=Paper=
{{Paper
|id=None
|storemode=property
|title=Interoperable Processing of Sensor-data in Spatial Data Infrastructures - A Use Case for Wind Power Analysis
|pdfUrl=https://ceur-ws.org/Vol-712/paper4.pdf
|volume=Vol-712
}}
==Interoperable Processing of Sensor-data in Spatial Data Infrastructures - A Use Case for Wind Power Analysis==
https://ceur-ws.org/Vol-712/paper4.pdf
Interoperable Processing of Sensor Data in SDIs – A
Use Case for Wind Power Analysis
Sandra Lanig, Georg Walenciak, Alexander Zipf
Dept. of GIScience, Institute of Geography, University of Heidelberg, Berliner Str. 48, 69120
Heidelberg, Germany
{lanig,walenciak,zipf}@uni-heidelberg.de
Abstract. Nowadays, sensor data are omnipresent and ubiquitous available.
Additionally, sensor measurements were required in several domains such as
disaster management or renewable energies. This paper presents a proposal how
sensor data measurements can be integrated in a standardized Spatial Data
Infrastructures (SDIs). Therefore we extended the SDI by the OGC Web
Processing Service (WPS) in order to compute and access sensor data
measurements served by a Sensor Observation Service (SOS).
Keywords: SDI, Sensor, SOS, WPS, WPS Profile, Renewable Energy
1 Introduction
Classical Geographic Information Systems (GIS) support geospatial
analysis and generating complex workflows in a proprietary manner.
However, each system interprets each geospatial analysis in a specific way
without clarifying a formal definition of the analysis. This hinders to interact,
exchange or execute analysis automatically on different systems. For the sake
of interoperability, a formal definition of geospatial analysis is required to
obtain proper working distributed systems. The formal definition needs to be
stated in both syntactically and semantically way. Regarding the movement
towards Web services, Spatial Data Infrastructures (SDI) are being
established on regional, national and supranational level e.g. GDI.de or the
European INSPIRE initiative. Especially, regarding the establishment of
SDI’s, interoperability of analysis is required to ensure further utilization of
geospatial data hold by web services. Thus, it is necessary to identify methods
to describe and structure the main Geographic Information Analysis (GI-
Analysis) formally of one specific domain.
On the one hand, the GI-Analysis of one domain needs to be identified. On
the other hand, each analysis has to be reviewed in regard to its internal
structure. On each level, GI-Analysis need to be described formally keeping
relevant attributes and parameters in mind. Identifying methods to formally
describe a GI-Analysis is one essential topic of this work. For that, this work
2 Sandra Lanig, Georg Walenciak, Alexander Zipf
is to be located on the conceptual level leading to conclusions that help to
develop standards ensuring and enabling interoperability of GI Analysis.
2 How to build a WPS Profile
Talking about GI-Analysis the OGC Specification Web Processing Service
1.0 [1] may be considered as the interface to enable interoperable GI-Analysis
in a SDI. In a nutshell, a WPS offers the possibility to hold a repository of
implemented geospatial processes. A client may request a description of the
repository (GetCapabilities operation) respectively a detailed description of
each process (DescribeProcess operation). Finally, it is possible to execute
each process (Execute operation). The process description (DescribeProcess
Response) is the essential aspect required to execute spatial analysis. As the
WPS is a generic interface, the process description defines the structure of an
analysis through description of the input-data and the output-data. However,
as the WPS was designed to be a generic interface, no specific GI-Analyses
are defined and though, no specific standardized GI-Analysis are offered via
this interface. Therefore, the specification offers the option to define WPS-
Profiles. In principle a WPS Application Profiles includes the formal
description of one specific process and an OGC URN that identifies the
analysis. The specification further states that it is possible to specify a
repository that represent a semantically structure of processes which may be
part of the same application domain [1].
Although there are quite a lot of scientific papers that show how geospatial
analysis can be provided through the WPS interface [2, 3, 4, 5, 6] several
authors believe that the essential goal, to enable interoperability, has not been
reached yet [7]. This is reasoned by the strong generic nature of the
specification and by the imprecise process description. Especially in regard to
the semantic description of GI-Analysis several authors see the need for
further research [8, 5, 9].
Concerning application domains, there are some examples on how to build
a semantically structure in a WPS Profile [7, 10, 6]. However, as the process
description is regarded not to be sufficient, the definition WPS Profiles is
hindered since the description is an essential aspect of a profile. Although
there are several approaches in building classification schemes for GI-
Analysis [11, 12, 13, 14], those are too general or too generic to enable the
development of domain-specific interoperable GI-Analysis so further research
regarding this topic is required.
