Evolving patterns of spatial data infrastructures for modeling of data ecosystems
Keywords:
spatial data infrastructure, architecture, data ecosystems, digital transformations.Abstract
Introduction: Spatial data infrastructures are not designed to coexist collaboratively with new data models from heterogeneous sources.
Objective: To analyze the evolution of the interrelationships of these infrastructures with digital technologies, and how this leads to modeling data ecosystems.
Methods: Three frameworks are followed. The first is the open distributed processing reference model, used to describe the complexities of spatial data infrastructures. The second is related to evolutionary patterns that contemplate models and architectures representative of the interrelationships between such infrastructures with emerging digital technologies. The latter pattern underpins the proposed data ecosystem architecture.
Results: The first pattern resulted in a collaborative spatial data infrastructure architecture in the cloud and was a milestone for its scalability. With the second, it was obtained a semantic service model with greater efficiency in information retrieval. Context sensitivity and data management in Internet of Things environments for geospatial data is the result of the third pattern, while the fourth adds value to the previous ones and offers architectures to manage complex data. The experimentation of the governance of these infrastructures is carried out from an agent-based simulation.
Conclusions: The evolutionary patterns experienced and some references of data architectures made it possible to model an ecosystem architecture as the basis for new flexible, agile and self-sustaining digital ecosystems.
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