "denver"}, {"product": "widget 2", "amount": "5", "loc": "seattle"} ] }

Geo. JSON { "type": “feature”, “geometry”: { “type”: ”point”, “coordinates”: [124. 6, 10. 1] }, “properties”: { "location": "denver" } }

Common GIS Formats

Spreadsheet

The Reality of User ALL Data Incomplete Messy Non-Existent (geometry)

Why is this valuable? Generic data integration, manipulation and visualization

What do I mean by “generic”?

My data, Your data, Everyone’s data

No Geom? No Problem

How does this work in a web application?

What about geometries?

Geometries Are Used To Visualize Geo. Entities Visualize lowest level data points Algorithmically enhance data Validate spatial relationships However, geometries are optional

Runway. SDK in The Wild Deployed to 7 countries and growing

Demo

Thank You! @jmapping

Git. Hub Links github. com/terraframe/Runway-SDK github. com/terraframe/geodashboard