Awan egov01 journal 20100717b

Architectural Model of Spatially Enabled E-Government in Indonesia Adhiawan Soegiharto1, Dana Indra Sensuse2 1,2 Magister Teknologi Informasi, Fakultas Ilmu Komputer, Universitas Indonesia Gedung Pusat Ilmu Komputer Universitas Indonesia Jl. Salemba Raya No. 4, Jakarta Pusat, Indonesia [email protected] [email protected] Abstract— Data and spatial information has been recognised as an important element in decision making. The high cost of spatial data procurement can become an obstacle in accessing spatial information, so that the spatial data held by certain institutions cannot be shared by other institutions that may need it. To overcome this problem, national government has issued policies on the dissemination of spatial data. This policy appoints several agencies to act as nodes and node connectors of a National Spatial Data Network. However, within this policy there is no reference to the architecture that is required to build an egovernment which can support the use of spatial data for decision making. To build such an architectural model, identification and observation is required in every relevant Indonesian institution designated as nodes and connecting node in the National Spatial Data Network. To establish current best practice, a critical observation and comparative review will be completed of e-government architecture models in other spatially enabled countries. The results of this identification and observation become the basis for the design of an appropriate architectural model. Architectural models thus formed can provide a reference for agencies in Indonesia. Such a reference is expected to facilitate institutions in building the information technology architecture that can enable them to efficiency and effectively make best use of spatial data. Keywords— e-government, e-government architecture, spatial information, data integration, core diagram I. BACKGROUND AND MOTIVATION E-government initiatives in Indonesia began in the early 2000s and confirmed by the issuance of Presidential Instruction (Inpres) No. 6 year 2001 on Telematics. This Presidential Directive states that government officials should use telematics technology to support good governance. The Initiative is expanding so that the government issued Presidential Instruction No. 3 year 2003 on e-government development policy. E-government development, in addition to improving the quality of service to the community, also improves the quality of data and information provided through the service. Data and information can be used as a basis for decision making, both by businesses, the public, or other government institutions. According to the survey results on Spatial Enablement of government in Australia by Geoscience Australia in 2007, ‘the use of spatial information will improve the quality of decision making, reduce administrative costs, improve the quality of the governmental activities, and improve opportunities for industrial development. However, this requires the availability of spatial data and its access that is well maintained to be used by most of spatially unaware people’ [46]. Government that provides extensive spatial information is referred as a spatially enabled government. From the initial literature study, the authors conclude that if spatial elements are embedded in e-government, then the awareness of the use and dissemination of spatial data and information is expected to start rising. This is due to the purpose and nature of e-government itself, which provides access information to the public in a simple and accessible form. This public awareness will lead to increased community interest in obtaining access to spatial information. The high public interest is expected to increase the awareness of government institutions in the larger benefits of wider spatial data and information dissemination and sharing. II. PROBLEM STATEMENT Government regulations on the establishment of the ministries (UU No. 39 year 2008) states that each function of governance may not be done by only a particular institution or ministry. Governance functions which are performed by several institutions led to the emergence of several programs which will use similar data and information. About 80 percent of them contain elements of spatial information [38]. Currently, in Indonesia, the use of spatial data and information, both by public and government institutions, is still very small. The expensive provision of spatial data is one of the main reasons. Currently, each sub-directorate, which launched a program almost always procure their own spatial data. Procurement of spatial data is usually a significant cost of financing the overall program. The high cost provision of spatial data causes each institution to store spatial data for their own. This causes the provision of the same spatial data at different institutions. Multiple procurements cause higher procurement costs for the same spatial data for the government as a whole. Other impacts that occur are the lack of awareness that spatial data use can become widespread, due to the tendency of not sharing data. Data sharing has been recognized to be the solution to the expensive spatial data procurement. To facilitate the dissemination of spatial data, the Government of Indonesia has established the NSDI (National Spatial Data Infrastructure/Infrastruktur Data