SDI Convergence - Nederlandse Commissie voor Geodesie - KNAW

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Figure 3: IMGeo roads (a) and TOP10NL implementations of roads by Kadaster (b) and municipality of Rotterdam (c). 100 a: Object oriented GBKN (source data for IMGeo) b: Kadaster TOP10NL roads c: Municipal TOP10NL roads Figure 4: Left: Terrain class in current TOP10NL model. Right: Subclasses for different types of Terrain result in homogenised classes. «FeatureType» TOP10NL::Terrain + geometry: GM_Surface + physicalAppearance: PhysicalAppearance [0..*] + heightLevel: Integer + name: CharacterString + typeOfLandUse: TypeOfLandUse «enumeration» TOP10NL:: TypeOfLandUse jetty farmland basalt bl ocks built-up area orchard tree nursery forest: mixed forest grassland sand ... «FeatureType» HarmonizedTOP10NL::Terrain + geometry: GM_Surface + physicalAppearance: PhysicalAppearance [0..*] + heightLevel: Integer + name: CharacterString Jetty Farmland BuiltUpArea Forest Orchard MixedForest Grassland BasaltBlocks TreeNursery Sand
Such homogenous classes will also avoid that different classes are used for the same concepts (section 2.5). Differences in attribute values (section 2.4) can be harmonised through lists of common types completed with harmonised values in case of non-significant differences, for example for the paving types (Figure 5) and railway types. Some values may remain information model specific, example is the built-up area for TOP10NL terrain types which is lacking in IMGeo because buildings cause gaps in the terrain. class HarmonizedPavement «enumeration» nen3610:: Pav ementType open closed paved unpaved unbound pavement Figure 5: Harmonised values for paving types. «enumeration» IMGEO:: Pav ementType closed pavement unpaved open pavement «enumeration» TOP10NL:: Pav ementType partially paved unknown unpaved paved «enumeration» HarmonisedPav ingTypes open pavement closed pavement unpaved unbound pavement unknown The same attribute name for different concepts (section 2.6) can only be harmonised by agreeing on common use of attributes. To avoid such differences in the future, attribute names should be used that have less ambiguous semantics. To solve differences in amount of information (section 2.7), information required at the smallest scale (TOP10NL), but not available in the largest scale (IMGeo) can be either moved down to the largest scale or be removed from the smallest scale. Moving down information to IMGeo is only of interest for municipalities when it is relevant for their application domain. To solve differences in class definitions (section 2.8) new objects at cross sections of classifications could be generated. However, a class for every possible combination makes the models more complex. An example are the four possible combinations for area with plants/forest (IMGeo) and deciduous/coniferous wood (TOP10NL): DeciduousWoodAreawithPlants etc. A better option is therefore to keep the classes from the original models. This will result in overlapping polygons in the datasets, but since two different concepts are registered for the same area (maintenance and land-cover) this reflects the real-world situation. In any case the exact definitions of classes should be unambiguously defined in the information models. In the current situation such differences only become clear when comparing the data (i.e. instances of classes). Harmonising the information models using these recommendations will result in better aligned IMGeo and TOP10NL models. The more harmonisation can be achieved, the more straightforward the integration of the two domain models will be. 101
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SDI Convergence Research, Emerging
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SDI Convergence. Research, Emerging
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An Integrated Framework for the Imp
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Peer Review Board for SDI Convergen
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domain are or may become important
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Services taking advantage of multip
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changes that have taken place in th
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The Potential of a National Atlas a
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tion, the Royal Netherlands Geograp
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challenge for the National Atlas Fo
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experience 'instant satisfaction' u
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data are found offered by the data
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spread of flora and fauna, especial
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Spatial Data Infrastructure of Spai
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ecords managed through the services
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esult of applying GUI production ru
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28 Table 1: Mapping between OGC Cap
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30 Figure 4: Online metadata editio
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ACKNOWLEDGEMENTS This work has been
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Public Sector Geo Web Services: Whi
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Figure 1: Serving geo-information u
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nue. With an increasing number of m
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3.2 Types of business models Malone
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Not all revenue models described by
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uses this model to finance large-sc
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of web service (WMS, WFS/WCS, WIS,
Page 57 and 58: REFERENCES Anderson, C. (2008). Fre
Page 59: INTERVIEWS Jellema, M., DataLand, R
Page 62 and 63: gion, aware of the INSPIRE context,
Page 64 and 65: 3.3 International activities on man
Page 66 and 67: use happens when the final user wil
Page 68 and 69: Geolicences implementation has draw
Page 70 and 71: Spatial Information Council (2008).
