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Geography Compass 3 (2009): 10.1111/j.1749-8198.2009.00241.x
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Blackwell Oxford, Geography GECO © 1749-8198 Journal March 10.1111/j.1749-8198.2009.00241.x 241 1 0 Original 20??? Review ??? 20092009 of The UK Compilation Article GIS Publishing Compass Authors Design© Ltd 2009 Blackwell Publishing Ltd
GIS Design: A Review of Current Issues in Interoperability Miguel-Ángel Manso* and Monica Wachowicz Universidad Politécnica de Madrid
Abstract
The evolution of Geographic Information Systems (GIS) has witnessed an important step towards achieving interoperability through the communication, exchange, cooperation and sharing of resources between systems. The main developments in interoperability include the use of standards for transfer and exchange of geographical information, the integration of different data types up to the development of comprehensive interoperability models. This article aims to review the main advances in interoperability of GIS and provide a basis to identify the future research issues in this field. It first considers the various points of view from which interoperability can be defined and then examines the concept of interoperability itself. An overview is provided on how interoperability can be modelled by discussing the main aspects that directly have an effect on how interoperability levels have been created according to different contexts and purposes of use. It also points out the significant advances in terms of measures that can determine the ability of a GIS to interoperate with other systems, predict the resources needed for successful interoperation, and discover techniques useful to achieving interoperability. We conclude with some suggestions where the research will go next.
1 Introduction The evolution of Geographic Information Systems (GIS) has been significant and has shown the migration from the mainframe to the desktop personal computer and to the portable device (Dangermond 1991; Longley et al. 2000). Currently, there exist hundreds of software houses developing GIS applications based on their own or third-party technologies. Geographers are also developing their own applications using macro, scripting or mark-up languages. As a result, there are a growing number of different systems and data formats available, leading to a variety of software that coexist and interact over the Internet in such a way that users may not be aware of such multiplicity and heterogeneity. This is interoperable GIS. However, it took time for the realisation of the benefits of interoperability as the ability to combine disparate data and to allow different systems to communicate to each other. For example, the concept of remote data © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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capture and storage, which is accessible through common tools, is one that underpins the World Wide Web. This analogy has recently been applied to the GIS sector. Some examples include collaborative geospatial Web applications (Balram and Dragiaceviac 2006) and public participation GIS (Sieber 2006). Without any doubt, the new generation of GIS will continue to have interoperability as one of its main research topics. This literature review focuses on how interoperable GIS were developed in comparison with information systems in general; the interoperability models that are used to implement them; the technical standards they mandated and recommend; the way they are managed; and the implementation and measure mechanisms they have established. The overall goal is to identify the current research issues in terms of interoperability models, levels and measures. However, it is important to point out that a complete review is not possible here because of the extensive research carried out in interoperability in the last decades. Moreover, it is essential to us that the readers have at least an objectively comprehensive review that provides an impartial and balanced survey of interoperability, and its relationship to information system development. Following the Introduction, Section 2 illustrates the various points of view from which interoperability can be defined and then examines the evolution of the concept of interoperability itself using the standard and scientific views. Section 3 considers how interoperability can be modelled by discussing the main aspects that directly have an effect on how interoperability levels have been created according to different contexts and purposes of use of information systems, and in particular information systems, and in particular GIS. Section 4 briefly describes how these interoperability levels can be related in different contexts, including the GIS domain. Section 5 discusses the main achievements in computing measures that can determine the ability of a GIS to interoperate with other systems; predict the resources needed for successful interoperation; and discover techniques useful to achieving interoperability. In Section 6, we conclude with some challenges where the research will go next. 2 The Evolution in the Definitions of Interoperability The term interoperability has many meanings, including the notions of communication, exchange, cooperation, and sharing of resources between systems. In fact, the essence of interoperability is that it is a relationship between systems, where each relationship is a manner of communication, exchange, cooperation and sharing (Carney et al. 2005). Our focus is on GIS, which may be composed of several components of hardware, software, supplies, policies, procedures and people, which store, process and provide access to geographic information. Within these components, users have traditionally adopted a proprietary or homogeneous approach based on a single GIS product and using that system’s proprietary technology as a © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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Fig. 1. xxxxxxxxxxxxxxxxx.