Spasial Nasional – IDSN). Spatial data infrastructures are the key to the formation of a spatially enabled government [37]. This implementation is followed by the release of Presidential Regulation (Perpres) No. 85/2007 regarding the NDSN (National Spatial Data Network/Jaringan Data Spasial Nasional – JDSN). E-Government architectural models that support spatial enablement assist institutions in building e-government architecture which in turn means that institutions become spatially enabled and, at the same time, take advantage of spatial data infrastructure available. Because such reference model architecture supports e-government usage does not exist yet in Indonesia, the research question to be answered by this thesis is "what is the architectural model for spatially enabled e-government in Indonesia." III. LITERATURE STUDY Literature review conducted on the documents of institutions establishment, the journals, articles, and reference books on spatially enabled government, e-government, spatial information, spatial data integration, current geospatial technologies, enterprise architecture, and related studies that have been done in the field of e-government. In Indonesia, there are 4 types of institutions; the State Supreme Agencies, Ministry, Ministerial Level of Government Institutions and Non-Departmental Government Institutions (Lembaga Pemerintah Non Departemen – LPND). Of the four types of them, there are 2 types of institutions designated to become the nodes and node connector in the National Spatial Data Network (NDSN/JDSN), the ministry and LPND. These institutions were established to carry out the functions of governance as in the regulation. Each of the governance functions are described in detail in the Document of e-Government Blue Print Design issued by the Ministry of Communications and Informatics (Kemenkominfo). Rajabifard states that a government or society is said to be spatially enabled when spatial information has been widely available for the community and spatial information are widely used by consumers as the use of non-spatial information. In developed countries, the use of spatial information has now become a common part of the egovernment and broader government ICT strategy [46]. Müller estimates that about 80% of data in the process of governance institutions is a spatial data or data that relate to spatial data, so the establishment of spatial data infrastructure becoming a very important part of the processes that exist in e-government [38]. A. Interoperability Interoperability is a crucial issue in the formation of this spatially enabled government. One of the objectives of the establishment of NSDI is to address this issue. Sukyadi has constructed a model of e-Government interoperability [57], but it has not considering the spatial dimension. Other researches on spatial data interoperability were conducted by Zhang et.al [69], Huang et.al [19], and Zheng et.al [70] on web service interoperability model. These researches show a positive result on implementation of Open Geospatial Consortium (OGC) standards as interoperability model. From the perspective of interoperability on spatially enabled egovernment, the research by Sukyadi (e-government) and other four researches above are complementing each other. The interoperability models from those five researches became matters of literature study to form an integration model in enterprise architecture of e-government. B. Spatial Data Infrastructure SDI (Spatial Data Infrastructure) is a collection of technologies, policies and institutional arrangements that facilitate access availability to spatial data [46]. Rajabifard states that the spatial data infrastructure is the key to the establishment of a spatially enabled government [47]. In Indonesia, the NSDI was formed as a consortium of concerned institutions for spatial data. This consortium is coordinated by Bakosurtanal as government institution that serves as the coordinator of the survey and mapping. The NSDI consists of 3 components: institutional, legislation, and primary data. One of NSDI results is the emergence of Perpres No. 85/2007 regarding the NSDN (National Spatial Data Network). C. National Spatial Data Network To prevent the procurement of the same spatial data collection, the Government of Indonesia (GoI) has issued Perpres No. 85/2007 regarding the NSDN. This regulation states that NDSN administered through an electronic media (i.e. Internet) and serves as a means of exchange and dissemination of spatial data. This regulation specifies which parties are given the responsibility as a Node and Node Connector of NDSN. Mesh networks consist of government institutions, departmental and non-departmental, provincial, and municipal/district. Network Node Connector played by the Coordination Agency for Surveys and Mapping (Bakosurtanal). The table below shows the institutions included in NDSN. TABLE I AGENCIES IN NDSN No. Government Sector Agency 1 2 3 4 5 6 Survey and mapping Land administration Internal affairs Bakosurtanal (Badan Koordinasi Survei dan Pemetaan Nasional) BPN (Badan Pertanahan Nasional) Kemendagri (Kementerian Dalam Negeri) Transportation Kemenhub (Kementerian Perhubungan) Communication and Kemenkominfo (Kementerian informatics Komunikasi dan Informatika) Public works Kementerian PU (Pekerjaan Umum) No. Government Sector Agency 7 Culture and tourism 8 9 