SDI Convergence - Global Spatial Data Infrastructure Association

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data and grid computing infrastructures with associated metadata to deliver on-line spatial data processing and modelling. Figure 1 organizes metadata into several simple functional classes and assists in illustrating the conceptual relationships between spatial data, spatial data metadata and the different forms of model metadata. Figure 1: Functional classes of metadata. This approach to describing metadata is slightly unorthodox because it extends the common paradigm that uses metadata largely for purposes of search and discovery. The term metadata, purportedly first used in 1969 (Howe, 1996) is defined as “structured information that describes, explains, locates or otherwise makes it easier to retrieve, use or manage an information resource” (NISO, 2004). A more commonly used definition is that metadata is “data about data”. Here we use ‘model metadata’ as a term or descriptor meaning ‘data about models’. This is not to be confused with the terms meta-modelling and meta-models as these describe a contemporary approach to model selection, construction and assembly (Keller and Dungen, 1999; Bridewell et al., 2006). The NISO (2004) metadata report states “Metadata is key to ensuring that resources will survive and continue to be accessible into the future”. In Agriculture and Natural Resource Management (NRM) this is undoubtedly true for metadata about data and information resources as these are often primary sources of knowledge describing the state and nature of environmental systems and are important for comparative analysis regardless of their age. However, this is probably less so for model metadata as models represent the interpolative, inferential or processing systems that are used in research. These methodologies are generally subject to continual improvement and consequently it could be argued that model metadata has a greater potential to age and is most useful when it is more current. Although there are metadata standards for data and information (ISO 19115) similar standards are only beginning to emerge for model metadata. The functional levels shown in Figure 1 are closely related to three main types of metadata: descriptive metadata, structural metadata and administrative metadata (NISO 2004). At level 1 the metadata is primarily used as a resource for discovery and identi- 139
fication both of data and models. The usage of spatial data metadata for this purpose is a fundamental service within SDI and is in wide use (van der Wel, 2005; Stout et al., 2007; Nogueras-Iso et al., 2005). At this point there are many model registers supporting model search and discovery (i.e., NASA Global Change Master Directory (Website 3), Freebase - Environmental Modelling Collection (Website 4), Catchment Modelling toolkit (Website 5)). At level 2 a deeper description of both information and models is required to assist their utilisation. For data and information in particular this includes metadata describing the genesis, quality and condition of the data resource. In the fields of Agriculture and NRM this metadata is of high importance as data often exists as a collection of data instances that have been produced by a number of projects and initiatives. These are often spread over time and may be subject to an evolving standard or improving collection methods and associated technologies. Unless there has been strong adherence to a data collection standard the specific instances in the collection may differ in subtle ways that can have a profound influence on their utility. At this level these differences are captured in the metadata which is often of a more technical nature. At present this type of metadata does not get much attention in metadata schemas (NIOS, 2004) and can be costly to collect. An exception is the emerging Numerical Model Metadata standard associated with climate modelling (Steenman-Clark et al., 2004). Stout et al. (2007) provide an example where the US Federal Geographic Data Committee (FGDC) metadata standard is being extended to support some of this type of metadata. At level 2 the use paradigm for model metadata is changed. Rather than generally describing the model itself emphasis is placed on storing contextual information about the modelling activity and how to implement. To support effective model use not only are technical descriptions of the inputs and description of how to execute the model important but understanding where and who implemented the model is extremely useful. This can benefit to prevent duplication in modelling effort. In contrast to level 1 there are not many tools that effectively address and use model metadata at this level. Most approaches to date are associated with theme based modelling groups and a good example is the ‘Earth System Curator’ and its prototype database used by climate modellers. In this context the record of model activity is confined to the community of interest. This prototype has the stated objective to “store metadata related to model runs and datasets” but is still under development. The authors have not yet found published model metadata systems recording details of model instances spatially (other than the MIKE system described herein). Practical support for this function requires user-friendly and efficient approaches to the spatial registration of these instances. At level 2 there are opportunities to link model and data metadata repositories (for those models with stable or fixed data inputs) and support queries informing understanding of spatial data availability for modelling. These approaches require a common referencing scheme for datasets in both registers. This is a key component within the case study described in the following section. At the third level the emphasis for metadata shifts to record details that can support associated processes both for models and data. In the data area examples include metadata to support publication and transformation of data such as in web based mapping or even workflows associated with data such as managing collection by third parties (Stout et al., 2007). In relation to models this metadata serves as a base to underpin applications for automated model processing or pre-processing of data for models. Current development in this area is largely confined to process models in remotely sensed data (Jianto et al., 2003) or in climate modelling. The development of metadata in this area is a crucial part of an SDI to support automated publication of data and models. Where the metadata is extended to store processing instructions, algorithms or 140
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GSDI Global Spatial Data Infrastruc
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SDI Convergence Research, Emerging
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Table of Contents Foreword vii Peer
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Foreword This book is the result of
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Spatial Data Infrastructure Converg
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SDIs are not for free, and thus nee
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gional level specific and complete
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management issues. They do not foll
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esses (scenario 5b in Figure 1) req
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implements the SDI concept. INSPIRE
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cluded. Map functions refer to pop-
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The toolbar at the top of the map a
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18 Figure 5: Technical implementati
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Development and Deployment of a Ser
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the development of the services off
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Web Applications Services Aplicatio
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Figure 2: ISO 19119 elements for se
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means of their capabilities informa
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- Column Nr_dc (and its associated
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Nebert D., Whiteside A. and P. Vret
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of the four essential parts of a su
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2.1.2 ICT standards web services Fo
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model (see Figure 3). The four comp
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4. FINANCIAL MODELS 4.1 Cost models
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5. Hybrid models: These are models
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4.4 Price strategies Apart from the
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6. CONCLUSIONS AND RECOMMENDATIONS
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MICUS Management Consulting GmbH (2
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Standard Licences for Geographic In
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3. PHASE I: EUROPEAN CONTEXT AND AC
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The reuse of public sector informat
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(c) free copies or privileged acces
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The ‘Guidelines on the use of geo
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Legal Simcity; Legislative Maps and
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Figure 1: Result set showing protec
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Figure 3: Detailed text-to-map retr
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(Simple Knowledge Organization Syst
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Legal Atlas approach, except for pe
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Furthermore, we pointed out that th
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Power and Privacy: the Use of LBS i
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for these needs by increasing the q
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TARGET [citizen(s)] 3.2.2 Citizens
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tionship with the citizen-subject.