de facto standard. In contrast, interoperable GIS are computing environments in which a variety of the same components coexist and interact. In Figure 1, the three smaller circles represent an individual GIS that is related to two others by some interoperability relationship. All together, they are distributed or heterogeneous GIS but related as a unit, usually named as system of systems, which is depicted by the large oval. Different definitions of the term interoperability are available in the literature and they usually differ in terms of the relationship description as well as the system components. They vary from focussing on system and hardware components onto services in order to provide information and components sharing information, and to use the information that has been exchanged in a useful and meaningful manner without any special manipulation (Buehler and Mckee 1998; Flater 2002; Ford et al. 2007). From the point of view of the standards developing organisations, the focus is given to the technical objectives of exchanging resources between systems. In particular, the standard specifications of the ISO 19100 series are related to the standardisation of geographic information. The Geographic Information–Reference Model (ISO 19101 2002) and Geographic Information–Services (ISO 19119 2005) are the standardisation efforts to facilitate interoperability of GIS, including interoperability in distributed computing environments. In contrast, the definitions of interoperability proposed by policy studies organisations have emphasised the engagement process necessary to exchange and reuse of information. Some authors point out that such a process should ensure that systems, procedures and culture of an organisation need to be managed in such a way as to maximise opportunities for © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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exchange and reuse of information, whether internally or externally (Dekkers 2007; Gordon 2003; Miller 2000; Nedovic-Budic and Pinto 2001). The notion of compatibility has also been introduced to define the relationship of systems from a policy point of view. Taylor (2004) defines interoperability as the compatibility of two or more systems such that can exchange information and data without any special manipulation of the users. The notion of cooperation has also been proposed by standard organisations (Buehler and Mckee 1998; ISO 19101 2002). In the GIS domain, Rawat (2003) defines interoperability as the ability of a system to cooperate and exchange geographic information and data of different organisations, for any kind of applications over networks. Carney et al. (2005) extended the above definitions by adding the notions of purpose (goal) and context (environment). As a result, interoperability becomes the ability of a collection of system components to (a) share specified information and (b) operate on that according to a shared operational semantics in order to achieve a specified purpose in a given context. This leads to the definition of interoperability models, which can ensure that interoperability occurs between systems, but accordingly to different purposes and contexts. 3 The Research Domain on Interoperability Models There are many approaches to building GIS by means of interoperability models. Each approach has specific advantages and disadvantages with respect to achieving interoperability in a particular context (Lewis et al. 2005). But in general, the main advantages of interoperability models are the ability to (a) define a common vocabulary that allows meaningful discussion and analysis; (b) provide hints regarding the structure of solutions; and finally (c) serve as a basis to evaluate new ideas and assess different options (CMU-SEI). Some examples of interoperability models that have been successfully applied to contexts outside of the GIS domain were the C4ISR Architectures Working Group’s Levels of IT Systems Interoperability model from (Software Engineering Institute 1997), the Enterprise Interoperability Maturity Model (EIMM) (Athena 2005), the Organisational Interoperability Maturity Model (OIMM) (Clark and Jones 1999), and the Organisational Interoperability Agility Model (OIAM) (Kingston et al. 2005). Two exceptions are the Levels of Conceptual Interoperability Model (LCIM) defined by Tolk (2003) and refined by Turnitsa and Tolk (2006) as well as the Intermodel5 (Shanzhen et al. 1999) that have been used in the GIS domain. Basically, they focus on the highest layers of organisational interoperability, having seven levels: no interoperability, technical, syntactic, semantic, pragmatic, dynamic and conceptual levels (Figure 2). Without any doubt, the outmost research challenge in interoperable GIS still remains of closing the gap between the different models that © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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would provide a unified method based on the strengths and weakness of each individual model and their seamless integration. Nowadays, each interoperability model in GIS defines a common taxonomy that supports different purposes of use by achieving interoperability in different contexts. Layers, dimensions, levels or areas are the concepts usually used to define such a common taxonomy. They depend on the type of context an interoperability model is applied to implement an interoperable GIS. The next session will review the efforts carried out to undertake this research challenge. 