Abstract |
Currently, spatially distributed data concerns cases where information is location-dependent,
concerning various data categories ranging from physical objects, events, and equipment, to
processes, people and even access regulations. In this context, a mixture of visualization-driven
querying and browsing is crucial to ensure optimal information access. The need for such
spatial visualizations varies depending on some key parameters: (i) the involved detailed
structure of the information items; (ii) the chosen overviews for presentation, such as image
thumbnails, video icons, titles and tooltips; (iii) the adopted map functionality, enabling deploy
outdoor and indoor data distributions; (iv) the use of either SQL or No-SQL data management
backbones; and (v) the ability to encompass, at the front-end level, custom data form and table
implementations.
In this context, we present a generic software framework for the needs of spatially
distributed data visualizations over indoor and outdoor maps, primarily targeted to
programmers, offering the necessary parameterization and configuration functionality while
allowing easy embedding within full-stack web applications.
Some of the features include general string tags, which can be interpreted by pluggable
location tag handlers, e.g. as longitude and latitude coordinates, raster coordinates, building
areas, and in general any form of custom location scripting. Such tags are combined with
presentation-specific metadata, including icons, images, videos, and audio, while supporting
additional metadata as JSON data items displayed in overlays. Besides the standard
functionality offered by our visualizer, these tags combined with extensible JSON metadata
constitute a scripting mechanism, enabling host applications interpret them as needed, for
instance, as ontology annotations and configuration preferences, giving enough freedom to
programmers handle them in an application-dependent manner. Furthermore, our tool
empowers programmers with the ability to insert buttons anywhere on maps and allow
programmers to handle them as needed in the context of the host application.
Overall, we emphasized a level of functional flexibility that enables programmers to fine-tune
and adapt the visualizer to meet the demands of a wide range of situations.
Regarding indoor maps, programmers can establish a structured tree hierarchy for the
interior organization of a building, and support placement of information items in every area.
Floorplans can be associated to areas, while data items can be inserted either directly on them,
or alternatively stay associated at the logical level of a building structure. In the context of
outdoor maps, we use a web-service interface to link to existing geographical map
implementations, such as Google Maps, enriched with data placement and visualization
features. Additionally, we allow an outdoor item to link to an indoor one, thus leading to the
respective indoor information provision module, such as when selecting a building on the map
and navigating across individual floors or areas. The latter emphasizes the synergy between the
indoor and outdoor maps, enabling developers to organize and detail information items across
these two spatial layers.
In summary, we emphasized the provision of a parameterized and configurable visualization
tool for spatial information, enabling developers to plug, when needed, new custom-made
components for information entry, editing, search, and display. The tool has been implemented
for adoption in a full-stack web application context and is implemented entirely in JavaScript
and React JS.
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