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Proposal Master Thesis, March 2008 Spatial Decision Support Systems – Geographic Information Science and
Operations Research Keywords: location based
service (LBS), location based decision service (LBDS), mobile spatial decision
support system (mSDSS), decision analysis, mobile geoinformation application. Motivation and Task Location based services (LBSs) are normally
defined as information services accessible with mobile devices through a mobile
network and utilizing the ability to make use of the location of the mobile
device (Virrantaus
et al., 2001).
Other definitions describe LBSs as wireless service that uses geographic
information to serve a mobile user. All these definitions focus on the idea
that LBSs are services for providing information to the users rather than
services for decision support. Research topics related to LBSs include network
architectures and standards (Adams
et al., 2003, Ahn et al., 2004, Beaubrun et al., 2007),
mobile positioning techniques and space-time recording (Mountain
and Raper, 2001, Miller, 2003, Worboys and Duckham, 2004),
user interface design and user interaction (Meng,
2001, Hjelm, 2002, Zipf and Strobl, 2002), business cases and application fields for LBS (Beinat,
2001, Benson, 2001, Barnes, 2003) and locational privacy (Kwan
and Schmitz, 2002, Myles et al.,
2003, Armstrong and Ruggles, 2005). Typical applications are tourist information
systems, emergency response and disaster management, navigational services,
mobile yellow pages and leisure applications like buddy finder or instance messaging
(Palazzi,
2004). Figure 1 shows a diagram with
different application fields of LBSs. According to the field of interest there are several possibilities to
distinguish between different kinds of location services. One classification is
done on the application design (Voisard and Schiller, 2004, Kolodziej and Hjelm,
2006). Here in general two different kinds of location
services, considering if information is delivered on user interaction or not,
can be distinguished: ·
Push services imply that the user receives information without
direct or active request. The information may be sent to the user with prior
consent (e.g., subscription-based) or without prior consent (e.g., advertising
message) ·
Pull services deliver information actively requested from the
users. That means a user actively uses an application and pulls information from the network. For pull services a further
separation can be done into functional
services, like ordering a taxi by using a service on the device, or information services, like the search
for Point of Interests (POIs). Some services such as
a friend finder application integrate both push and pull functionality (Voisard and Schiller, 2004). Most LBSs use spatial
queries, like “find the nearest POI from my current location” or “find the
shortest path from my current location to a gas station”. Some of the
applications use a combination between spatial queries and attributive
information, e.g., “find the nearest hotel which costs less than a certain
amount of money”. With the introduction of the universal mobile
telecommunications system (UMTS) a big hype for LBSs was predicted, but the
potential of LBS is still not reached. Marcussen (2000) describes ten factors which are necessary to ensure the success of
LBSs. These could be summarized in bandwidth, actual content, location,
appropriate costs and secure payment, usability, personalization and privacy,
portals and search engines and internet enabled mobile devices. This list shows
aspects that have to be considered for implementing LBSs. The trend of LBS applications shows that
stronger personalization of the services is necessary to provide adequate and
user specific results (Zipf
and Strobl, 2002). At
the same time the privacy of the user has to be ensured. LBS applications have
found insufficient in considering individual user preferences and possible subtasks
(Zipf
and Strobl, 2002, Rinner and Raubal, 2005). To add decision support methods is one way to integrate
personalization in such services. LBSs should not only inform the users about
spatial phenomena but also assist them in their decision process according a
task related to space and eventually to time. The definition of Rinner and
Raubal (2005) about LBSs focuses on this idea: Location-based services (LBS) assist people in decision-making while
they perform tasks in space and time. Decision support methods in geographic
information systems (GIS) and LBSs go beyond simple querying. They enable users
to evaluate and rank decision alternatives based on multiple criteria. GIS-based
multi-criteria evaluation (MCE) is commonly used in applications such as site
suitability analysis (Malczewski,
1999). This set of methods, leads
to new challenges to software applications for mobile devices, and shows that LBSs
have to be enhanced in case of decision support functionality and
representation of decision alternatives. Research in geographic information
science and related disciplines like spatial decision support systems (SDSS) or
information technology can be considered for designing LBSs that assist people
in their decision processes. LBSs with decision support methods are sometimes
named as location based decision services (Pühretmair et al., 2002, Raubal, 2006, Muntermann,
2007) or
mobile spatial decision support systems (mSDSS). There are attempts to
integrate spatial decision support methods in web services (Rinner
and Malczewski, 2002, Rinner, 2003, Sugumaran and Sugumaran, 2005), but
until now decision support methods in combination with LBSs are rarely
suggested (Lee,
2005, Rinner and Raubal, 2005). Methodology This work should be a contribution to user-guided methods and user
interaction to maps on mobile devices to answer spatial and location related
questions and support decision processes. Decision analysis is a set of
systematic procedures for analyzing complex decision problems. The basic
strategy is to divide the decision problem into small understandable parts;
analyze each part; and integrate the parts in a logical manner to produce a
meaningful solution (Malczewski,
1999). The integration of geoweb
services or “geoweb 2.0” services could simplify the decision process and
reduce the complexity of the overall decision tree. Especially “geoweb 2.0”
services where the information is produced by a community can be useful to
integrate in the decision analysis. For example, a service where the community
can rate different hotels can be integrated in a LBS for finding the best hotel
according to different user parameters. The integration and combination of
distributed web services for data and functionality is influencing the
represented result. In this approach community information from geoweb services
together with actual location information is used as parameter influencing the
result of the mobile spatial decision support system (mSDSS). Additional
parameters for LBSs are evaluated in order to enhance the user personalization.