Statistics Energy and mineral resources Forestry Agriculture Marine and fisheries Meteorology and geophysics Space and aeronautics 10 11 12 13 14 Kemenbudpar (Kementerian Kebudayaan dan Pariwisata) BPS (Badan Pusat Statistik) Kementerian ESDM (Energi dan Sumber Daya Mineral) Kemenhut (Kementerian Kehutanan) Kementan (Kementerian Pertanian) KKP (Kementerian Kelautan dan Perikanan) BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) Lapan (Lembaga Antariksa dan Penerbangan Nasional) There are 44 types of spatial data, which is mentioned in NDSN regulation, which must be produced by institutions that have been designated as a nodes and node connector of the NDSN. Spatial data production process will become the basis for building spatial information model of each institution in NDSN. The NDSN regulation clearly states that NDSN must be held through an electronic-based information network. This assumes technologies that utilize the Internet as a medium of exchange of spatial data. Reviews of this technology include the standards of publication, representation, processing, and production of spatial data. Internet Map Server is one of the most common technologies in use today which has implemented this standard. For the processing and production of spatial data, GIS desktop applications remain a top choice so far, because this application provides much more complete spatial features than the web-based mapping applications. Although it’s desktop-based, the current applications of GIS has been able to connect spatial database through the Internet with the same communication standard used by web mapping. To show a simple/generic form of a spatially enabled egovernment architecture, the authors adopt Ross core diagram [40]. A core diagram provides main points in the enterprise architecture to be a reference for the responsible management in developing and utilizing this architecture [40]. The management in this case is the Government of Indonesia. This diagram is expected to facilitate the government in the overall view of the architecture. IV. FRAMEWORK AND METHODOLOGY From the literature study, the author develops a framework which is adopted from Ross core diagram forming process. The framework is shown by the following figure. FIG. 1 ARCHITECTURE DESIGN FRAMEWORK Model design proceeded in three phases, namely the identification, creation of core diagrams, and testing. Model design steps are as follows: 1) Identification of operating model: Performed to get the most suitable operating model that needed to adopt by government agencies to be spatially enabled. 2) Identification of key customers: Conducted to see which parties are to be clients for government agencies. 3) Identification of business model: Performed to obtain any data/information related to business processes (governmental function) in this case. 4) Identification of information model: Results of business model identification is then processed in this activity to find what data/information that must be shared or disseminated, and which governmental function that can be linked. 5) Identification of application and technology model: This activity is performed to get the right technology to integrate the spatial information. 6) Core diagram design: Core diagram is formed on the basis of all the result from above 5 steps. 7) Model testing: Performed by expert panel method. The reference documents in the above activities are UU No. 39/2008 on Ministry, Keppres No. 103/2001 on Non Ministerial Government Agencies, Perpres No. 85/2007 on NDSN, Document of E-Government Blue Print Plan by Kemenkominfo, and medium term development plan (RPJMN) 2010-2014 by Bappenas. To form the core diagram, the references above are combined with the literature study on the most current architecture of applications that are already implemented OGC standards. V. DISCUSSION The model will be designed in accordance with the framework mentioned above. A. Operating Model From the study of operating model, the authors found that in Indonesia case, the agency can simply choose coordination operating model to prepare the spatial enablement. There are three points to be considered: a) Noting the influence of the data produced by institutions with the interests of other institutions, while maintaining its own business processes; b) Following the data standardisation that has been established by the NSDI; only spatial data related that need to follow this standardisation; c) IT architecture and/or infrastructure related decision making are taken at institutional level. Implementation and technology selection can be decided by the units under it, as long as spatial data related technologies are referring to NSDI. C. Information Model Identification information model is performed by map the outputs with basic needs of spatial information in each of the agency in NDSN. The result is then summarised to see the overall relationship between the functional classifications of spatial data with the institutions concerned. This summary is shown in the matrix below. LAPAN BMG KKP Kementan Kemenhut Kementerian ESDM BPS Kemenbudpar Kementerian PU Kemenkominfo Kemenhub Kemendagri BPN Bakosurtanal B. Business Model The business model in government case is indicated by its services. Service model is formed by mapping the governance functions (which exist in the governmental functional system framework) with the institutions mentioned in NSDN. The output of this analysis then summarised to a table, then mapped to a matrix of institution vs. functional block as a service model. d) Though performed by all institutions, the function of information publication and government service is not related to other institutions because the information is only related to each institution itself. Although focused on the function of National Development, but on the core diagram to be constructed, the seven governance function will be listed. Governance functions 1, 4, and 5 will be listed on the first level only, while the functions of governance 2, 3, 6, and 7 will be listed until the first sub-levels. 