Water Analytics and Management with Real-time Linked Dataspaces
7
provide Application Programmable Interfaces (APIs) over the dataspace that can
be re-used by application developers.
• Water Analytics Applications: At the top of the architecture are the water
usage and management applications that consume the resulting data and events
from the Real-time Linked Dataspace. These applications not only consume the
information from the dataspace but also generate user-friendly views over the
underlying data.
The support services play a crucial role in realization and exploitation of the
Real-time Liked Dataspace. These services include but are not limited to:
• Search & Query Service: The query service concerns the technical aspects of
enabling access to the data in the Real-time Linked Dataspace through structured
queries or RESTful API calls. The query service also enables low latency
data analysis. The search service provides keyword-based lookup queries over
underlying data sources and their descriptions. The objective of such a service
is to help developers and applications in a situation when their queries are not
well-defined.
• Entity Management Service: This service provides a catalog that serves as the
central registry of entities, datasets, and data sources. Within the catalog, all
water related datasets, entities, and other sources of information are declared
along with their descriptions. This includes a) the list of entities such as sensors
or locations that are important for understanding water data and b) open data
sources that are relevant to water management such as weather observation
stations or forecast services. Besides the APIs and query endpoints provided by
the individual data sources, the catalog also provides queries services over the
descriptions of entities and datasets.
• Event Processing Service: The event processing service allows automatic
matching of events similar to users defined rules based on a semantic model
for water management. Thus, it simplifies the task of water sensor management.
It allows the system to go up early, while administrators can add more meta-data
for sensor management in a pay-as-you-go manner [13, 15, 8].
• Human Computation Service: The support services, as described above, are
primarily focused on providing management tools and programmable access to
the constituent information of the Real-time Linked Dataspace. These services
are further complemented with a human computation service that is concerned
with the collaborative aspect of data management [27, 30]. Essentially, it allows
small tasks for data management to be distributed among people who are willing
to participate in the dataspace management and improvement process [29]. The
same service is further utilized for spatial tasks of data management in public
spaces [28].
7
provide Application Programmable Interfaces (APIs) over the dataspace that can
be re-used by application developers.
• Water Analytics Applications: At the top of the architecture are the water
usage and management applications that consume the resulting data and events
from the Real-time Linked Dataspace. These applications not only consume the
information from the dataspace but also generate user-friendly views over the
underlying data.
The support services play a crucial role in realization and exploitation of the
Real-time Liked Dataspace. These services include but are not limited to:
• Search & Query Service: The query service concerns the technical aspects of
enabling access to the data in the Real-time Linked Dataspace through structured
queries or RESTful API calls. The query service also enables low latency
data analysis. The search service provides keyword-based lookup queries over
underlying data sources and their descriptions. The objective of such a service
is to help developers and applications in a situation when their queries are not
well-defined.
• Entity Management Service: This service provides a catalog that serves as the
central registry of entities, datasets, and data sources. Within the catalog, all
water related datasets, entities, and other sources of information are declared
along with their descriptions. This includes a) the list of entities such as sensors
or locations that are important for understanding water data and b) open data
sources that are relevant to water management such as weather observation
stations or forecast services. Besides the APIs and query endpoints provided by
the individual data sources, the catalog also provides queries services over the
descriptions of entities and datasets.
• Event Processing Service: The event processing service allows automatic
matching of events similar to users defined rules based on a semantic model
for water management. Thus, it simplifies the task of water sensor management.
It allows the system to go up early, while administrators can add more meta-data
for sensor management in a pay-as-you-go manner [13, 15, 8].
• Human Computation Service: The support services, as described above, are
primarily focused on providing management tools and programmable access to
the constituent information of the Real-time Linked Dataspace. These services
are further complemented with a human computation service that is concerned
with the collaborative aspect of data management [27, 30]. Essentially, it allows
small tasks for data management to be distributed among people who are willing
to participate in the dataspace management and improvement process [29]. The
same service is further utilized for spatial tasks of data management in public
spaces [28].