My Master Thesis

 Location Based Services and mobile Spatial Decision Support (Working Title)

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