What is GMaVis?
Data generation has increased exponentially in recent years due to the popularization of technology. At the same time, information visualization enables the extraction of knowledge and useful information through data representation with graphic elements. Moreover, a set of visualization techniques may help in information perception, enabling finding patterns and anomalies in data. Even tought it provides many benefits, the information visualization creation is a hard task for users with a low knowledge in computer programming. It becomes more difficult when these users have to deal with big data files since most tools do not provide features to abstract data preprocessing. In order to bridge this gap, we proposed GMaVis. It is a Domain-Specific Language (DSL) that offers a high-level description language for creating geospatial data visualizations through a parallel data preprocessor and a high-level description language.
Its compiler abstracts complexities from the whole visualization creation process, even in the data pre-processing phase. Also, it allows domain users with low-level knowledge in computer programming to create these visualizations through a high-level description language. These users can easily do it with a few lines of code, using simple declarations and blocks to express visualization details. Currently, GMaVis supports the creation of three types of geospatial visualization: markedmap, clusteredmap and heatmap.
Furthermore, GMaVis provides declarations to create filters and classes. These declarations can be used to select data, remove registers, apply data classification, highlight specific values, and create legends with symbols and classification description. Also, it includes delimiter specification that enables the use of raw datasets as input. In this case, GMaVis parses the input data using the specified delimiters. Moreover, this DSL provides automatic data processing, requiring users to only inform the data structure and field’s location for latitude and longitude.
A compiler was developed in order to enable the use of GMaVis. This compiler processes the DSL code together with input dataset to generate the geospatial data visu-
alization automatically. Also, it allows users to use big and raw datasets. Big datasets are supported because this compiler can process huge data files even in low memory computers through a smart memory allocation and data processing. Also, raw data 3 can be used since GMaVis description language supports data structure specification. A parallel data preprocessor module is responsible for parsing, filtering, classifying, and generating an output with only useful information to generate the visualization. As a result, domain users do not need to handle data manually or use data processing tool. This compiler also generates this data preprocessor module automatically, using the information in the input code.