4 The Design of Interoperability Levels The levels of interoperability are a set of criteria and associated processes for assessing GIS capabilities and implementation in the context of the degree of interoperability required. Several levels have been proposed in the literature according to the interoperability required: semantic, technical, legal, organisational and others. Table 1 illustrates our attempt to show an indication of the evolution on the definition of interoperability levels. By no means is a complete summary of the efforts found in the literature © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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© 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
Year Model acronym
x
x
x
x
x
x x x x
x
x
x x
x
x
x
x
x
x
x
x x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Technical Schematic Semantic Organisa- Physical Empirical Syntactic Pragmatic Social Intercom- Political/ Legal InterDynamic Conceptual or structural tional munity Human national
Interoperability levels
1990 x 1997 1997 Integrated x Interoperability model for GIS Bishr 1998 Vckovski 1998 Harvey et al. 1999 x Shanzhen 1999 Intermodel5 et al. Ouksel and 1999 Open Systems x Sheth Framework for Social Interaction Miller 2000 x Nedovic2001 Budic and Pinto Tolk 2003 Coalition x Interoperability Model Tolk and 2003 LCIM x Muguira
ISO Goh Goodchild et al.
Author
Table 1. An indication of the evolution on the definition of interoperability levels.
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2004 2004 2004
Bermudez Shekhar Schekkerma n Stroetmann Ding Kuhn Nowak et al. Mohammad i Kalantari Vas Assche
Geography Compass 3 (2009): 10.1111/j.1749-8198.2009.00241.x
x
x
x
8
x
x x
20
8
1
1
x
16
x x
x
x x x
x
x x x x
x x x
x
x
x
x
x
x x x x
x x x
7
x
x
x
4
x
x
x
2
x
4
x
4
x
x
1
4
x
4
x
Technical Schematic Semantic Organisa- Physical Empirical Syntactic Pragmatic Social Intercom- Political/ Legal InterDynamic Conceptual or structural tional munity Human national
Interoperability levels
2006 x 2006 An Interoperability Framework Turnitsa and 2006 LCIM x Tolk Dekkers 2007 x Chen D. 2007 InterOp x Zeigler and 2008 Hammonds 14
2006
2005 2005 2005 2005
Year Model acronym
Author
Table 1. Continued
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in the design of interoperability levels. There are a large number of interoperability levels proposed in the literature, and it would be very difficult to tell them apart because their classification is highly correlated, and their definitions have common characteristics with each other. In general, fifteen levels of interoperability have been proposed in the literature in the last decade. They are Semantic, Syntactic, Technical, Pragmatic, Organisational, Schematic or Structural, Dynamic, Legal, Conceptual, Social, Intercommunity, Political/Human, International, Empirical, and Physical. They are usually considered to have a hierarchical structure such as the one proposed in the LCIM (Turnitsa and Tolk 2006). This has particularly been the case in the GIS domain, where integrated hierarchical interoperability levels have been proposed (Goodchild et al. 1997, Shanzhen et al. 1999). Users are usually required to predetermine the interoperability levels and place procedures and measures for the necessary communication to occur within an application domain. It is important to note that the International, Empirical, and Physical levels have rarely been mentioned in the literature; whereas the Semantic interoperability level has been the most cited, followed by the Technical, Syntactic and Pragmatic levels, respectively. In contrast, the remaining interoperability levels have hardly ever been mentioned. They are one of the following:
Interoperability Level, which identifies cultural aspects, such as the 7 • Social interests, beliefs, expectations and commitments (Assche 2006; Kuhn
2005; Mohammadi et al. 2006; Ouksel 1999); • Intercommunity Interoperability Level, which is related to common solutions at different levels of geographic granularity and different knowledge domains (Kalantari et al. 2006; Miller 2000); • Political/Human Interoperability Level, which identifies aspects related to policies or guidelines of organisations concerned with the dissemination and maintenance of information (Harvey et al. 1999; Miller 2000; Mohammadi et al. 2006), • International Interoperability Level, which considers aspects of the language in which data are provided or described, so as to avoid comprehension problems of certain languages on the part of users (Miller 2000); • Empirical Interoperability Level, which is related to the entropy, variety and equivocation encountered in systems (Assche 2006); and • Physical Interoperability Level, which is related to the physical appearance, the media and amount of contact (Assche 2006). As a result, they will not be mentioned any further in this review. 4.1