1. Institutional Support & Services 2. Politics & Legislation 3. Defense & Security 4. Laws, Regulations, & Legislation 6. National Development 5. Monetary & Fiscal 6.1 Governance 6.2 Zoning 6.3 Social 6.4 Facilities & Infrastructures 7. Information Publication & Government Services FIG. 2 SUMMARISED OF SERVICE MODEL MATRIX OF INSTITUTIONS IN NDSN The shaded part in the matrix above shows: a) Governance function that is performed by the agency in its column above. b) That governance function is coordinate by the agency in its column above. c) Other agencies that may perform the same function have to refer to the procedure or standards set by the agency in its column above. The matrix above will be used in the mapping process between service model and information model, which is focused on function of national development. The considerations to choose it are: a) The function of institutional support and service is an internal function of each institution. Therefore, no inter-institutions relationship patterns are identified in this function. b) The function of politics and legislation and the function of defence and security, from the scope of this thesis (NDSN), are only performed by Kemendagri. c) There is no institution mentioned in the NDSN regulation that is performed function of laws, regulations, and legislations, and the function of national monetary and fiscal. FIG. 3 AGENCY IN NDSN OUTPUT AND SPATIAL INFORMATION NEEDS D. Integration Model Web-based technology is chosen as integration technology with the use of Internet Map Service. Integration model adopted from the model of application architecture, webmapping applications that have implemented OGC standards. Models of spatial data integration for publication can be seen in Fig. 4. Production, processing, and management of spatial data perform by using desktop GIS applications. For spatial data management, web-mapping applications can be used, but today, tools for production and processing spatial data in desktop applications are still have much more complete features than in web-mapping applications. Features of spatial analysis on a desktop application are also more sophisticated than web-mapping. files. All spatial data that has been connected is processed, analysed, and/or combined to produce a new spatial data. Cleaning process at each connected spatial data topology must be done before performing spatial analysis. RS applications or extensions are used to perform data mining process in raster files of satellite imageries or aerial photos. This process results are vectors that can be processed or analysed further by GIS application. The final output is then stored into a spatial data warehouse. Spatial data stored in a data warehouse are (has to be) already topologically clean. This would be very useful for other institutions that will use this spatial data, because it will reduce time of topology cleaning significantly. Both integration models above are then combined to form an overall integration model (Fig. 6). Agencies producing spatial data will access spatial data required via database connection. It is strongly recommended to use the Internet channels with specific security levels that can only be accessed by government agencies. FIG. 6 INTEGRATION MODEL OF SPATIAL INFORMATION FIG. 4 INTEGRATION MODEL IN SPATIAL DATA PUBLICATION In data integration, these desktop GIS applications use the same communication standard with a web-mapping, which uses OGC standards. Figure below shows the model of integration of spatial data through desktop GIS applications. E. Architectural Model of E-Government In accordance with literature studies on Ross core diagram, the analysis then mapped onto the core diagram forming process. The mapping can be seen in the following table. TABLE II MAPPING OF ANALYSIS RESULTS WITH CORE DIAGRAM Process Shared customers Shared data Integrating technologies Linked processes Analysis Result Public, business, and other government institutions. All spatial data mentioned in NDSN regulation. The use of Internet Map Service and GIS applications which are already implemented OGC standards. Governance function in governmental functional framework. From the analysis of each of the above process, the egovernment architecture formed as shown in the Fig. 7 below. FIG. 5 INTEGRATION MODEL IN SPATIAL DATA PRODUCTION Through the database connection layer, GIS application connects to al required spatial data, vector files, and raster ministry itself, or in other agencies. Referring to the role of Kementerian PU in the national development function, the spatial data are used to make decisions related to the function of 6.1 governance, 6.2 zoning, and 6.4 