Author: Melissa Dennison, November 18, 2015
Course Assignment, SA8905, Fall 2015 (Rinner)
I chose the history of Native Title claims in Australia as the topic for this map. “Native Title” is a general term for the legal framework and process for indigenous land claims in Australia. Following the landmark 1992 Mabo v. Queensland (No. 2) case, which was the first legal recognition of the interest of indigenous Australians in their traditional lands and waters, the Australian Parliament passed the Native Title Act in 1993. Claims under the Act began in 1994. This video provides an excellent quick introduction to the topic:
My goal was to create an animated map in CartoDB showing Native Title activity across Australia, both active claims and determined outcomes, from Mabo to the present.
My data source was the National Native Title Tribunal (NNTT) open data portal. I faced the following constraints in achieving my goal:
- CartoDB’s animation (Torque) function is available on points only, on one layer only
- The NNTT spatial data is for polygons, and comes in 4 datasets
- My CartoDB account only provided 100MB storage
- Native Title is an extremely complex topic while an animated map is simplistic
Step 1: Downloading and reviewing the data
On September 22, 2015, I downloaded the current Native Title claims and outcomes data, and the geospatial data model, from:
The data came in four shapefiles, two for current claims and two for determined outcomes.
|Current claims files||Determined outcomes files|
|Schedule of Native Title Determination Applications
Registered Native Title Determination Applications
|Determinations of Native Title
Determinations of Native Title ‐ Native Title Outcomes
The Schedule of Native Title Determination Applications lists claims that have been filed but have not yet passed the registration test (the test involves meeting certain legal requirements in order for the claim to proceed). The Registered Native Title Determination Applications file lists those claims that have passed the test. Working with the files I found some overlap between them, in that they referred to many of the same tribunal cases and land areas. (I expect this has to do with a time lag between when various files are updated on the Tribunal’s main database, and then extracted and uploaded to its open data portal. By downloading them all on the same day I inevitably got some outdated information.) I chose to work only with the Schedule for this project, as it contained the most Tribunal cases.
The determined outcomes files also overlapped, but contained different information. The Determinations of Native Title file indicates areas of land where Native Title was found to exist, to have been extinguished and/or a combination of each. The Determinations of Native Title ‐ Native Title Outcomes file shows areas where Native Title exists, exclusively or non-exclusively, or where Native Title does not exist or has been extinguished. Because there is no unique identifier in the dataset for each land area, only for claims and determinations (which can refer to multiple parcels of land), it was not possible to combine the files in such a way as to capture all the determination information for individual parcels of land. I chose to use both files in order to retain this information and just live with the overlap.
Note that Native Title claims that are withdrawn, discontinued, rejected, struck out or pre‐combined are transferred to a historical dataset that is not publicly available, and are therefore not shown on this map.
Step 2: Merging files in QGIS
The three shapefiles were too large, over 130MB, for my CartoDB account, so I loaded them into QGIS and used the MMQGIS plugin to merge the files. I named the new shapefile NTmerge1.
What to click in QGIS to merge files: MMQGIS>Combine>Merge Layers
Step 3: Preparing the shapefile for uploading to CartoDB
NTmerge1.shp was 116.8MB, still too big for my 100MB limit on CartoDB, so I had to reduce its size. Fortunately converting the polygons to points, which I had to do anyway because Torque only works on point data, was the solution. I named the new file NTpoints1. Its size was 428KB, well below my CartoDB limit.
What to click in QGIS to convert polygons to points: Vector>Geometry Tools>Polygon Centroids
Step 4: Uploading the data to CartoDB and preparing it for Torque animation
Uploading the data on CartoDB went smoothly, literally just clicking “New Dataset” and then selecting the file. Preparing the data for animation was a bit more involved. I should note that I actually used the Torque Cat (Category) function, which is a refinement of Torque in that it enables depiction of categories within a variable. However, it is only possible to run Torque Cat on one time column and one category column. As a merged file, NTpoints1.shp contained multiple date columns (such as “date lodged” for active claims and “determination date” for determined outcomes) and null values for active claims in the “determination outcome” column. Using simple SQL statements (seen in the table below) in CartoDB’s SQL workspace, I created a single date column and a single outcome category column.
|To create and fill new date column||To create and fill new category column|
|ALTER TABLE ntpoints1
ADD COLUMN dateall date;
WHERE datelodged IS NOT NULL;
WHERE detdate IS NOT NULL;
|ALTER TABLE ntpoints1
ADD COLUMN current CHAR(255);
SET current=’active claim’
WHERE datelodged IS NOT NULL;
WHERE detoutcome IS NOT NULL;
Step 5: Activating Torque Cat and finishing the map
In the CartoDB “Map layer wizard”, I selected Torque Cat, my newly-created columns as the time and category columns, and colours for each category. I set the duration of the animation to 60 seconds, and left the defaults for everything else.
In the CartoCSS editor (seen in the image below), I changed the default specification “linear” to “cumulative” so that the dots would remain on the map for a cumulative effect.
Finally, I added a title and some text for further information.
The end result can be seen at: