SDI Convergence - Nederlandse Commissie voor Geodesie - KNAW

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3.2 Recommendations for integrating: Base Model Topography We propose an information model topography that integrates the two information models. The modelling principles that we present here are motivated by two important conclusions of the comparison study (section 2). Firstly, two datasets defined in two information models topography are necessary to meet the specific demands of the two domains, i.e. IMGeo for maintenance of public area and TOP10NL for visualisation at scale 1:10k. Secondly TOP10NL cannot be derived from IMGeo, because the application domain proofs to be more dominant on the perception of topography than scale is. Starting from these two conclusions, we propose an intermediate domain model between NEN3610 at the one side and IMGeo and TOP10NL at the other side: Base Model Topography (BMT). The motivation for this intermediate layer instead of solving the integration within NEN3610 is that NEN3610 is meant to integrate at a higher level of abstraction. The two conclusions that direct the modelling principles of BMT are invalid for all domain models under NEN3610. Consequently it is better to solve the integration of these two topographic domains outside NEN3610. BMT is an information model defining scale-independent topographic classes where both IMGeo and TOP10NL can be derived from. The BMT classes respect both the IMGeo and TOP10NL perspectives on topography. However, they do not necessarily have the same label (see further). For the moment BMT defines how concepts in IM- Geo are related to concepts in TOP10NL. This provides consistency for users (and applications) when moving from one dataset to the other. However, the data is still separately collected until an organisation has interest to collect data to serve both domains. In that case the ‘collect once, use many times’ principle will be realised through collecting data on BMT classes. Therefore they contain all information that becomes relevant in any dataset that needs to be derived from BMT. The modelling principles of our approach are based on the multi-scale Information Model TOPography (IMTOP, see Stoter et al., 2008). IMTOP, which integrates topographic data at scales 1:10k to 1:1000k for the Netherlands’ Kadaster, proposes an abstract super class for every topographic class. These super classes have subclasses at all scales and only contain attributes and attribute values valid for all scales. The super classes are abstract and the data is collected for the largest scale dataset, while smaller scale datasets are derived from the next larger scale dataset. Similar to IMTOP, we define IMGeo and TOP10NL classes that are derived classes from BMT classes. An example is shown in Figure 6 where we model the derivation of the PartOfRoad object. Constraints defined in Object Constraint Language (OCL) can define how objects in IMGeo and TOP10NL can be derived from BMT. Although we follow the main principles of IMTOP, the proposed BMT differs on a few fundamental aspects. Firstly, the name of the BMT classes and the derived classes can be different because of different perspectives on concepts (see Figure 7). In contrast, every IMTOP super class occurs as subclass with the same name in each scale. For example the properties of an IMTOP road super class are inherited by road class at 1:10k scale, by road class at 1:50k scale, by road class at scale 1:100k. Secondly, we define association relationships between BMT classes and the derived classes, instead of a generalisation/specialisation relationship as in IMTOP. The reason is that BMT classes and the derived classes do not necessarily represent the same concepts. Thirdly, the BMT classes (comparable to super classes in IMTOP) are non-abstract. The reason for this is that objects in both domains (IMGeo and TOP10NL) are derived from instances of 102
BMT classes, which contain all information required to derive both IMGeo and TOP10NL data. Fourthly, we recommend moving all information down to BMT to avoid extra data acquisition for derived datasets. This implies that all attributes of the IMGeo and TOP10NL objects are derived, except the Identifier and other system attributes not shown in Figure 6. In IMTOP the classes at smaller scales can have extra attributes which are only valid (and collected) for the specific scale. Our BMT approach also slightly differs with the i(integration)-classes as identified in the multi-representation approach of Friis-Christensen and Jensen (2003). The i-classes only contain attributes that are valid in the corresponding classes, as the super classes for IMTOP. Figure 6: Concept of PartofRoad, modelled in integrated model topography. IMGEO::PartOfRoad +/ relativeHeigthLevel: Integer +/ typeOfInfrastructure: TypeOfInfrastructure BMT::PartOfRoad +liesBelow 0..* + numberOfLanes: Integer [0..1] + typeOfRoad: RoadType + roadNumber: CharacterString [0..*] + physicalAppearance: PhysicalAppearanceRoad [0..*] + geometryLine: GM_Curve [0..1] +liesAbove + geometryPoint: GM_Point [0..1] 0..* + geometrySurface: GM_Surface [0..1] + centerPoint: GM_Point [0..1] + separateLanes: Boolean + centerLine: GM_Curve [0..1] + mainTrafficUsage: MainTrafficUsage [0..*] + typeOfRoad: RoadType [1..*] + widthOfPavement: Real [0..1] + isGrouldLevel: Boolean + typeOfPavement: TypeOfPavement +derivedFrom +derivedFrom «FeatureType» TOP10NL::PartOfRoad +/ geometryLine: GM_Curve [0..1] +/ geometryPoint: GM_Point [0..1] +/ geometrySurface: GM_Surface [0..1] +/ centerPoint: GM_Point [0..1] +/ centerLine: GM_Curve [0..1] +/ mainTrafficUsage: MainTrafficUsage [0..*] +/ heightLevel: Integer +/ typeOfRoad: RoadType [1..*] +/ widthOfPavement: Real [0..1] +/ typeOfPavement: TypeOfPavement Finally, we recommend relationships (liesAbove and liesBelow) and the Boolean attribute IsGroundLevel to every BMT class (as shown in Figure 6) to derive both the relativeHeight and heightlevel attributes required for IMGeo respectively TOP10NL. Consequently both the IMGeo and the TOP10NL implementation of topology can be derived from BMT. 103
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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,
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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 and 108: Some differences are not clear from
Page 109: Such homogenous classes will also a
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
Page 159 and 160: 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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