SEMANTIC INTEROPERABILITY LEVEL
Semantic interoperability concerns with the meaning of the information, or in other words, it is about making sense of other people’s data © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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(Dekkers 2007). The differences in information context are usually due to the different meanings of the same real-world entity that is stored in different databases (Nowak et al. 2005; Schekkerman 2004). Bermudez (2004) and Goh (1997) have identified three aspects related to different interpretations of a concept in metadata domain. They are synonyms and homonyms of scales as well as measurement units. In fact, Vckovski (1998) has emphasised the need for specifications that can deal with the semantic heterogeneities. Other authors have also emphasised the need of a common reference model for information exchange since the meaning of the data is shared at the semantic interoperability level, which represents the harmonised terminology and interpretation of concepts (Antonovic and Novak 2006; Kalantari et al. 2006; Turnitsa and Tolk 2006). Ding (2005) adds the importance to storing the interrelations between ontologies and the application of fuzzy mapping. For example, a road network for pavement management has different semantic descriptions from transportation data maintained in a GIS database designed for small-scale topographic mapping applications (Bishr 1998). Therefore, it is evident that the current research issue is still tied up to the fact that the geographical space may have more than one description in the underlying GIS databases that complies with various disciplines, giving as a consequence semantic heterogeneity. Several efforts in dealing with this research issue are found in the literature (Frank and Kuhn 1999; Kuhn and Raubal 2003). Another research issue is that different GIS users should be able to understand the meaning of exchanged information. In this case, semantic interoperability is concerned with ensuring that the precise meaning of exchanged information is understandable by any other application not initially developed for this purpose. There has been several efforts to produce standardised taxonomies in domains such as transportation networks that use the Geographic Data Files standard to store geographic information for intelligent transport systems (OGC 1998) as well as the development of new approaches for the description of semantic proximity between objects, relationships and context (Harvey et al. 1999; Probst 2006; Rodriguez and Egenhofer 2003). 4.2
SYNTACTIC INTEROPERABILITY LEVEL
The syntactic interoperability level provides a common structure to exchange information in which a common data format is applied (Turnitsa and Tolk 2006). The CMU-SEI has included this level into the LCIM model as the one allowing data exchange in standardised format (supporting the same protocol and format). In the GIS context, Shekhar (2004) defines syntactic interoperability as the specification of common message formats (e.g. tags and marking) to interchange spatial data, patterns and © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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relationships. Bishr (1998) points out the roles of syntactic heterogeneity since each database may be implemented in a different Database Management System of different paradigms, such as relational or object-oriented models. At this interoperability level, the need to translate metadata from one application context to another is an important requirement that has received relatively little attention in the GIS domain. Metadata is a hierarchical concept in which metadata is a descriptive abstraction above the data it describes (Zeigler and Hammonds 2008). The research challenge relies on understanding how appropriate is metadata in existing data exchange at the syntactic level for a range of possible applications in interoperable GIS. The research begins with the identification of candidate metadata attributes and it continues with the analysis to determine whether the metadata are interchangeable and to what degree (Landgraf 1999). 4.3
TECHNICAL INTEROPERABILITY LEVEL
Dekkers (2007) relates this level with the interconnection, presentation and exchange of data, accessibility and security characteristics such as protocols, interfaces, document formats, data encoding, as well as accessibility measures and security solutions. Miller (2000) proposes communication, transport, storage and representation standards as technical aspects of interoperability, and he mentions the Z39.50 protocol as an example (ISO 23950 1998). On this level a communication protocol exists for exchanging data between participating systems. There is certainly a need to develop standard communication, exchange, modelling and storage of data information, as well as access portals and interoperable Web services equipped with user-friendly interfaces (Kalantari et al. 2006). The CMU-SEI recommends taking into account the technical aspects when creating evaluation models to assess interoperability, rather than using them into models