In a nutshell, there is further need for research concerning interoperability
of GI-Analysis. To even broaden the view on WPS Profile, this paper is on
integrating live sensor data in a WPS Profile since the link between sensor
and analysis is an important area of application.
Interoperable Processing of Sensor Data in SDIs – A Use Case for Wind Power Analysis
3
3 Integrating Live Sensor Data in 3D SDI
The OGC Sensor Web Enablement (SWE) initiative dealing with the
integration of all kind of types of dynamic sensor data like wind
measurements, temperatures, water levels etc. in a standardized way within
SDIs [15].
3.1 State of the Art
The integration of sensor data into a SDI was recognized with the
emergence of a variety of live sensor data sources coupled with rapidly
declining sensor costs [16]. However, the collecting of sensor data can cause
huge data sets. The question that arises is: how can this massive datasets are
analyzed in a standardized way. One solution to support utilization of these
datasets is the use of geospatial analysis offered via the WPS interface. First
steps are made providing traffic data (TMC data) by a Sensor Observation
Service (SOS) [17] and processing of the SOS results using a WPS [18]. In
another use case we analyze the dispersion of a gas plume caused by a gas
leakage and integrate wind speed and wind direction measurements form a
SOS in our 3D SDI [19].
3.2 Use Case - Workflows for Renewable Energies
Our research focuses on the integration of live sensor data of the renewable
energy domain into SDI. Based on former research [18, 19], initial steps have
been taken by the integration of live sensors in our 3D WPS. Therefore, as a
proof of concept, we present a proposal how the integration of SOS-based
wind measurements in a SDI could take place via WPS profile.
In our geoprocessing workflow, the WPS process
`WindPowerStationScenario3D´ uses input data from a SOS interface to
encapsulate weather data like wind speed and wind direction provided for
example by the German Weather Service (DWD). The input parameter of the
WPS process is the location of the weather measuring station (x, y, z
coordinates), and the actual measurements of wind speed and direction. Thus,
the `WindPowerStationScenario3D´ process sends a GetObservation request
to the SOS. The next step is the interpolation of wind speed and direction
measurement of each weather station by the WPS interpolation process. The
interpolation takes place based on the SOS values of the weather
measurement stations.
A location analysis for the use of wind energy requires the consideration of
specific wind conditions. Generally a wind turbine or a wind park is
economically profitable with wind speed of at least 6 m/s at hub height.
Besides wind speed there are further limiting factors for the usage of wind
4 Sandra Lanig, Georg Walenciak, Alexander Zipf
energy and the appropriate location. This includes protected areas and nature
reserve, the slope of terrain, a buffer around settlements, the infrastructure,
and water or forest surfaces.
Fig. 1. Sequence diagram overview WPS Application Profile for
`WindPowerStationScenario3D´ analysis
3.3 Proposal for a `WindPowerStationScenario3D´ WPS Application
Profile
Currently, there is no formal specification about the combination of
application profiles and the OGC SOS. In a nutshell the SOS allows
operations to request live sensor data respectively sensor data from a specified
time period. In respect to a WPS Application Profile, a detailed description of
the required sensors is an essential prerequisite on building WPS Profile that
integrates live sensor data. Technically the SOS provides the option to
formally describe one specific sensor. This description should be added to a
WPS Application Profile. One possible solution is to extend a WPS Profile by
the description of the depending data sources. Whereby, the data source must
be described in terms of their data structure. This way, the definition of an
analysis would be more precise since the definition of input data is essential
for the correct outcome of the process.
Interoperable Processing of Sensor Data in SDIs – A Use Case for Wind Power Analysis
5
In order to operate a wind park economically, the possible energy potential
must be determined for planning the location of a wind park. For this a
domain specific WPS Application Profiles `WindPowerStationScenario3D´
was developed. Therefore, we use generic basic analysis like the buffer or the
slope calculations of a terrain model and integrate these basic analyses in a
complex workflow. Thus, suitable locations for wind parks can be
determined. Still missing is the integration of the weather measurement data.
This is made by the definition of a WPS extension for live weather
measurement sensors. Based on the measured weather data the wind speed
and the wind direction for different hub heights can be computed. For this
computation models already exist. But to access these models in an
interoperable and standardized way it may be available via the WPS interface.
4 Summary and Outlook
In this paper we present first steps how sensor data can be integrated in SDI
through a WPS. This takes place by a WPS Application Profile based on a
typically use case for wind power analysis in the renewable energy domain.
Further research has to deal with the integration of more complex wind speed
simulation models based on Computational Fluid Dynamics (CFD).
Additionally we would like to integrate our results into our 3D SDI.
