Abstract
Spatial data is information that is defined spatially (in location) by four dimensions (geometry and time) related to the earth (Grooth and McLaughlin, 2003). With the advancement of technology, most decision makers from many disciplines tend to rely on up-to-date accurate and accessible spatial data to support their operational and strategic decisions. The demand to access multi-organization spatial data continue to increase and has pushed the organization to share their spatial data as rarely all these data sets reside within one organization. However, persistent challenges exist in utilizing available spatial data across the multi-organization.
This paper provides an analysis of the state of spatial data sharing and examines intricate issues that hinder the utilization of multi-organizations spatial data. Content analysis and cognitive mapping techniques were applied using qualitative software ‘Nvivo8’ to help conceptualized the key issues.
A preliminary framework for research in spatial data sharing was derived from these findings and later refined by case studies in three different government departments in Brunei to produce the proposed conceptual framework.
Keywords: spatial data, spatial data sharing, framework
1 Introduction
Spatial data is information that is defined spatially (in location) by four dimensions (geometry and time) related to the earth (Grooth and Mc Laughlin, 2003). With the considerable advancement in the information technology, spatial data plays an important role in supporting many operational decisions from many disciplines especially in the built environment. Its usage is widespread across the globe and the demand to access a larger and wider data sets continue to increase. The ability to access a more comprehensive data sets will allow comprehensive analysis to be done and would therefore, improve in decision making. However, data sets do not normally reside within one organization.
Different organizations have different roles and responsibilities and most organizations have their own data sets and policy in dissemination and usage of their spatial data.
This research can be conceptualised within the framework as illustrated in figure 1.1. Figure 1.1 (a) shows current mechanism to access spatial data and figure 1.1 (b) shows proposed mechanism to access spatial data.
A preliminary framework for research in spatial data sharing N. Salleh & F. Khosrowshahi
School of Built Environment, University of Salford, UK
Fig 1.1: (a) accessing spatial data (current mechanism) (b) accessing shared spatial data (propose)
Therefore, it is undeniable that spatial data sharing is a strategy that would help decision makers such as architects, surveyors, planners, land values, engineers to access up-to-date and wider data sets to support their operational and strategic decisions.
1.1 Why share spatial data?
The need to share spatial data was clearly summarized by the Mapping Sciences committee of the National Research Council in 1993. ‘The principle of a spatial data sharing program is to increase the benefits to society arising from the availability of spatial data. The benefits will accrue through the reduction of duplication of effort in collecting and maintaining spatial data as well as through the increased use of this potentially valuable information. The exposure of these data to the wider community of users may also result in improvements in the quality of data. This will eventually benefit the donors and other users.’
The benefits of multi-organisational spatial data sharing cited in the existing literature are generally positive. Nedovic & Pinto (1999) highlighted spatial data sharing can reduce time spent in data collection and decision making, inclusion of more diverse maps and increased availability of data.
Onsrud and Rushton (1995) inferred the value of spatial data comes from its use, the more it is used, the greater the number of people evaluated and addresses the wide range of pressing problem to which data may be applied and thus increased the value of the data. The author further added sharing also allowed the data to be used rapidly for different process and resulted in greater use of the data without increasing the cost of developing and maintaining it.
Other benefits cited in the literature are user’s access up-to-date common data, allow cross- jurisdiction and cross-sectoral decision making, improve services and reduce time in accessing the data (National Research Council, 1993; Nedovic & Pinto, 1999; Azad & Wiggins, 1995; Onsrud &
Rushton, 1995; Kevany, 1995; Williamson et al., 2003; Masser, 2005).
Sharing also creates intangible advantages such as improved staff morale and self confidence (Nedovic-Budic & Pinto, 1999). Improved moral was by encouraging staff to communicate with other organizations and by providing necessary staff training would help to boost their self-confidence.
D3
D5 D 4
D1 D 2
D3 D 5 D 4
D 1
Barriers to access data Spatial Data sharing D2
USER
USER
USER USER
USER USER
USER
USER
1.2 Challenges in Spatial Data Sharing
Despite all these benefits, there were persistent challenges to multi-organizations spatial data sharing.
These challenges can be categorized as technical and non-technical factors (Onsrud & Rushton, 1995).
The technical factors relate to problems in coordinating system requirements (Calkins &
Weatherbe, 1995) lack of common data definition, formats, and models (Dawes, 1996), differences in data quality and networking costs (Nedovic-Budic and Pinto, 1999). Campbell & Masser (1995) argued that technical factors were well studied and mostly resolved, the non-technical factors which are equally important and needs more attention.
Non-technical factors relate to data confidentiality, liability, pricing (Campbell & Masser, 1995), lack of negotiation, institutional inertia (Craig, 1995), fear of losing autonomy over control of information and organizational power (Pinto & Azad, 1994; Azad & Wiggins, 1995; Meredith,1995), legal and public policy (Onsrud & Rushton, 1995), different data access policy established by individual organization (Nedovic-Budic & Pinto, 2001; Warnest, 2005), little coordination among various organizations (Wehn de Montalvo, 2003; Omran et al., 2006), inadequate planning and consultation about data use, insufficient staff, institutional disincentives, historical and ideological barriers, power disparities, differing risk perceptions, technical complexity, political and institutional culture (Dawes, 1996).