of interoperability. Goodchild et al. (1997) consider technical aspects of the interoperability of the distributed computing environment, the communication networks, the technologies themselves, and the distributed computation platforms. It extends the need of improvement in technical interoperability to data and middleware. Technical interoperability is basically regarded as the link between computer systems and services (Schekkerman 2004; Tolk and Turnitsa 2006). The main research issue is to have a network of interoperable GIS that allows access to data and services for their manipulation at sustainable cost, together with application standard protocols for Earth Observation, GIS, and mobile sensor networks. The technical interoperability level is the backbone that allows providers of geo-information to attach their data and services at marginal costs, and as a result, getting the profit derived from their usage. This is particularly relevant with the advent of user-generated © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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mapping (Dodge 2008), volunteer geo-information (Goodchild 2008) and affective cartography (Cartwright 2007). Only the availability and easy technical interoperability will enable the access to value-added providers of even more specialised, higher-level services, which will be targeted to a specific application use. 4.4
PRAGMATIC INTEROPERABILITY LEVEL
Assche (2006) attributes to this level the intentions, responsibilities and consequences behind the expressed statements. Pragmatic interoperability is achieved to the extent that users of interoperable services have compatible intentions, responsibilities and consequences concerning the interoperable services and information exchange. In this context pragmatic interoperability is especially concerned with the fact that all parties involved in providing and using a service also take their responsibility. For Turnitsa and Tolk (2006), this level is reached when the interoperating systems are aware of the methods and procedures that each are employing. In other words, the use of the data – or the context of its application – is understood by the participating systems. Shanzhen et al. (1999) proposes the exchange of geo-processing and analysis functions between different communities or departments mainly because we can adopt distributed object computing. The main research issue is related to how do we provide pragmatic interoperability level mechanisms in a Service Oriented Architecture (SOA) (ESRI 2007). SOA separates functions into distinct units, or services, which developers make accessible over a network in order that users can combine and reuse them in the production of GIS applications. Users might do it fairly well in static contexts, but even a small change of context will result in miscommunication. The developing of net-centric and SOAbased environments have made addressing this problem at the pragmatic level critically important. 4.5
ORGANISATIONAL INTEROPERABILITY LEVEL
Dekkers (2007) includes in this level cooperation within organisations (business process interoperability), business goals and process modelling. It includes exchange of information between partners (scientific domains, suppliers and clients, administration agencies), as well as all coordination of business task such as meeting user needs, results of cost–benefit analysis. The IDABC Project (2006) reiterates Dekkers’s views and takes into account the user requirements regarding identification and access, as well as user orientation availability. In summary, organisational interoperability primarily determines when and why certain data is exchanged (SAGA 2006). This means that within the scope of organisational interoperability, processes that result in the © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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interchange of data are coordinated with a view to legal frames of reference (e.g. legislation and regulations). However, very few studies have been carried out to address the mechanisms and implementation factors involved in the coordination process, as well as the benefits from achieving organisational interoperability, especially in terms of human and coordination aspects of sharing GIS and associated databases across organisational boundaries. Goodchild et al. (1997) point out that the benefits will be achieved when the business interoperability is clearly defined as the individual conceptualisation of organisations. Moreover, Nedovic-Budic and Pinto (2001) provide an interesting evaluation of interorganisational activities in the US context that facilitate or obstruct the process of coordination to reach organisational interoperable GIS. The Infrastructure for Spatial Information for Europe (INSPIRE) and National Spatial Data Infrastructure (NSDI) initiatives are probably the most relevant ventures to enabling a cooperation process for organisational interoperability by encouraging partnership among organisations to assist data sharing best practices (Georgiadou and Harvey 2007; Lance et al. 2008; Vandenbroucke 2005). 4.6
CONCEPTUAL, SCHEMATIC OR STRUCTURAL INTEROPERABILITY LEVEL
