Speakers
We lining up some of the most relevant industry leaders in Big Data for keynote sessions. The time limit to submit proposals is over so we will soon reveal the definitive list of speakers.
12:45 ~ 13:30
Sala 5
Javier de la Torre
CEO and co-founder CartoDB- Technical
Big data meets scalable visualizations
The power of visualizing time-series data derived from remote sensing products can not be overestimated. Visualization can give scientists, policy makers, journalists and others immediate insights into how the landscape and environment is changing over time and can lead to quicker understanding and action.
Effectively putting time-series data on maps remains very difficult. With the advent of web-based data portals, our ability to publish interactive maps to accompany data has greatly expanded. New problems with the scale and complexity of data mean data visualization remains a challenge. Here, we present our work to develop solutions to temporal data mapping for the Global Forest Watch 2.0 web portal (http://vizzuality.com/projects/gfwprototype). Deforestation data contain rich temporal information that is often lost when mapped in static formats. To ensure that these data are effectively communicated through the forthcoming Global Forest Watch portal, we developed several novel methods for data query, transfer, and finally map-based visualization. Deforestation is detected from each publication of MODIS imagery using a novel algorithm, FORMA.
The FORMA algorithm is implemented on a large-scale Hadoop based infrastructure. The FORMA algorithm is currently under peer review, here we will focus on the visualization mechanism for the data outputs. Locations of deforestation events are converted from raster products to JSON data objects. Each JSON data object efficiently stores an index of the date and pixel locations of deforestation on quadtree map-tiles. On the client, these three-dimensional JSON objects are unpacked and used to render HTML5 canvas objects that are displayed on the map. In combination with user-interface controls, users can interact with the history of deforestation on the map.
The methods developed for the Global Forest Watch website have been further generalized in an open-source library called, Torque (http://github.com/CartoDB/Torque). A generalized SQL statement to compress temporal-geospatial data to tile-based JSON objects and the HTML5 canvas rendering functions will be expanded in the future to visualize the motion of multiple agents and ordered, non-temporal, data. In this presentation we will describe in-depth the analysis of deforestation data, the efficiency of the temporal JSON data schema, and finally the challenges and rewards of visualizing temporal data on the web.
Takeaway Points:
- Users will learn about developing challenging data visualizations on maps.
Effectively putting time-series data on maps remains very difficult. With the advent of web-based data portals, our ability to publish interactive maps to accompany data has greatly expanded. New problems with the scale and complexity of data mean data visualization remains a challenge. Here, we present our work to develop solutions to temporal data mapping for the Global Forest Watch 2.0 web portal (http://vizzuality.com/projects/gfwprototype). Deforestation data contain rich temporal information that is often lost when mapped in static formats. To ensure that these data are effectively communicated through the forthcoming Global Forest Watch portal, we developed several novel methods for data query, transfer, and finally map-based visualization. Deforestation is detected from each publication of MODIS imagery using a novel algorithm, FORMA.
The FORMA algorithm is implemented on a large-scale Hadoop based infrastructure. The FORMA algorithm is currently under peer review, here we will focus on the visualization mechanism for the data outputs. Locations of deforestation events are converted from raster products to JSON data objects. Each JSON data object efficiently stores an index of the date and pixel locations of deforestation on quadtree map-tiles. On the client, these three-dimensional JSON objects are unpacked and used to render HTML5 canvas objects that are displayed on the map. In combination with user-interface controls, users can interact with the history of deforestation on the map.
The methods developed for the Global Forest Watch website have been further generalized in an open-source library called, Torque (http://github.com/CartoDB/Torque). A generalized SQL statement to compress temporal-geospatial data to tile-based JSON objects and the HTML5 canvas rendering functions will be expanded in the future to visualize the motion of multiple agents and ordered, non-temporal, data. In this presentation we will describe in-depth the analysis of deforestation data, the efficiency of the temporal JSON data schema, and finally the challenges and rewards of visualizing temporal data on the web.
Takeaway Points:
- Users will learn about developing challenging data visualizations on maps.