facilities and infrastructure. G. Proposed Solution Proposed implementation of solutions on the institutions integration model of spatial data are mapped in Fig. 9 as follow. FIG. 7 E-GOVERNMENT CORE DIAGRAM As shown in the core diagram, there are 2 main layers, the interface layer, and system layer. Interface layer is the layer that connects between the systems with potential data users (in this case, the general public, businesses, and government institutions). Interface layer is separated into two types to differentiate its services, to the general public and business community, and to government institutions. Layer consists of database systems, spatial database, data processing applications, and integration. XML, GML and SVG primarily are the choice of technology for this integration. F. Sample Implementation The authors make an example of architecture implementation if applied in Ministry of Public Works (Kementerian PU). Kementerian PU produces six types of spatial data using nine types of base spatial data in four different agencies. This example is shown in the Fig. 8 below. FIG. 9 MAPPING OF PROPOSED SOLUTION As seen on the proposed implementation above, there are two important parts on the integration model. The first part (1) is a production process which includes GIS (overlay, spatial analysis, network analysis) and RS (georeferencing, image classification, digitisation). This production process can retrieve data from a local database (4) and the end result is stored into a spatial data warehouse (3). The second part (2) covers the process of publication; publication is only performed on spatial data stored in spatial data warehouse (3). FIG. 8 SAMPLE IMPLEMENTATION IN KEMENTERIAN PU The six types of spatial data in the spatial data warehouse (1) are the result of analysis using GIS and/or RS (2). Analysis is performed on base data/base map from other agencies (3) which then overlaid with some spatial data (4) or additional rasters (6). If necessary, the result then stored to a local database (5) so then it can be analysed further before generating the final spatial data which then stored to spatial data warehouse (1). Data that has been stored in a data warehouse can then be used by other institutions (8) to produce the required spatial data. Spatial data in a data warehouse are then published through the IMS (7) for use by decision-makers (9) either within the FIG. 10 SAMPLE SOLUTION FOR SPATIAL DATA PRODUCTION 1) Sample solution for spatial data production: There are three activities in the production process spatial data, namely topology cleaning, image processing, and GIS processing. An example of the proposed solution is shown in Fig. 10. Other solution examples for the production of spatial data can be seen in Table III below. This table also contains some proprietary solutions, apart from open source solutions. TABLE III SAMPLE SOLUTION FOR DATA SPATIAL PRODUCTION Sample Solution Open Source GRASS GIS grass.itc.it OSSIM www.ossim.org Quantum GIS www.qgis.org Ilwis www.ilwis.org Proprietary ArcGIS www.esri.com Erdas Imagine www.erdas.com Idrisi www.clarklabs.org Manifold www.manifold.net GeoMedia www.intergraph.com Topology Image Cleaning Processing TABLE IV SAMPLE SOLUTION FOR SPATIAL DATA PUBLICATION GIS Processing ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ 2) Sample solution for spatial data publication: There are three layers in the publication of spatial data, the server layer, application layer, and web servers, as seen in Fig. 11. Sample Solution Open Source MapGuide Open Source mapguide.osgeo.org MapServer mapserver.org GeoServer geoserver.org OpenLayers openlayers.org CartoWeb www.cartoweb.org Apache httpd.apache.org GeoNetwork sourceforge.net/projec ts/geonetwork/ Proprietary ArcGIS Server www.esri.com Manifold IMS www.manifold.net/inf o/ims.shtml GeoMedia WebMap www.intergraph.com IIS (Windows Server) www.microsoft.com/se rvers Map Application/ Web Map Map Server Framework Server Viewer Catalog ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ 3) Sample solution for database and data warehouse: Currently, open source databases have not been able to use as a data warehouse because, currently, the maximum data size that is accommodated by open source solutions is 4 Gigabyte. Data warehouse, especially for storing spatial data, should be able to accommodate larger data sizes, with no size limit. TABLE V SAMPLE SOLUTION FOR DATABASE AND DATA WAREHOUSE Sample Solution FIG. 11 SAMPLE SOLUTION FOR SPATIAL DATA PUBLICATION Other solution examples for the production of spatial data can be seen in the following Table IV. This table also contains some proprietary solutions, apart from open source solutions. Open Source Postgres+PostGIS www.postgresql.org postgis.refractions.net MySQL Spatial www.mysql.com Proprietary Postgres Plus www.enterprisedb.com Oracle Spatial www.oracle.com Cubewerx CubeSTOR www.cubewerx.com Spatial Database Spatial Data Warehouse ■ ■ ■ ■ ■ ■ ■ ■ H. Implication of Architecture Implementation There are several implications of the adoption of this spatially enabled e-government architecture. 1) Management: To ensure the integration of spatial data in the architectural model in this thesis, the government should establish a policy to choose a georeference standard for all agencies in Indonesia. On the other hand, the application of spatial data warehouse means necessary enforcement of SOPs from every production process in the use of spatial data and data cleaning. 