Turnitsa and Tolk (2006) state that this type of interoperability may be reached when the conceptual model may be documented by engineering methods, so that it may be interpreted and assessed by a third party. In this case, if the conceptual models – i.e. the assumptions and constraints of the meaningful abstraction of reality – are aligned, the highest level of interoperability is reached. Nowak et al. (2005) also define the heterogeneity in the database models or schemas as aspects related to the structural interoperability; meanwhile, Abel (1998) proposes the development of Virtual GIS as a solution for heterogeneous systems integration. Several approaches have been proposed in the literature (Bishr 1998; Goh 1997; Shekhar 2004) for handling data type (different data primitives in different systems), label inconsistencies (synonyms and homonyms in different schemes), aggregation discrepancies (different forms of design or assignment of attributes to the entities) and generalisation conflicts (ways of relating entities to one another). One recent effort is Geoscience Markup Language, which consists of a Geography Markup Language (GML) Application Schema that can be used to transfer information about geology, with an emphasis on the ‘interpreted geology’ that is conventionally portrayed on geologic maps. It was created to support schematic interoperability of information served from Geologic Surveys and other data custodians (Commission for the Management and Application of Geoscience Information 2008). More similar efforts towards the development of application schemas built on specific GML profiles are expected in the near future. © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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4.7
DYNAMIC INTEROPERABILITY LEVEL
This type of interoperability takes place when systems are able to comprehend the state changes that occur in the assumptions and constraints that each is making over time, and are able to take advantage of those changes (Turnitsa and Tolk 2006). Shanzhen et al. (1999) proposes a resource discovery level in Intermodel5, which is based on the existence of metadata standards, and the capability to locate resources for their exploitation. There are many methods, such as FGDC developed metadata Clearinghouse, in the project of NSDI. Metadata provide the description of spatial information (including content, quality, and position) and recommend application. The main research issues are related to mobile sensor networks, mainly because they are revolutionising the way geospatial information is collected and analysed in GIS (Nittel and Stefanidis 2004). Their dynamic interoperability has already been pointed out as an important issue by the OGC for the implementation of integrated sensing systems (Botts et al. 2007). The research challenge is twofold: dynamic data interoperability and dynamic network interoperability. The dynamic interoperability of sensor data will aim to ensure the exchange and integration of sensing data from distributed heterogeneous sensors with other kinds of information systems. On the other hand, the purpose of network interoperability will be the integration between network components, where they must exchange and act on information provided by other components or external networks. Components and networks must share their memory, energy, communication and sensing resources; therefore, dynamic interoperability is needed to perform the communication between the network gateway and users as well as among networks, to exchange messages and to handle the network communication. 4.8
LEGAL INTEROPERABILITY LEVEL
Miller (2000) defines the Intellectual Property rights, the laws or standards supporting information dissemination publicly as aspects of legal interoperability. Kalantari et al. (2006) propose the development of directives, rules, parameters and instructions for the managing business workflow considering information and communication incorporation in the business of land administration. This consideration may be extended or understood in the NSDI context. Onsrud (2004) identifies the most influential areas of law that can affect the use of geographic information as being Intellectual Property, freedom of information, and information privacy of individuals. Zevenbergen et al. (2006) provide a practical example of making legal use conditions more transparent in the design and implementation of a geoportal network in the Netherlands. It is clear that there are insufficient incentives to move towards a wise policy on the conflicts of laws among nations. This may © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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suggest that the need to reconcile competing interests in achieving legal interoperability will become more intense in the near future. However, it is also important to point out that nations’ needs will dictate the appropriateness of the changes in their policies and practices. 