Cross-Agency Interoperable Application Development: A Local Government SDI Perspective

• Main Authors: Yi-LingHuang, 黃乙翎
• Other Authors: Hung-Jung Hung
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/qvksjr

碩士 === 國立成功大學 === 測量及空間資訊學系 === 104 === Cross-Agency Interoperable Application Development: A Local Government SDI Perspective Yi-Ling Huang Jung-Hong Hong Department of Geomatics, National Cheng Kung University SUMMARY Spatial Data Infrastructure has been viewed as a cooperative infrastructure of spatial resources for centralizing different spatial resources from different departments. There has been bundles of developed instances of national level spatial data infrastructure around the world, as the rapid progression of information technology, the developing trend of spatial data infrastructure has turned toward establishing a portal of web services, as a gathering of spatial resources which has been responsible by different departments through the working of web catalogue service. It provides an easy way for users to reach resources in need. Three major contributions can be summarized : 1) characterizing common dataset with fixed aspects, including temporal, spatial, identifying and quality, provides an uniform way to evaluate adequacy 2) a series of common solution is proposed with respect to each characteristics, and will be carried out through web service technology by cooperation among different departments with different professional backgrounds 3) correctness and interoperability of cross-agency sharing can be ensured by categorizing data by characteristics and applying the corresponding common solutions through web services The last but not the least, this study emphasizes the importance of a tightly coupled cooperation scenario by taking the application need of users with cross-agency affairs into consideration. And expect to activate the original developing trend of spatial data infrastructure at national level and finally to attend a brand new era of spatial data infrastructure. Key worlds : spatial data infrastructure, local government, cross-agency INTRODUCTION Spatial Data Infrastructure(SDI) has been viewed as a cooperative infrastructure of spatial resources for centralizing different spatial resources from different departments. There has been bundles of developed instances of national level spatial data infrastructure around the world, as the rapid progression of information technology, the developing trend of spatial data infrastructure has turned toward establishing a portal of web services, as a gathering of spatial resources which has been responsible by different departments through the working of web catalogue service. It provides an easy way for users to reach resources in need even without any professional backgrounds. The development of spatial data infrastructure at national level has been focused on open format, standards of data. Often leave the problem of interoperability behind due to the lack of vertical coordination among national governments and local governments and horizontal coordination among departments under local government. The goals of this research are: 1. Characterize the dataset of common need in cross-agency affairs to ensure the correctness of heterogeneous data fusion. 2. Propose common solutions correspond to characteristic types and consider the importance of professional knowledge in interactions between different agencies and take it into consideration when designing the solutions. 3. Accomplish the cooperation planning mentioned above and the coordination among departments under local government by assigning different roles and missions through public power. MATERIALS AND METHODS As for achieving the goal of using heterogeneous data right and interoperable, this research propose solutions by characterizing common dataset with respect to temporal, spatial, identifying and quality aspect. In the meanwhile, a standardized data analyzing procedure is accomplished and hence common solutions are proposed as well. Planning mentioned above is executed by assigning roles of departments under local government with professional backgrounds of each and is ensured to be implemented with the aid of public authority. Among characteristic types mentioned above, temporal factor is the most important one due to every data has its own temporal record no matter what semantic meaning is, like time of data manufactured or time of data updated, and has profound influence in correctness issue of data fusion. Common dataset is set by categorizing dataset involved in cross-agency affairs especially land related among local government apartments. Common dataset include spatial and literal data type : door-plate data, administrative maps, cadastral maps, urban plan data, household registration data, land and building registration data, legal building certification, land tax data. Most of literal data maintained by local government apartments has indirect spatial meaning and could be assign it’s spatial meaning by geocoding. In this way, the efficiency of cross-agency data fusion would be highly enhanced through series of standard data character analyzing, take the corresponding common solution and finally applying into the working of different apartment affairs correctly. Solutions with respect to each characteristics are outline as Table 1. Table 1. Common solutions corresponding to each characteristics Aspect Solution Temporal 1.record time of dataset, include begin and end time of each historical version 2.record semantic meaning with standardized description Spatial 1.direct spatial meaning : (1)record spatial reference system with EPSG code set up by The International Association of Oil ＆ Gas Producers (IOGP)(2)record semantic meaning of spatial location with standardized description contents 2.indirect spatial meaning : (1) spatial hierarchy : record the hierarchical relationship and its contents in standardized way (2)record each historical version with begin and end time Identifying 1.record whether spatial location changes with different historical identifier versions Quality 1.adopt quality elements regulated in TWSMP RESULTS AND DISCUSSION Several data characteristic types are derived after analyzing with temporal, spatial, identifying, and quality aspect. In temporal aspect, time efficiency and historical version existence are two major categories. There are last update type and (up-to-date) time efficiency types and continuous, discontinuous and non-historical version types. With the type of continuous historical, every changes of data can be traced back and data at any time stage within its life cycle can be requested. In spatial aspect, direct and indirect spatial meaning and are two major categories. Characteristic types of indirect spatial meaning can be separated into three major types due to historical version of its literal contents, semantics of spatial location and the hidden spatial hierarchy. If the hierarchy relationship of indirect spatial meaning is known and contents of data has been standardized, then data with higher scale can be generated by elaborating the hierarchy stage of data with lower scale. In identifying aspects, whether spatial location changes with different identifier versions which represent indirect spatial meaning is the major categorization rule. If spatial location never changed with alternations of identifier, then its spatial location is capable to be traced by linking different historical versions. In quality aspect, this research adopted TWSMP quality elements, which follow up ISO19113, as data quality information. CONCLUSION Correctness of heterogeneous data fusion within departments under local government is confirmed by analyzing characteristics with fixed aspect and corresponding common solutions. With local government SDI, cross-agency cooperation is accomplished by assigning role of data producer, data broker or data user and ensured to be taken into practice by formulating local policies. Common dataset has been analyzed with temporal, spatial, identifying and quality aspects and solutions with respect to each one have been turned into designs of data attribute and service flow. Solutions proposed provide data producers an uniform procedure when producing data with different characteristics as well as providing data users a simple and clear way when manipulating different kind of data even without complete domain knowledge. Interaction between national and local governmental SDI should be both top-down and bottom up in order to eliminate restrictions resulted from the nature it originally designed. Top-down interaction exists in the adoption of national SDI in the development of local government SDI. And bottom-up interaction exists in the collection of common needs among different local governments as reducing duplication and strengthening connections between the two. Finally achieving the effect of sharing right and enhancing the essence of SDI.