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Information and Knowledge Management using ArcGIS ModelBuilder

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Misoo Kwon<br />

<strong>Information</strong> fidelity: This indicator is for reviewing whether the data can satisfy user requirements<br />

<strong>and</strong> measures quantitative sufficiency of information, diversity of information <strong>and</strong> substitutability<br />

for existing resources.<br />

Utilization convenience: This indicator reviews whether a user can easily use wanted data <strong>and</strong><br />

measures convenience of database use <strong>and</strong> search speed.<br />

Utilization rate: This indicator reviews the performance of database use such as the number of<br />

visits, searches <strong>and</strong> downloads.<br />

Utilization efficiency:This indicator is for reviewing whether the provided data increased business<br />

efficiency of user in terms of the amount of time saved.<br />

System management status: This indicator is for reviewing whether the database system is<br />

maintaining its optimized operation level. In particular, it reviews whether database management<br />

system monitoring is performed <strong>and</strong> checks the number of times that data were tuned.<br />

System processing speed: This indicator reviews whether the response time <strong>and</strong> throughput<br />

satisfy transaction requirements of each business process. In detail, it reviews the average<br />

response time of database <strong>and</strong> throughput.<br />

Data integrity: This indicator reviews if there are any data missing from required processes for<br />

business support. Specifically, it reviews the ratio of business <strong>and</strong> logical null values.<br />

Data accuracy: This indicator reviews whether the patterns <strong>and</strong> codes of data in the database are<br />

accurate. Specifically, it measures the ratio of data threshold compliance, ratio of pattern<br />

accuracy <strong>and</strong> ratio of code accuracy.<br />

Data consistency: This indicator reviews whether there is any inconsistency between the same<br />

data within the database.<br />

2.3 Performance review time <strong>and</strong> reviewer<br />

Performance review of NDP is one that is carried out during the second half of every year on the<br />

project result of the previous year. The reason for reviewing the performance afterwards is to<br />

measure the outcomes <strong>and</strong> impact of investment, find any problems in project operationas well as<br />

ways to improve them, <strong>and</strong> further improve performance.<br />

Performance review is carried out by selected survey agencies under the management of National<br />

<strong>Information</strong> Society Agency, which is the main organization supporting the project. The result of<br />

performance review is reported to the Ministry of Public Administration <strong>and</strong> Security <strong>and</strong> is used for<br />

selecting the next year NDP.<br />

3. Result of performance review in 2010<br />

3.1 Overview<br />

In 2010, the performance review was carried out on 50 databases that were established in 2009<br />

mainly in terms of business performance (user satisfaction, system utilization, system performance<br />

<strong>and</strong> data assurance) <strong>and</strong> economic impact.<br />

The review target was database users, system managers operating <strong>and</strong> managing developed<br />

databases, while the target for data assurance review was the entire databases developed during<br />

2009. Database users included internal users who use the developed database for business<br />

processes within their organization, relevant users who utilize the database from outside <strong>and</strong> the<br />

general citizens.<br />

Tools that were used for review were a survey questionnaire, checklist <strong>and</strong> survey tool for each<br />

performance review category as described above <strong>and</strong> face-to-face interview <strong>and</strong> online survey were<br />

the methods of review. From users, user satisfaction <strong>and</strong> convenience were the two categories<br />

surveyed through face-to-face interviews <strong>and</strong> online surveys (on a five-point scale). From system<br />

managers, system performance, utilization rate <strong>and</strong> time-saving were surveyed <strong>using</strong> a survey<br />

checklist. As for reviewing data assurance, a survey tool was used.<br />

Reviewing data assurance is to inspect any error in data values of the database. During the process,<br />

an automation tool is used based on st<strong>and</strong>ard information <strong>and</strong> business codes as defined in columns.<br />

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