5 Interoperability Measures An interoperability measure represents the degree of interoperability that allows knowing the strengths and weaknesses of relationships between systems. Different measures can lead to the improvement of interoperability, as well as help us to avoid deficiencies. A significant research work has already been carried out in this domain ( Hamilton et al. 2004; Janowicz et al. 2008; Kasunic and Anderson 2004; Rodriguez and Egenhofer 2003; Zeigler and Hammonds 2007). However, defining the type of metrics remains a complex research issue, mainly due to the difficulty of identifying the parameters that characterise the type of interoperability level (Daclin et al. 2006, 2008). In fact, interoperability models, together with their respective interoperability levels, require metrics that enable to measure the interoperability degree that is achieved. These metrics can also evaluate GIS interoperability in a quantitatively or qualitatively way (Hamilton et al. 2004). In practice, interoperability measures have been proposed without any consideration of interoperability models and levels. Pridmore and Rumens (1989) relate interoperability measurements with the analysis of system requirements by proposing a metric definition. This metric compute weight scores by representing the degree to which a requirement is met. Basically, they have followed two principles: (i) the identification of parameters relating to interoperability, and (ii) the implementation of these parameters by metrics. As a result, the interoperability measures of a given GIS can be defined by a vector characterised by three types of measurement: (i) interoperability potentiality measurement, (ii) interoperability compatibility measurement, and (iii) interoperability performance measurement. The interoperability measures play an important role in the design of the future GIS in order to evaluate the existence and adequacy of the different levels of interoperability according to the interoperability model being used. The research challenge is twofold: (i) associate current measures to interoperability levels, and (ii) generate new measures for testing that everything is as it should be at a specific interoperability level. A first attempt is described by Zeigler and Hammonds (2007) where measures have been proposed to pragmatic, semantic and syntactic levels based on the LCIM model. However, the lack of specific measures in the GIS domain still remains a research issue, mainly because developing and applying precise interoperability measures in GIS is difficult and has a multifaceted nature (Kasunic and Anderson 2004). Janowicz et al. (2008) © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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has recently proposed a semantic similarity measurement based on the explanation and approximation of similarity values, together with the integration of extended context theories within semantic reference systems. 6 Future Research Challenges There are many aspects of interoperability that can be considered when providing a review of current research issues in a GIS context. We have focussed on three of them; namely, Interoperability Models, Levels and Measures. The main reason is due to the existing shortcomings of current methodologies in the design of interoperable GIS. Therefore, our literature review indicates three potential research topics in interoperability within a GIS context. 1. System of systems interoperability. Assuming that a large set of GIS will be interoperable in the near future, we posit that there is a need to study the complexity of the relationships between interoperability levels of systems of systems, and its impact on the development of the future generation of interoperability models. One example is given by the design of the Global Earth Observation System of Systems that aims to provide decision-support tools to a wide variety of users (2008). As with the Internet, the Global Earth Observation System of Systems will be a global and flexible network of content providers that will require the development of interoperability models to address different purposes of use. 2. The non-hierarchical structure of interoperations. Concerning the existing relationships between the different levels of interoperability, we argue that they are not necessarily hierarchical, as proposed in the above-mentioned review of the literature. Our hypothesis is the existence of different types of relationship – not necessarily only hierarchical – between the different levels of interoperability. As an example, our assumption is that in order to reach the conceptual interoperability, for which the data models and the application schemas are most important, the syntactic and semantic interoperability are necessary, although the pragmatic or dynamic interoperability levels do not appear to be needed. We could find another example in regard to legal issues, such as intellectual property and use constraints. To be able to handle these issues, a syntactic and semantic interoperability is required, but that is not the case for the conceptual, dynamic or pragmatic interoperability. Both examples reveal that the dependency relationships between the levels of interoperability of non-hierarchical nature. 