Calkins and Weatherbe (1995) criticised that organizational resistance to sharing data was due to lack of motivation, where organization are normally motivated if there are needs and capabilities. The author further inferred that ‘people’ were the main challenges to spatial data sharing because they represent the need to better isolate and address the human factors that are likely to impede free data sharing across organizational boundaries.
On social perspective, Wehn de Montalvo (2003) investigated the theory of ‘planned behavior’ as an organizational framework for the willingness to share spatial data. Omrans et al., (2006), purports that individual and organizational behavior are crucial factors to spatial data sharing. The author proposed a theoretical model that interacts between organizational behavior of spatial data sharing and social and cultural aspects.
All these frameworks and theories were not well grounded (except for When de Montalvo and Nedovic-Budic framework), and most of them draw on authors’ extensive understanding and experience with data sharing. However, it had provided a very useful basis to understand the current issues. They emphasized the importance of developing an improved understanding at the organizational level of the motivations and barrier for organizational cooperation.
The uncertainty on the effectiveness of these frameworks and theories was still a question.
Therefore, this paper examines the intricate issues that hinder the multi-organisation spatial data sharing both from the literature and empirically. Figure 2.1 shows the critical analysis of literature resulted in the conceptualisation of issues pertaining to spatial data sharing.
Figure 2.1, The conceptualisation of issues pertaining to spatial data sharing from critical analysis of literature
2 Analysis
In this research, multiple holistic case studies were adopted. Method of data collection was through semi-structured interview, focus group meeting and documentation in 3 selected government departments in Brunei. A total of 12 personnel ranged from Directors, Engineers, Planners, Surveyors, GIS/ IT background officers and technicians were involved. The questions were based on the preliminary findings from the critical analysis of literature (figure 2.1).
A qualitative software Nvivo8 was used to aid in performing analysis. The interviews and focus group meeting was transcribed in word process and transfer to Nvivo8. Using Nvivo8, the main issues rose were coded and grouped into theme of factors. These factors include Institutional, political, legal, social, technical and economic. A cognitive mapping was derived from the content analysis result to help in conceptualizing the findings (figure 2.2).
Institutional Political Legal Social
Non Technical Technical
Environment Resources Outcomes
Policy Power
Constraint
Confidentiality Liability Pricing
Insufficient staff Motivation
Behaviour Awareness
Data Forma IT
Capacity Infrastructure
Bureaucracy Responsibility
ISSUES
Figure 2.2, The conceptualisation of issues pertaining t spatial data sharing from case studies in 3 in Brunei
The case studies had identified issues that were well supported by the literature. It was revealed, security was one of the main concerned to spatial data sharing in Brunei. Economic was also raised as one of the main factors and plays an important role in sharing and maintaining spatial data.
Table 1 shows a comparison of the main issues rose in the literature findings and in the case studies. The ‘Hits’ showed the number of times that the issues been raised and this can be used as guidelines as common obstacles to spatial data sharing.
Institutional Political Legal Social Non Technical
Technical
Environment
Responsibility
Resources
Outcomes
Bureaucracy
Policy Power
Constraint
Confidentiality Liability Pricing
Motivation Behaviour Awareness
Data Format Infrastructure
Security
Economic
Continuous Funding ISSUES
IT Capacity
Insufficient Staff
Table 1. Issues in Spatial Data Sharing (comparison between literature review and case studies)
LITERATURE REVIEW CASE STUDIES
Factors Issues Hits Hits Issues Factors
Institutional Roles & Responsibility 15 12 Roles & Responsibility
Institutional
Environment 9 21 Environment
Resources to share 5 10 Resources to share
Outcomes 4 0 Outcomes
Political
Bureaucracy 6 13 Bureaucracy
Political
Policy 12 5 Policy
Power Disparities 5 0 Power Disparities Constraint &
Impediments
2 3 Constraint &
Impediments 7 Security
Legal
Confidentiality 3 3 Confidentiality
Legal
Liability 5 5 Liability
Pricing 6 11 Pricing
Social
Insufficient Staff 2 13 Insufficient Staff
Social
Motivation 7 0 Motivation
Behaviour 8 1 Behaviour
Awareness 5 2 Awareness
Technical Data Format 5 14 Data Format
Technical
IT Capacity 5 13 IT Capacity
Infrastructure 2 4 Infrastructure
12 Expertise
7 Continuous Funding Economi c
3 Development of conceptual framework for research in spatial data sharing
The paper addressed the problem associated with issues to spatial data sharing. The methodology which was adopted consisted of semi-structured interview, focus group meeting and documentation has provided an in-depth investigation in the 3 selected government departments in Brunei. It was revealed that there are 6 factors that remain as barriers to spatial data sharing. These factors include Political, Legal, Institutional, Social, Economic and Technical. In addition to this investigation, the existing literature has provided a solid foundation to conceptualise the framework.
Figure 3.1 illustrated a proposed conceptual framework for research in spatial data sharing, which was extended from figure 1.1(b) to include the 6 main factors.
4 Conclusion
The proposed conceptual framework consists of 6 main factors. Each of these factors needs to be considered in achieving successful spatial data sharing. The framework is useful for investigating the success or failure of multi-organisation spatial data sharing. Furthermore, the result achieved from this framework enabled us to focus main obstacles that need priority attention. It is important to note that this framework was derived from case studies in Brunei. Therefore, there tend to be additional or fewer issues in other countries because of difference in culture and administration.
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