LBDS systems should include alternatives which are considered and integrated in
the system. This work should show how geoweb services can be integrated in an LBDS
system to simplify the decision process. Decision strategies are reconsidered
in order to integrate them into such applications. Users should be supported in trading off good against poor
characteristics of alternative destinations for example in a multi-criteria
evaluation or other decision support methods. MCE is a decision support
methodology, which is based on the idea that people use multiple decision
criteria to determine their best solution. Multi-criteria decision rules have
been implemented in geographic information systems (GIS) since the 1990s
including the simple additive weighting, analytic hierarchy process, ideal
point analysis, concordance, and ordered weighted averaging (OWA) methods (Carver,
1991, Jankowski, 1995, Malczewski, 1999, Jankowski and Nyerges, 2001). An
investigation on existing LBSs and academic works will be done to evaluate the
state of the art. Different decision support methods e.g. multi-criteria decision
making (Malczewski,
1999, Jankowski and Nyerges, 2001), will be reviewed for integration in mobile geographic applications. The
differences between current LBS approaches and LBSs with decision support and
the motivation to integrate spatial decision support techniques will be shown. Recent developments in the sector of mobile devices and mobile phones,
which can be seen as secondary or enabling technologies for spatial and
location services, should be considered to build new user centralized, mobile decision
support systems. These secondary or enabling technologies are for example
touch- or multi-touch screens and gesture interaction, open frameworks for
mobile platforms, (relatively) fast internet connections (3G and Wi-Fi) and positioning
technologies. The work should show a possible architecture for building LBDSs
or mSDSSs. Emphasis is taken on mobile eventually open frameworks. Possible
technologies could be Android (code.google.com/android, www.openhandsetalliance.com),
or the compact .net framework. The technology should serve users with
information that support their decisions near real time. Hypotheses Following hypotheses should be proven or repute throughout the work:
Expected Outcomes Objective of this work is to show the motivation and advantages for
integrating decision support methods in LBSs. In this scope current LBS
architectures are evaluated and differences between current approaches and LBDSs
or mSDSSs are identified. Geoweb services or “geoweb 2.0” services can simplify
the decision analysis. As output a proposal is given how geoweb services and
“geoweb 2.0” services can be integrated in LBS applications to reduce the complexity
of the decision tree and serve for decision support. One part is to show the
combination and interaction between information from geoweb services and
decision support methods for LBSs. The design of a prototype will show the possibilities of distributed web
services on a mobile map interface of an LBDS system. The example should allow
input for multi criteria evaluation. Users specify decision relevant parameters
to be used as evaluation criteria. The current location of the device is also
used as significant parameter in the decision process. This prototype is
evaluated and compared with existing solutions showing advantages and
disadvantages. The solution should be open and flexible to extent features and
modify it for different application fields. Literature Adams, P.M., Ashwell, G.W.B. & Baxter, R.,
2003. Location-Based Services — An Overview of the Standards. BT Technology Journal, 21, 34-43. Ahn, Y.S., Park, S.-Y., Yoo,
S.B. & Bae, H.-Y., 2004. Extension of Geography Markup Language (GML) for
Mobile and Location-Based Applications. Computational
Science and Its Applications – ICCSA 2004. 1079-1088. Armstrong, M.P. & Ruggles,
A.J., 2005. Geographic Information Technologies and Personal Privacy. Cartographica: The International Journal for
Geographic Information and Geovisualization, 40, 63-73. Barnes, S.J., 2003.
Developments in the M-commerce value chain: Adding value with location-based
services. Geography, 88, 277-288. Beaubrun, R., Moulin, B. &
Jabeur, N., 2007. An Architecture for Delivering Location-Based Services. IJCSNS International Journal of Computer
Science and Network Security, 7,
160-166. Beinat, E., 2001.