3. The choice of interoperability measures. Any interoperability model scenario should assume the unfeasibility of successfully and globally defining the measures for quantifying or qualifying the relationships across all interoperability levels. More research is needed © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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to define interoperability measures and some integration is needed between a set of measures and different interoperability levels. The implementation of test-beds will play an important role in understanding the dynamic aspects of interoperability measures in a GIS context. Short Biography Monica Wachowicz, after receiving a PhD in Geography from the University of Edinburgh in 1995, worked on spatio-temporal modelling for ubiquitous computing at the Computer Science Department, University of Cambridge, in England, for 2 years. She then took a research fellow position at the Pennsylvania State University before joining the Wageningen University and Research in 1999. She is currently a Visiting Professor at the Technical University of Madrid, Spain. Her research interests are in the areas of geographic knowledge discovery (data mining and information fusion), spatio-temporal data modelling (movement knowledge representation and reasoning) and visual analytics (usability and geo-visualisation). Current research efforts are focussed on the modelling of collective movement behaviour of people. For the past 8 years, she has been working on policy, research and educational issues at European and national levels, aiming to address the needs in spatial planning and environmental management. Working in internationally funded research projects has provided her with the experience of operating in multidisciplinary teams from government, industry, and international organisations. In addition, one of her most rewarding experiences has been in teaching students from different cultural backgrounds and nationalities Miguel-Ángel Manso Callejo is a telecommunications engineer, senior lecturer at the Topographic and Cartographic Engineering Department of the Technical University of Madrid since 1992. Teaching Computer Science, Spatial Data Information Systems and in past time Remote Sensing. Main research topics: Geospatial data automatic metadata extraction, Geoservices: standards and new generation, Spatial Data Information Systems, Historical Digital Maps libraries. Note * Correspondence address: Miguel-Ángel Manso, ETSI en Topografía, Geodesia y Cartografía, Campus Sur UPM, Ctra de Valencia Km 7.5 CP E28031 Madrid, Spain. E-mail:
[email protected].
References Abel, D. (1998). Towards integrated geographical information geoprocessing. International Journal of Geographical Information Science 12, pp. 353–371. Association for Library Collections & Technical Services (2004). Committee on Cataloguing: Description & Access: Task Force on Metadata. Summary Report. [online]. Retrieved on 1 October 2008 from http://www.libraries.psu.edu/tas/jca/ccda/tf-meta3.html © 2009 The Authors Journal Compilation © 2009 Blackwell Publishing Ltd
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Query
43
Author: It seems that ‘SAGA’ is not the correct author here, as it is the abbreviated form of the application. In this case, please supply the name of the institution who developed this. Further, the webpage indicated here cannot be accessed.
44
Author: Please confirm that changes made to Shanzhen et al. 1999 are OK.
45
Author: Please supply publisher’s location of Vckovski 1998.
46
Author: Please supply publisher's location of Zeigler and Hammonds 2007.
Remarks
MARKED PROOF Please correct and return this set Please use the proof correction marks shown below for all alterations and corrections. If you wish to return your proof by fax you should ensure that all amendments are written clearly in dark ink and are made well within the page margins. Instruction to printer Leave unchanged Insert in text the matter indicated in the margin Delete
Textual mark under matter to remain
New matter followed by or through single character, rule or underline or through all characters to be deleted
Substitute character or substitute part of one or more word(s) Change to italics Change to capitals Change to small capitals Change to bold type Change to bold italic Change to lower case Change italic to upright type
under matter to be changed under matter to be changed under matter to be changed under matter to be changed under matter to be changed Encircle matter to be changed (As above)
Change bold to non-bold type
(As above)
Insert ‘superior’ character
through letter or through characters
through character or where required
Insert ‘inferior’ character
(As above)
Insert full stop Insert comma
(As above)
Insert single quotation marks
(As above)
Insert double quotation marks
(As above)
Insert hyphen Start new paragraph No new paragraph
(As above)
Insert or substitute space between characters or words Reduce space between characters or words
or new character or new characters
or under character e.g.
or
over character e.g.
(As above) or
linking
and/or
or or or
Transpose Close up
Marginal mark
characters
through character or where required
between characters or words affected
and/or