2) System: Open source applications for GIS and web mapping is now approaching features of proprietary applications, so the cost of purchasing and updating applications can be suppressed. Because the integration of the proposed architecture is built upon the network (Internet), then the government needs to establish a special channel of data communication between agencies. This data communication lines can be a WAN or MAN. Implementation of spatial data warehouse will minimise data inconsistency. 3) Academic perspective: From the academic side, the implications of the adoption of e-government architecture which spatially enabled in this thesis are:  Study on the implementation of this spatially enabled architecture at agencies that have not been included in NDSN.  Research on ICT governance for the implementation of architecture that is spatially enabled.  Research on the communication security between agencies in the implementation of this architecture.  Study on spatial data acquisition speed improvement for decision making on the implementation of the architecture.  Study on the improvement in term of speed and accuracy of interventions for the decision based on the use of spatial data. c) Government and the agencies producing spatial data need to assess the utilization of open source applications, both on the production and publication processes. d) Government should consider the establishment of the government service provider to provide electronic channels (Internet) for communication between government agencies, to ensure the security and speed of delivery and exchange of information, especially spatial information. e) Each agency needs to ensure the implementation of spatial data warehouse concept, to maintain the validity of data. C. Further Research Conduct further research or study on: a) The implementation of this spatially enabled architecture on other agencies that are not yet designated as NSDN nodes; b) The proper ICT governance for the implementation of a spatially enabled architecture; c) Security factor in communication channel (Internet) between agencies to accommodate the integration in this spatially enabled architecture; d) The increase of speed in spatial data acquisition for decision making on the implementation of the architecture; e) The speed and accuracy of intervention upon the decision based on the use of spatial data. VII. [1] [2] VI. CONCLUSION AND SUGGESTION A. Conclusion 1) Model of data spatial integration: Can be done by implementing the OGC standards, whether for publication or for the production and processing. 2) Open source applications: Already have a fairly complete feature in the publication of spatial data, while for the production, processing, and spatial data management, use of open source applications still need to be combined with the use of proprietary applications. 3) Result of expert panel: The proposed architectural model has been considered to be a national benchmark or reference for the development of spatially enabled egovernment. B. Suggestion a) The government should issue a policy to choose a georeference standard for all agencies in Indonesia that produce spatial data. b) Each agency shall issue, enforce, and supervise the implementation of the SOP on spatial data production processes. [3] [4] [5] [6] [7] [8] [9] [10] BIBLIOGRAPHY John W. Barnes and Richard J. Lisle, Basic Geological Mapping, 4th ed. England: John Wiley & Sons Ltd, 2004. Karin Berkhoff and Sylvia Herrmann, "Modeling Land Use Change: A GIS Based Modeling Framework to Support Integrated Land Use Planning (NabanFrame)," in Advances in GIScience, Monika Sester, Lars Bernard, and Volker Paelke, Eds.: Springer-Verlag Berlin Heidelberg, 2009. Rick Bradford and Daniel Vincent, "Development of Temporal Mapping Techniques to Support Urban Retrospectives Database," US Geological Survey, 1998. Günay Çakir, Fatih Sivrikaya, Salih Terzioğlu, and Emin Zeki Başkent, "Mapping Secondary Forest Succession with Geographic Information Systems: A Case Study from Bulanıkdere, Kırklareli, Turkey," Turkish Journal of Agriculture and Forestry, vol. 31, pp. 71-81, February 2007. Daniel M. Campbell, Local Government Handbook for GIS Implementation Within the Commonwealth of Pennsylvania.: Pennsylvania Mapping and Geographic Information Consortium (PaMAGIC), 2002. Commonwealth Cultural Resources Group, Inc., "Minnesota Deep Test Protocol Project," Minnesota Department of Transportation, Jackson, 2006. Leslie M. Cone, "Explaining the National Integrated Land System (NILS)," U.S. Bureau of Land Management, 2008. Michele Crosetto and Paolo Pasquali, "DSM Generation and Deformation Measurement from SAR Data," in Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences: 2008 ISPRS Congress Book, Zhilin Li, Jun Chen, and Emmanuel Baltsavias, Eds. London: Taylor & Francis Group, 2008. Christopher Daly, E. H. Helmer, and Maya Quińones, "Mapping the Climate of Puerto Rico, Vieques and Culebra," International Journal of Climatology, vol. 23, pp. 1359-1381, August 2003. Rolf A. de By et al., Principles of Geographic Information Systems, 3rd ed., Rolf A. de By, Ed. Enschede, The Netherlands: The International Institute for Geo-Information Science and Earth Observation (ITC), 2004. [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] Direktorat