References
1. Schut, P.: Web Processing Service. Open Geospatial Consortium, DocNr. 05-007r7 (2007)
2. Stollberg, B., Lutz, M., Ostländer, N., Bernard, L.: Geoprozessierung in
Geodateninfrastrukturen - Aufgaben für die nächste Generation. In: GIS Zeitschrift für
Geoinformatik 4, S. 24-29 (2007)
3. Stollberg, B., Zipf, A.: Geoprocessing Services for Spatial Decision Support in the Domain
of Housing Market Analyses - Experiences from Applying the OGC Web Processing
Service Interface in Practice. The 11th AGILE 2008 Conference on GI Science (AGILE
2008). Girona. Spain (2008)
4. Foerster, T.: Establishing an OGC Web Processing Service for generalization processes. ICA
workshop on Generalization and Multiple Representations. IGN. France (2006)
5. Brauner, J., Foerster, T., Schaeffer, B., Baranski, B., Haunert, J-H, Kieler, B., Milde, J.:
Towards a Research Agenda for Geoprocessing Services. In: Sester, M.; Bernard, L.;
Paelke, V. (Hg.): Advances in GIScience. Proceedings of the 12th AGILE Conference.
Dordrecht: Springer (Lecture notes in geoinsformation and cartography) (2009)
6. Lanig, S., Zipf, A.: Proposal for a Web Processing Services (WPS) Application Profile for
3D Processing Analysis. In: Proceedings of the 2010 Second International Conference on
Advanced Geographic Information Systems, Applications, and Services. Washington, DC,
USA: IEEE Computer Society (GEOPROCESSING ‘10), S. 117-122 (2010)
7. Nash E.: WPS Application Profiles for Generic and Specialised Processes. In: Pebesma, E.;
Bishr, M.; Bartoschek, T.: GI-Days 2008: Proceedings of the 6th Geographic Information
Days, June 16-18, 2008, Münster, Germany. Münster : Institut für Geoinformatik,
Universität Münster, 2008. - ISBN 978-3-936616-54-5, S. 69 - 79 (2008)
6 Sandra Lanig, Georg Walenciak, Alexander Zipf
8. Kiehle, C., Greve, K., Heier, C.: Requirements for Next Generation Spatial Data
Infrastructures-Standardized Web Based Geoprocessing and Web Service Orchestration. In:
Transactions in GIS, Jg. 11, H. 6, S. 819–834 (2007)
9. Yang, C., Raskin, R.: Introduction to distributed geographic information processing research.
In: Int. Journal of Geographical Information Science, Jg. 23, H. 5, S. 553–560 (2009)
10. Walenciak, G., Zipf, A.: Designing a Web Processing Service Application Profile for
Spatial Analysis in Business Marketing. In. Proc. of AGILE 2010 Conference (2010)
11. Goodchild, M. F.: A spatial analytical perspective on geographical information systems. In:
Int. Journal of Geographical Information Systems, Jg. 1, H. 4, S. 327–334 (1987)
12. Tomlin, C. D.: Geographic information systems and cartographic modeling. Englewood
Cliffs, NJ: Prentice Hall (1990)
13. Chrisman, N.: A transformational approach to GIS operations. In: International Journal of
Geographical Information Science, Jg. 13, H. 7, S. 617–637 (1999)
14. Albrecht, J.: Universelle GIS-Operationen. Eine benutzerzentrierte Systematisierung
datenstrukturunabhängiger GIS-Funktionalität als Grundlage einer Geographischen
Modellierungssprache (1995)
15. Botts, M.: OGC White Paper - OGC Sensor Web Enablement: Overview and High Level
Architecture. Version 2.0. OGC 06-050r2 (2006)
16. Resch, B., Blaschke, T. and Mittlboeck, M. (in press) Live Geography - Interoperable Geo-
Sensor Webs Facilitating the Vision of Digital Earth. International Journal on Advances in
Networks and Services, pp. 323-332 (2011)
17. Na, A., Priest, M.. Sensor Observation Service. Version 1.0 OGC 06-009r6 (2007)
18. Mayer, C., Stollberg, B. and Zipf, A.: Providing near Real-time Traffic Information within
Spatial Data Infrastructures. The International Conference on Advanced Geographic
Information Systems & Web Services (GEOWS 2009). Cancun. Mexico (2009)
19. Walenciak, G., Stollberg, B., Neubauer, S. and Zipf, A.: Extending Spatial Data
Infrastructures 3D by Geoprocessing Functionality - 3D Simulations in Disaster
Management and environmental Research. The International Conference on Advanced
Geographic Information Systems & Web Services (GEOWS 2009). Cancun (2009)