The ‘Where’ question is central to our everyday lives. Geospatial data shapes our ability to answer that question and build intelligent applications, whether on the web or on your mobile device.
Supported by contributions from crowd-sourced data projects and open source software, geo data and its technology spectrum has grown impressively in recent years. In the face of this massive and diverse range of spatial data and technologies, the ability to choose effective methods for storage, retrieval and visualisation becomes critical .
The Cartonama conference is about geographic data, the technology behind it, the applications built around it and the overarching aspect of community and mobility.
We will organize workshops along with the conference. The goal would be to provide hands-on training to collect, store and visualize geographic data, and finally, to build location-based services with these tools. Workshop theme falls into:
- Nature of Geospatial Data: Structure, Formats and Operations
- Collection, Storage & Delivery of Geospatial Data: Crowd-sourced Models, Standards and Databases
- Location-based Services: Front-end and Back-end tools to build and manage your applications
- Leveraging Open Geographic Data Repositories: Using OpenStreetMap to visualize and tell stories through maps
You can submit your workshop proposals via the submissions through the funnel below.
You can submit a proposal to speak at Cartonama via the submission funnel below. Please describe your proposal in as much detail as possible. Detail is important if you'd like to be voted up into the schedule.
Your submission will be up for public voting for up to 2 weeks before the event. For the final tally, we will only consider votes from ticket holders, as a way to ensure participants get exactly what they pay for.
Making a funnel submission does not guarantee final selection. Selected speakers will get a free ticket to the event (limited to one speaker per proposal). Proposers whose talks are not on the final schedule will be able to purchase tickets at the prevailing rate for the day on which they made their proposal.
You can buy a ticket to the event here.
Challenges and Best Practices when working with location based data.
Challenges and Best Practises when working with location based data.
What are the possible ways of storing,retrieving and representing geo-spatial data? What drives the choice of a given representaion of this data? How can small tweaks enhance performance?
The discussion aims to enlighten pros and cons of the various methods of representation when trying to resolve a problem involving geo-spatial data. How would we store and index the data for a location like Bangalore and get relevant information for an area like Koramanagala to serve intelligent information.
We would also like to cover several ways to save infrastructural costs(example of Amazon EMR will be taken).
Our experience is mainly around writing pipelines for processing huge ammounts of spacial data from their raw form to creating relevant reports. We would like to talk about the several performance bottlenecks we faced in representing and maintaining data as well as performance and how we overcame these.
Surface Knowledge of Big Data.
Varun is the Techincal Architect for Big Data at Minjar, Kuliza Technologies. He is working on solving the several problems involved with representation of geo-spatial data and mining this data.
Loves to work on new and exciting challenges. Having worked in diverse technologies involving Rules Management, Virtualization, Mobile etc. in different organizations, he is now working at Minjar, Kuliza Technolgies.