Page 72 and 73: make it hard for citizens and civil
Page 74 and 75: 66 Figure 2: Prototype to test navi
Page 76 and 77: ”Member States may limit public a
Page 78 and 79: sor is dragged further into the pro
Page 80 and 81: cause changes in Dutch and regional
Page 82 and 83: Hoekstra, R., Winkels R.G.F. and Hu
Page 84 and 85: The use of location-based informati
Page 86 and 87: tion which does not measure a perso
Page 88 and 89: important role (Dobson and Fisher,
Page 90 and 91: camera surveillance on a public roa
Page 92 and 93: Furthermore, the Court gave a numbe
Page 94 and 95: ECtHR (2003a). Peck v. The United K
Page 97 and 98: Harmonising and Integrating Two Dom
Page 99 and 100: ing and integrating these two domai
Page 101 and 102: Table 1: Differences in background
Page 103 and 104: Figure 1: Examples of IMGeo data (c
Page 105 and 106: Concept Table 4: Same concept, diff
Page 107: Some differences are not clear from
Page 111 and 112: BMT classes, which contain all info
Page 113 and 114: phy, both illustrated with UML exam
Page 115 and 116: An Analysis of Technology Choices f
Page 117 and 118: The objectives of this article are
Page 119 and 120: 3. THE COMPARTIMOS REFERENCE MODEL
Page 121 and 122: sufficiently simple to allow repres
Page 123 and 124: same implementation of a geospatial
Page 125 and 126: 5. RESULTS Through the development
Page 127 and 128: Di L., Chen A., Yang W., Liu Y., We
Page 129 and 130: SDI and Metadata Entry and Updating
Page 131 and 132: A critical problem for metadata col
Page 133 and 134: 2.1.8 Functionalities A MET must al
Page 135 and 136: Collection of related documents Sta
Page 137 and 138: well as more enhanced tools to impr
Page 139 and 140: access to geo-referenced databases,
Page 141 and 142: metadata and spatial data is new an
Page 143 and 144: Phillips, A. and Williamson, I. P.
Page 145 and 146: A Prototype Metadata Tool for Land
Page 147 and 148: data and grid computing infrastruct
Page 149 and 150: model elements it becomes possible
Page 151 and 152: Figure 2: Overview of the system co
Page 153 and 154: 1. selection of a model; 2. provisi
Page 155 and 156: the tool is deployed more widely us
Page 157 and 158: Chan, T., Beverly C., Ebert, S., Ga
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Implementation of Recent Metadata D
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) definition of a metadata organisa
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3.2 Definition of a metadata schema
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This is just an example of how comp
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6. CONCLUSIONS The Public Administr
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An Integrated Framework for the Imp
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2.1 Six Sigma Six Sigma is one of t
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However, the traditional methods of
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The fifth element for BSC design is
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Table 2: Strengths and weaknesses o
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Camp, R. C. (1989). Benchmarking: T
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Nedovic-Budic, Z., Feeney, M.E.F.,
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The Value Chain Approach to Evaluat
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The definition of assessment strate
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There may be several activities per
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The complexity of work, which was r
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Figure 5: Secondary interface: orga
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on investments. More importantly, i
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Porter, M. (1985). Competitive Adva
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Evaluation of Spatial Information T
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fully digital nationwide spatial da
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satellite imagery, digital vector d
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lic) and the National Mapping Agenc
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- Secondary spatial data available,
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Figure 1: Technical progress of SDI
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Khan, J. (2007). Karachi Master Pla
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Philippines http://www.geoinfo.ait.
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Local Government and SDI - Understa
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Australia, like many developed coun
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Table 1: Structure of the LGA quest
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(p
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Table 3: Results of multiple regres
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The role of local government in bui
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McDougall, K., A. Rajabifard and I.
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Changing Notions of a Spatial Data
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Table 1: Differences between GeoWeb
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The concept of spatially enabled go
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applications field and also in term
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The discussion in the fifth section
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Cooperation - a Key Factor for Sust
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appears at low levels and can seek
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Many of the problems of a non-techn
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4.4 Important aspects As cooperatio
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level’ within and between organis
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Seamless SDI Model - Bridging the G
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tuaries and oceans (Plunkett, 2001)
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Figure 2: Seamless administration s
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Figure 5: Seamless platform. A seam
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4.2 Standards SDI must be based on
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One more concern linked to the esta
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structures that not only do not yet
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The RRR Toolbox: a Conceptual Model
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curring in the present must not com
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databases and web mapping services.
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Principles, Institutional Principle
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The commonalities between SDIs and
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Mooney, J. D. and Grant, D. M. (199
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Building SDI Bridges for Catchment
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approaches. TCM is a holistic appro
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hierarchy namely; the umbrella view
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tions and practices in South Africa
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Figure 2: Conceptual framework: App
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In the Murray Darling Basin, there
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REFERENCES Australian Bureau of Sta
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Rajabifard, A., M.-E.F. Feeney and
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SDI Convergence - Nederlandse Commissie voor Geodesie - KNAW

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