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4.4 European case law 4.4.1 Rotaru
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Without prejudice to the general da
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Taylor, J.A., A.M.B. Lips and J. Or
Page 99 and 100: these datasets. Afflerbach et al. (
Page 101 and 102: gration can be realised. This secti
Page 103 and 104: 94 Table 2: Main classes in NEN3610
Page 105 and 106: 96 Table 3: Slightly different attr
Page 107 and 108: grassy area in TOP10NL data (right)
Page 109 and 110: Figure 3: IMGeo roads (a) and TOP10
Page 111 and 112: 3.2 Recommendations for integrating
Page 113 and 114: Figure 7: Modelling sport area as B
Page 115 and 116: Stoter, J.E., Morales, J.M., Lemmen
Page 117 and 118: SDI. This evaluation, as well as an
Page 119 and 120: ConsultCo now executes their geocod
Page 121 and 122: 4.1 The Catalogue 112 Figure 2: Obj
Page 123 and 124: 114 Figure 3: The address data cata
Page 125 and 126: multiple data services or resources
Page 127 and 128: 6. CONCLUSION We presented a scenar
Page 129 and 130: OGC OGF (2007). Memorandum of Under
Page 131 and 132: the identification, the extent, the
Page 133 and 134: integration of metadata and spatial
Page 135 and 136: 126 Category Criteria Technical Sta
Page 137 and 138: cords as required. The application
Page 139 and 140: element in the metadata record. Thi
Page 141 and 142: 132 Category Criteria Technical Sta
Page 143 and 144: MET designers should focus greatly
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Page 147: lative effects of activities on the
Page 151 and 152: study described in the next section
Page 153 and 154: tionality. Themes are ‘map view
Page 155 and 156: 146 Figure 5: Registration screen f
Page 157 and 158: As the research progresses more fee
Page 159 and 160: Pettit, C., W. Cartwright, I. D. Bi
Page 161 and 162: Over the last few years, important
Page 163 and 164: - the Regional Topographic Database
Page 165 and 166: - the attributes of each of these t
Page 167 and 168: 5. METADATA MANAGER For metadata cr
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Page 171 and 172: In the business management literatu
Page 173 and 174: To use this strategy, effective con
Page 175 and 176: whether the financial support is fr
Page 177 and 178: pation and control of their own qua
Page 179 and 180: With respect to this description, t
Page 181 and 182: Huarng, F. and Y.T. Chen (2002). Re
Page 183 and 184: 174
Page 185 and 186: (GPS) devices have changed the natu
Page 187 and 188: equired to know which properties th
Page 189 and 190: The first phase of the EcoGeo Proje
Page 191 and 192: Adding a ne w organisation in the p
Page 193 and 194: 6. CONCLUSIONS AND FUTURE WORK The
Page 195 and 196: Goodchild, M. (1995). “Geographic
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2. APPLICATION OF SPATIAL INFORMATI
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a set of simple tools and applicati
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Russia is just at the beginning in
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to explore appropriate services for
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Nevertheless it can be stated that,
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REFERENCES Abdulharis, R., van Loen
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Brazil http://www.gisdevelopment.ne
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204
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vertical integration of multiple le
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went from being “nice to have”
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Approximately 59% of LGAs indicated
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Variables 212 Table 2: Variables th
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5. DISCUSSION AND IMPLICATIONS FOR
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Giff, G. (2006). "The value of perf
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Warnest, M., A. Rajabifard and I.P.
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programme. Nevertheless the term 'S
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This distinction is also reflected
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several decades or more. In essence
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to play a larger part in the develo
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Masser, I. (2005). GIS Worlds: crea
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Studies of cooperation as a subject
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232 Figure 1: The ‘SDI-based netw
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Questions of SDI are strongly integ
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This leads to the conclusion that w
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Brunsson, N. (2006). The organizati
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However, current SDI design focuses
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242 Figure 1: Marine and coastal ma
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244 Figure 3: Issues and challenges
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emerged in response to a global rea
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The OGC/TC 211 implementation speci
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Results from European Spatial Data
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Nebert , D.D. (ed.) (2004). Develop
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The article begins by outlining the
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4. INITIAL RESPONSES TO THE RRRs CH
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cluded a qualitative and quantitati
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As an example the ‘Spatial and Te
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Dale, P., and McLaughlin, J.D. (198
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Van Oosterom, P.J.M., Lemmen, C.H.J
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each stakeholder can access, use, a
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elow (Rajabifard et al., 2003a). Ho
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3.3 Evolution Theory and SDI Evolut
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spread of a new idea from its sourc
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institutional complexities. This is
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with existing institutional arrange
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Hofstede, G. and G.J. Hofstede (200
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