E-Government, Direktorat Jenderal Aplikasi Telematika, Rancangan Blue Print E-Government. Jakarta, Indonesia: Kementerian Komunikasi dan Informatika, 2006. R.J.J. Dost and C.M.M. Mannaerts, "Generation of Lake Bathymetry Using Sonar, Satellite Imagery, and GIS," in ESRI Users Group Conference, 2009. Ralph Dubayah, Robert Knox, Michelle Hofton, J. Bryan Blair, and Jason Drake, "Land Surface Characterization Using Lidar Remote Sensing," in Spatial Information for Land Use Management, Michael J. Hill and Richard J. Aspinall, Eds., 2000. W. E. Featherstone, "On the Use of the Geoid in Geophysics: A Case Study Over the North-West Shelf of Australia," Exploration Geophysics, vol. 28, no. 1, pp. 52-57, 1997. FGDC, Geographic Information Framework Data Content Standard Part 4: Geodetic Control.: Federal Geographic Data Committee (FGDC), 2008. Witold Fraczek, "Mean Seal Level, GPS, and the Geoid," ArcUser, pp. 36-41, September 2003. Maria Grazia Fugini, "A Security Model and Architecture for Multichannel E-Government Systems," in Second International Conference on Availability, Reliability and Security, ARES, Vienna, 2007. Guangping He and Greg Orvets, "Capturing Road Network Data Using Mobile Mapping Technology," International Archives of Photogrammetry and Remote Sensing, vol. XXXIII, 2000. Fang Huang, Dingsheng Liu, Guoqing Li, and Jian Wang, "Preliminary Study on the Application of OGC Interoperability Specifications in Spatial Information Grid," in International Conference on New Trends in Information and Service Science, NISS. , Beijing, 2009, pp. 515520. International Association of Assessing Officers, Standard on Manual Cadastral Maps and Parcel Identifiers. Chicago: International Association of Assessing Officers, 2004. Noritoshi Kamagata et al., "A New Method of Vegetation Mapping by Object-based Classification Using High Resolution Satellite Data," in International Conference on Object-based Image Analysis, Salzburg, 2006. A. J. Kenny, M. Desprez I. Cato, G. Fader, R. T. E. Schüttenhelm, and J. Side, "An Overview of Seabed-mapping Technologies in the Context of Marine Habitat Classification," ICES Journal of Marine Sciences, vol. 60, pp. 411-418, 2003. Gottfried Konecny, Geoinformation: Remote Sensing, Photogrammetry and Geographic Information Systems. New York: Taylor & Francis Inc, 2003. Marwan Koudmani, "Applications of Remote Sensing to Hydrology and Hydrogeology," in International Conference on Water Resources & Arid Environment, Riyadh, 2004. Alphonce Kyessi and Victoria Mwakalinga, "GIS Application in Coordinating Solid Waste Collection: The Case of Sinza Neighbourhood in Kinondoni Municipality, Dar es Salaam City, Tanzania," in International Federation of Surveyors (FIG) Working Week, Eilat, 2009. Kamal Labbassi, Amina Tajdi, and Ahmed Er-raji, "Remote Sensing and Geological Mapping for a Groundwater Recharge Model in the Arid Area of Sebt Rbrykine: Doukkala, Western Morocco," in Geoscience and Remote Sensing Symposium, Cape Town, 2009, pp. 112-115. Nag Yeon Lee, E-Government Applications.: United Nations Asian and Pacific Training Centre for Information and Communication Technology for Development, 2009. Hyejin Lee and Lee Hyunah, "Design and Implementation of Integrated MapServer in Web Mapping Environments," in International Geoscience and Remote Sensing Symposium, 2005, Seoul, 2005. Bambang Edhi Leksono, Yuliana Susilowati, Hendriatiningsih, and Denisanto, "The Influence of Urban Accessibility in Determining Average Indicated Land Values for the Region.," in FIG Congress 2010: Facing the Challenges – Building the Capacity, Sydney, 2010. Arika Ligman-Zielinska, Richard L. Church, and Piotr Jankowski, "Spatial Optimization as a Generative Technique for Sustainable Multiobjective Land Use Allocation," International Journal of Geographical Information Science, vol. 22, no. 6, pp. 601-622, June 2008. Feng Ling, Qiu-wen Zhang, and Cheng Wang, "Comparison of SRTM Data with other DEM sources in Hydrological Researches," in [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] International Symposium on Remote Sensing of Environment, St. Petersburg, 2005. Lifan Li, Qing Yu, and Jiechen Wang, "Assistant Decision System of E-Government Based on WebGIS," in International Symposium on Information Engineering and Electronic Commerce, Ternopil, 2009. Xiaolin Lu, "A Unified E-Government Information Management Platform Based on Web GIS Technology," in International Conference on Computational Intelligence and Software Engineering, Wuhan, 2009, pp. 1-4. M.L. Manchanda, M. Kudrat, and A.K. Tiwari, "Soil Survey and Mapping Using Remote Sensing," Tropical Ecology, vol. 43, pp. 6174, 2002. Yannis Manolopoulos, Apostolos N. Papadopoulos, and Michael Gr. Vassilakopoulos, Spatial Databases: Technologies, Techniques, and Trends.: Idea Group Publishing, 2005. MapServer Team University of Minnesota, MapServer Documentation.: University of Minnesota, 2010. I. Masser, A. Rajabifard, and I.P. Williamson, "Spatially Enabling Governments through SDI implementation," International Journal of GIS, vol. 21, pp. 1-16, July 2007. Hartmut Müller, "Information Technology and Spatial Data Infrastructure for E-Government," in FIG Workshop on eGovernance, Knowledge Management and eLearning, Budapest, Hungary, 2006. Oil and Gas Management Branch, "Seismic Exploration," Yukon Government, Whitehorse, Yukon Government