Moving Features SWG
Ishimaru, Nobuhiro (Ishimaru, Nobuhiro ) - Co-Chair,
Kim, Kyoung-Sook (National Institute of Advanced Industrial Science & Technology (AIST)) - Co-Chair,
SAKR, Mahmoud (Université Libre de Bruxelles (ULB)) - Co-Chair
With the development of communication and positioning technology such as Global Navigation Satellite System (GNSS), Wi-Fi, and Beacon, collecting movement data for moving features, typically on vehicles and pedestrians, has become easy. A moving feature is a feature whose location continuously changes over time. A moving feature is widely used in several application domains, such as LBS (Location Based Service), marketing, and public health. These applications have considered not only the current location of features but also the historical data of a feature’s movement. These data are used to analyze the patterns of moving features and provide input to predictive models. Moreover, innovative applications for smart cities require the overlay and integration of moving feature data from different sources to create enhanced social and business values. For example, sharing moving feature data widely and seamlessly helps organizations to handle marketing at the micro-level, trace people contacts in penedemics, make an efficient evacuation plans in the case of a sudden disaster, control autonomous vehicles and personal mobility, and more based on people’s activities and movement conditions.
The goals for the Moving Features SWG are to develop and maintain enhancements to the moving features standard based on the following issues:
Data models and encoding formats to exchange the moving features data including GNSS-logged, network-constrained, semantic, and region-based moving features.
Service interfaces based on the emerging OGC APIs and SQL, such as a moving feature service, process service, and so on.
Data quality and validation of moving feature data.
Support other OGC working groups (SWG and DWG) to use moving feature data in there domains of interest.
Market demand is rapidly increasing recently for better integration of moving feature data with GIS and other geospatial technologies. Example applications using moving feature data include:
traffic congestion information services using probe cars or taxis equipped with GPS to measure the travel time of each road link;
tracking systems on auto-trucks for logistics management, and
agent-based road traffic simulation systems for forecasting traffic situations.
The pressing demand on mobility services is driving innovative data-powered solutions such as car-sharing, ride-sharing, mobility as a service MaaS, ECO-routing, and multi-modal to name some. As mentioned as the OGC White Paper “Geospatial Data Science” [OGC 20-001r2], providing the interoperability for heterogeneous applications requiring mobility data of moving features is increasingly important and impactful. This is because the spatiotemporal data analysis will broaden the market for big geospatial data. Systems relying on single-source moving feature data are now evolving into more integrated systems. The integration of moving feature data from different sources is key to developing more innovative and advanced applications. This SWG aims to provide OGC standards for handling and sharing moving features data.
The aim of the Moving Features SWG is to develop new candidate standards for accelerating the eco-system of moving feature data to share and reuse moving feature data by humans and machines. Existing standards for the feature representation do not address the dynamic aspects of location and property. A new candidate standard in preparation of that document as an RFC submission will cover one of the following scopes;
Conceptual models: ISO19141:2008 Schema for Moving Features should be referred to as the conceptual data model for the development of candidate standards. The Moving Features SWG will revisit the ISO19141:2008 schema to analyze the schema, whether it can cover new requirements of applications and use cases such as autonomous vehicles, augmented reality, indoor applications, and propagation of disease. A standard data model should describe the movement of zero to three-dimensional geometric features, including changes in attitude or rotation along with the movement.
Encodings: The encoding specifications for exchanging moving feature data should be prioritized, which more directly contributes to the system development and the data integration among heterogeneous data sources. The initial proposal is to define the standard and to illustrate it with an XML encoding, but other encodings may be used as well, such as a CSV, JSON, ProtoBuf, or other Binary encoding. The general framework to represent movements of point-based features is a starting point, but its scope should be expanded incrementally through communication and discussions with system developers and potential users.
Services: The implementation specifications to access, manage, and process moving feature data with places and times encourage rapid and advanced utilization of movement data across many sectors. The SWG will consider new service interfaces with existing and emerging OGC APIs and SQL to best query and publish various types of movements of features, such as moving points, moving curves, and moving regions.
Data quality: Raw location data of moving features contain a large portion of noise and missing location due to obstruction during positioning and the network disconnection. The SWG will discuss a set of quality measurements, an interoperable framework, and/or a guideline to process, validate, and improve the data quality for the sharing of high-quality moving feature data.