Welcome to. Workshop on Mee Seva - LRMIS Data Purification. 9 th December 2011. Mee-Seva Introduction. As per the Electronic Service Delivery Rules (2011),Government of Andhra Pradesh has initiated the Mee Seva Project, under which nine revenue services are initially lauched.
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- LRMIS Data Purification
9th December 2011
As per the Electronic Service Delivery Rules (2011),Government of Andhra Pradesh has initiated the Mee Seva Project, under which nine revenue services are initially lauched.
The Project was launched on pilot basis in Chittoor District by Hon’ble Chief Minister on 4th November 2011.
Subsequent Roll-out is planned in Krishna and Khammam District.
By 31-3-2012, all districts should also start Mee Seva services
MeeSeva is an e Governance initiative by Govt. of A.P. to improve delivery of citizen services and simplify the process of accessing them.
This is made possible trough the meesevaportal through which any citizen can access the available services by submitting an online request and making stipulated payment. The citizen gets a digitally signed certificate either at the meeseva counter or through courier at his door steps depending on the time frame fixed.
Thus he need not go to the Government Offices again and again wasting time and money.
Four Services related to Land Records data are included under Mee Seva Project. They are:-
LRMIS data is available in the client-server based stand alone LRMIS 6.5 application. The data is in Oracle.
Mee Seva is a web based application with a Central SQL Server data base located at State Data Centre, Hyderabad.
In LRMIS 6.5 SSID is the key factor.
In Mee Seva Khata Number is the key factor.
During data porting validations are made on:
1. Khata number should not be null or zero
2. Duplicate khata numbers are not allowed
3. Pattadar name can not be blank
4. Occupant name can not be blank
5. Pattadar/ Occupant extent should not be zero
6. Total Extent can not be zero or null
Thus our prime aim is to purify the Land Records data using LRMIS 6.5 software.
You will be given mandal-wise check lists to identify such data gaps in your LR data.
Take the help of your hand holding person to get the checklists.