Triggered by a search query, the webLyzard platform analyzes the set of matching documents to determine all referenced locations across multiple sources. The geographic map is a visual tool to explore such spatial datasets, for example to investigate the regional distribution of news articles or social media postings.
The notion of a Geospatial Web , or GeoWeb, has inspired our work for the better part of the last two decades. The June 2020 release Sagebrush Lizard takes webLyzard’s geospatial analytics capabilities to a new level. We rebuilt the geographic map module from scratch for optimized performance and a more effective information design. Custom base layers, adaptive tooltips and time-sliced animations increase the versatility of the component for various types of tasks. Export options and the ability to embed the component enable its reuse in external GeoWeb applications.
Try out the dashboard at unep.ecoresearch.net
Layout and Data Representation
Dynamic updates triggered by a user interaction help understand the geographic context of a query without interrupting the user’s workflow. Layout and color scheme of the geographic maps depend on the chosen base layer. Circles represent single documents or document clusters:
- The position of circles mark the coordinates – i.e., longitude and latitude of cities, countries, landmarks, etc. that were discovered in the documents.
- The size of the circles is proportional to the number of documents referring to a specific position.
- The color indicates one of the selected topics or metadata attributes such as sentiment or associated emotions. In the case of sentiment, for example, the color ranges from red (negative) to grey (neutral) and green (positive).
- Optional Arcs connect referenced geographic entities with the origin of the documents (i.e., the locations of authors or publishers). This feature allows analysts to explore frequently mentioned locations in a particular country’s media channels.
Interactive Geographic Map Features
The full potential of geographic maps and virtual globes in GeoWeb applications unfolds in conjunction with effective drill-down capabilities. webLyzard’s adaptive tooltip displays the most relevant information in a local context. It also allows restricting or extending the search.
- Hovering over a circle activates a document preview and a tooltip including a line chart and top associations with this particular location. All arcs pointing to this location are displayed with higher opacity. This highlights in which countries the location is being discussed.
- Clicking on a circle or country displays an extended tooltip with context-specific actions: (i) Focus on this Point to show results within a 100 km radius, automatically extended to 1000 km in case of sparse coverage, (ii) Replace the current search with a search for mentions of this location, and (iii) Restrict or Extend the search via Boolean operators (AND, OR).
- Zooming is available via the mouse wheel or double click. Clicking and dragging enable a seamless panning of the complete display. Such pan and zoom operations trigger new queries to dynamically update the map. This results in richer and more detailed visualizations without cluttering or slowing down the display at lower zoom levels.
Dynamic Geographic Map Rendering
Advancing the State of the Art in Geospatial Analytics
Developed as part of the ASAP and EVOLVE big data research projects, the geographic map module supports very large datasets. It has been tested successfully with search queries returning more than 100 million documents. The screenshot above shows a street-level display with an adaptive tooltip for on-the-fly query refinements. The blue markers present anonymized cell tower activity data for the City of Rome. The system then overlays this information with geotagged Twitter postings (green = positive; red = negative). With such an overlay, analysts can easily discover communication hotspots during an event. This shows how semantic technologies in conjunction with advanced visual tools transform statistical data into valuable repositories of actionable knowledge  for geospatial analytics applications.
- Scharl, A. and Tochtermann, K., Eds. (2007). The Geospatial Web – How Geo-Browsers, Social Software and the Web 2.0 are Shaping the Network Society. London: Springer.
- Bostock, M., Ogievetsky, V. and Heer, J. (2011). “D3: Data-Driven Documents”, IEEE Transactions on Visualization and Computer Graphics, 17(12): 2301-2309.
- Brasoveanu, A.M.P., Sabou, M., Scharl, A., Hubmann-Haidvogel, A. and Fischl, D. (2017). “Visualizing Statistical Linked Knowledge for Decision Support”, Semantic Web Journal, 8(1): 113-137.