Working with Data

Sumandro C, Sajjad A, Shashank S

Aug 3-5, Chennai.

Outline

Day 1, August 3

What is data? What is open data? What is spatial data?

What is ‘data format’? In what forms do data come?

1. Data, data formats, files, databases, indexes. Storage, retrieval.

What can be done with data?

1. NSSO
2. Community informatics, environmental governance <-- how can data support such initiatives
3. MapKibera and other examples of map-based advocacy/storytelling

Working with quantitative data

1. Statistical tools, visualisation tools
2. Scraping - Screen, web scraping. Ethics. Storage.

Working with spatial data

1. Spatial data: vector/raster
2. Field level collection and remote sensing imagery <- in the context of GIS

Discussion and installing softwares

Day 2, August 4

What is data visualisation?

Tools and methods of data collection

1. Survey of all kinds of data - social and ecological
2. GPS technology - History, satellites, coverage, devices, restrictions. Crowdsourcing - mobile, social media. Web/paper based forms, interviews. Online Petitions, campaigns.
3. Ushahidi, Google Public Alerts, Sahana, Humanitarian OpenStreetMap team.
4. Common Alerting Protocol

Tools for data visualisation

1. http://selection.datavisualization.ch/

Tools for geo-spatial visualisation

1. GRASS, QGIS, GeoCommons, Google stack
2. Web map paradigms, tiles, tile servers, map style sheets. TileMill, MapBox, Geocommons

Hands-on: QGIS, GeoCommons, Google Refine, Gnumeric, Inkscape

Day 3, August 5

Using a GPS device

1. History, satellites, coverage, devices, restrictions
2. Operational instructions.

Mapping Session.

OpenStreetMap - Collect, Edit, Consume.

1. OSM, Potlach, JOSM, Walking Papers, Visualization.

Google Map Maker, Google Earth, Google Maps.

1. Using GoogleMaps to create maps with custom markers, MapMapker and annotating Google Maps, Google Earth

GIS and geo-visualisation

Web-based data visualisation

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