Hello everyone I'm Chenglong 2 0:00:05.600,0:00:10.160 3 synthesis-powered visualization tool, 4 The grammar of graphics lies in the hearts of modern visualization tools.
Here visualizations are defined as mappings 6 0:00:21.760,0:00:27.840 7 two columns --> Date and Temperature, we can create 8 a line chart to show the temperature trends by mapping the Date column to x position of the lines
and the Temperature column to y position 10 0:00:38.960,0:00:44.000 11 graphics makes visualization easy, 12 However --> in practice, this is not always the case, 13 Here --> given a dataset with temperatures of two cities.
If we want to create a visualization to show 15 0:00:57.040,0:01:02.800 16 using a simple mapping like our last example, 17 The key problem here is that there exists a mismatch between the design
and the input data layout, and 19 0:01:13.760,0:01:19.520 20 transform the data and to specify the design --> 21 which can be challenging for non-experienced users.
To solve this problem, we designed 23 0:01:27.360,0:01:29.040 24 0:01:29.840,0:01:34.560 25 programming --> users can demonstrate a partial 26 visualization using example mappings from input data values to geometry.
In this example, the user created 28 0:01:43.840,0:01:46.960 29 the two cities on the first day --> 30 and an example line to demonstrate San Francisco temperature trends during the first two days.
With this example, our tool, Falx, can synthesize 32 0:02:00.560,0:02:04.560 33 is a synthesis algorithm that 34 can synthesize programs to generalize the example, 35 Now --> let me show you how it works in action, 36 After loading the data into Falx we can first create an example line that shows
San Francisco temperatures on the first two dates.
Then we can create an example bar to demonstrate
temperature difference between 40 0:02:36.720,0:02:40.480 41 to generalize our example, 42 The synthesizer finds different ways to generalize the example.
In this case, the first visualization is correct 44 0:02:55.840,0:03:01.440 45 without data transformation or programming, 46 Falx solves the synthesis problem in three steps, 47 Starting from the input data and the example --> Falx first decompiles each visualization layer
into a visualization program 49 0:03:16.400,0:03:20.880 50 synthesized data transformation programs 51 whose evaluation results are consistent with the example. This synthesis process
is achieved by searching for all programs 53 0:03:31.040,0:03:36.160 54 visualization script and render them 55 on the user interface for user exploration, 56 And this completes the synthesis process, 57 To evaluate Falx --> we conducted a between group user study with four visualization scenarios.
We recruited two groups of participants 59 0:03:52.880,0:03:55.680 60 0:03:55.680,0:03:59.840 61 change the visualization process, 62 Our quantitative results show that Falx users in general
perform better and have 64 0:04:08.320,0:04:12.240 65 Falx changed the visualization 66 process into a recognition task that includes demonstration and confirmation.
In this new process, participants discover 68 0:04:23.760,0:04:27.200 69 representative data points 70 in their examples to better convey visualization ideas,
and they can gain trust of synthesis results 72 0:04:36.480,0:04:42.160 73 use Falx in exploratory data analysis, 74 So --> this is Falx -- a synthesis-powered visualization tool. You can learn more
about our design and our study in our paper 76