Location-based Services - Market and Business Drivers. GeoInformatics 4, 6-9. Benson, J., 2001. LBS
technology delivers information where and when its needed. Business Geographics, 9,
20-22. Carver, S., 1991. Integrating
multicriteria evaluation with GIS. International
Journal of Geographical Information Science, 5, 321-339. Hjelm, J., 2002. Creating Location Services for the Wireless
Web New York: John Wiley. Jankowski, P., 1995.
Integrating geographical information systems and multiple criteria
decision-making methods. International
Journal of Geographical Information Science, 9, 251 - 273 Jankowski, P. & Nyerges,
T.L., 2001. Geographic Information
Systems for Group Decision Making London: Taylor & Francis. Kolodziej, K.W. & Hjelm,
J., 2006. Local Positioning Systems: LBS
Applications and Services Boca Raton: Taylor & Francis Group. Kwan, M.-P. & Schmitz,
B.C., 2002. Privacy Protection and Accuracy of Spatial Information: How Effective
are Geographical Masks? GIScience 2002
(Second International Conference on Geographic Information Science). Boulder,
Colorado. Lee, G.-S., 2005. Fuzzy Multi-criteria
Decision Making-Based Mobile Tracking. In
O. Gervasi (ed.) International Conference
of Computational Science and its Applications, ICCSA. Singapore: Springer
Verlag, 839-847. Malczewski, J., 1999. GIS and Multicriteria Decision Analysis
New York: John Wiley & Sons. Marcussen, C.H., 2000. Mobile
Phones, WAP and the Internet. 2000 ed.: Centre for Regional and Tourism
Research. Meng, L., 2001. The immediate
usability of self-explaining interface for mobile users. Journal of Geographical Sciences, 11, 9-11. Miller, H.J., 2003. What about
people in geographic information science?*. Computers,
Environment and Urban Systems, 27,
447-453. Mountain, D. & Raper, J.,
2001. Positioning techniques for location-based services (LBS): characteristics
and limitations of proposed solutions. Aslib
Proceedings: new information perspectives, 53, 404-412. Muntermann, J., 2007.
Event-driven Mobile Financial Information Services – Design of an Intraday
Decision Support System Dissertation. Universität Frankfurt a. M. Myles, G., Friday, A. &
Davies, N., 2003. Preserving Privacy in Environments with Location-Based
Applications. IEEE Pervasive Computing, 2, 56-64. Palazzi, C.E., 2004.
Buddy-finder: a proposal for a novel entertainment application for GSM. IEEE Global Telecommunications Conference. Dallas,
Texas: IEEE, 540-543. Pühretmair, F., Rumetshofer,
H. & Schaumlechner, E., 2002. Extended Decision Making in Tourism
Information Systems. In K. Bauknecht,
A.M. Tjoa & G. Quirchmayr (eds.) E-Commerce
and Web Technologies Third International Conference, EC-Web. Aix-en-Provence, France:
Springer, 414. Raubal, M., 2006.
Location-Based Decision Services - eine neuartige Form mobiler räumlicher
Entscheidungsunterstützung. VGI - Vermessung
& Geoinformation, 94, 30-37. Rinner, C., 2003. Web-based
Spatial Decision Support: Status and Research Directions. Journal of Geographic Information and Decision Analysis, 7, 14-31. Rinner, C. & Malczewski,
J., 2002. Web-Enabled Spatial Decision Analysis Using Ordered Weighted
Averaging (OWA). Journal of Geographical
Systems, 4, 385-403. Rinner, C. & Raubal, M.,
2005. Personalized multi-criteria decision strategies in location-based
decision support. Journal of Geographic
Information Sciences, 11, 61-68. Sugumaran, V. & Sugumaran,
R., 2005. Web-based Spatial Decision Support Systems (WebSDSS): Evolution,
Architecture, and Challenges. In K.
Corral & D. Schuff (eds.) Third
Annual SIGDSS Pre-ICIS Workshop: Designing Complex Decision Support: Discovery
and Presentation of Information and Knowledge. Las Vegas, Nevada. Virrantaus, K., Tirri, H.,
Veijalainen, J., Markkula, J., Katanosov, A., Garmash, A. & Terziyan, V.,
2001. Developing GIS-Supported Location-Based Services. 2nd International Conference on Web Information Systems Engineering
(WISE 2). Kyoto, Japan: IEEE Computer Society, 66-75. Voisard, A. & Schiller,
J.H., 2004. Location-Based Services
San Francisco: Elsevier Science & Technology Books. Worboys, M.F. & Duckham,
M., 2004. GIS A Computing Perspective, 2nd
ed. Boca Raton:
Taylor & Francis. Zipf, A. &
Strobl, J., 2002. Geoinformation mobil
Heidelberg: Wichmann Verlag. |
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