Oil and Gas Best Management Practices 2006. Open Geospatial Consortium. (2010, May) OGC Website. [Online]. http://www.opengeospatial.org Open GIS Consortium, OpenGIS Simple Features Specification for SQL.: Open GIS Consortium, Inc., 1999. Gordon Petrie and Kenneth Smillie, "Airborne Digital Imaging Sensors and Systems," in Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences: 2008 ISPRS Congress Book, Zhilin Li, Jun Chen, and Emmanuel Baltsavias, Eds. London: Taylor & Francis Group, 2008. Peter Poole, "Cultural Mapping and Indigenous Peoples," UNESCO, 2003. Presiden Republik Indonesia, Peraturan Presiden Republik Indonesia No. 85/2007., 2007. Yu-kun Qiao, Shi-cheng Wang, Jin-sheng Zhang, Li-hua Chen, and Qi Zhang, "Surface Spline Based Constructing Method for Geomagnetic Reference Map," in IEEE International Conference on Information and Automation, Zhuhai/Macau, 2009. Abbas Rajabifard, "SDI Design to Facilitate Spatially Enabled Society," in ISPRS workshop on Geoinformation and Decision Support Systems and 4th GIS Conference, Teheran, Iran, 2008. Abbas Rajabifard, "Spatially Enabled Government and Society: A Scenario for the Future," International Seminar on Land Administration Trends and Issues in Asia and The Pacific Region, August 2008. H.M. Rajesh, "Application of Remote Sensing and GIS in Mineral Resource Mapping - An overview," Journal of Mineralogical and Petrological Sciences, vol. 99, pp. 83-103, 2004. I. Prasada Rao, B. Kangadurai, P. K. Jain, and Neelam Jain, "Information System for Rural Road Network Planning - a case study," in Map India Conference, 2003. J. K. Rawat, Alok Saxena, and Sudhanshu Gupta, "Remote Sensing Satellite Based Forest Cover Mapping: Some Recent Developments," Indian Cartographer, 2003. T. J. Reerink, M. A. Kliphuis, and R. S. W. van de Wal, "Mapping Technique of Climate Fields between GCM’s and Ice Models," Geoscientific Model Development, vol. 3, pp. 13-41, January 2010. Ravi Prakash Rivastava, Nimisha Vedanti, and V.P. Dimri, "Optimal Design of a Gravity Survey Network and its Application to Delineate the Jabera-Damoh Structure in the Vindhyan Basin, Central India," Pure and Applied Geophysics, vol. 164, pp. 2009-2022, October 2007. Jeanne W. Ross, Peter Weill, and David C. Robertson, Enterprise Architecture as Strategy: Creating a Foundation for Business Execution.: Harvard Business School Press, 2006. M. Sarpoulaki, A. Eslami Rad, and A. Saleknia, "E-Government Concept and Spatial Information: A Case Study in Islamic Republic of Iran," The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVII, 2008. James Sinnott, Michael Lowry, Bill Cooter, Jennifer Lloyd, and Roger Anzzolin, "EPA Drinking Water Mapping Application: Client Focus [56] [57] [58] [59] [60] [61] [62] [63] and Architecture Design," in 23rd Annual ESRI International User Conference, 2003. State of Montana. (2010) Montana Base Map Service Center. [Online]. http://giscoordination.mt.gov Didi Sukyadi, Model Interoperabilitas Sistem Informasi Layanan Publik Studi Kasus: E-Government. Jakarta, Indonesia: Program Studi Magister Teknologi Informasi Fakultas Ilmu Komputer Universitas Indonesia, 2009. The Open Source Geospatial Foundation. (2010) MapServer History. [Online]. http://trac.osgeo.org/mapserver/wiki/MapServerHistory Waldo Tobler, "Movement Mapping," Center for Spatially Integrated Social Science, Santa Barbara, 2003. Yaw A. Twumasi, Andrew Manu, Tommy L. Coleman, Brian Schmid, and A. Moustapha, "Use of Geo-Spatial Data for Sustainable Management of Solid Waste in Niamey, Niger," Journal of Sustainable Development in Africa, vol. VIII, no. 1, 2006. University of Melbourne, Department of Geomatics, Country Report 2003: Indonesia.: PCGIAP-Working Group 3 "Cadastre"; FIGCommission 7 "Cadastre and Land Management", 2003. J. Wallace, I. P. Williamson, A. Rajabifard, and R. Bennet, "Spatial Information Opportunities for Government," Spatial Science, vol. 51, 2006. Shi-cheng Wang, Yu-kun Qiao, Jin-sheng Zhang, Li-hua Chen, and Qi Zhang, "SVM Based Constructing Method for Geomagnetic Reference [64] [65] [66] [67] [68] [69] [70] Map," in Pacific-Asia Conference on Circuits,Communications and System, Chengdu, 2009. Qihao Weng, Remote Sensing and GIS Integration: Theories, Methods, and Applications.: The McGraw-Hill Companies, Inc., 2010. Clay G. Wescott, "E-Government in the Asia-Pacific Region," Asian Development Bank, Working Papers January 2005. World Bank. (2002) The World Bank Group Web Site. [Online]. http://go.worldbank.org/M1JHE0Z280 Albert K. W. Yeung and G. Brent Hall, Spatial Database Systems: Design, Implementation, and Project Management.: Springer, 2007. Yun Zhang, "Pan-sharpening for Improved Information Extraction," in Advances in Photogrammetry, Remote Sensing and Spatial Information Sciences: 2008 ISPRS Congress Book, Zhilin Li, Jun Chen, and Emmanuel Baltsavias, Eds. London: Taylor & Francis Group, 2008. Shuliang Zhang, Jiayan Gan, LiZhi Miao, Guonian Lv, and Jiazhu Huang, "Study on GML Spatial Interoperability based on Web Service," in 31st Annual International Computer Software and Applications Conference, COMPSAC., Beijing, 2007, pp. 649-656. Wenfeng Zheng, Zhengtong Yin, and Xiaolu Li, "The Integration Evaluation and Explanation System of Geo-information in OpenGIS Environment," in International Conference on New Trends in Information and Service Science, NISS., Beijing, 2009, pp. 515-520