Difference between revisions of "BingBong"

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'''List of group members'''
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August Haug Hem, 
  
'''Group Members'''
 
August Haug Hem, 
 
 
Åvald Åslaugson Sommervoll,   
 
Åvald Åslaugson Sommervoll,   
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Mahasty Assi   
 
Mahasty Assi   
  
'''Assignment'''
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'''Summary of requirements'''
 
A Cleaning and Deduplication of Events
 
A Cleaning and Deduplication of Events
 
The DHIS2 Tracker module allows people to collect individual level data. These come in two forms:
 
The DHIS2 Tracker module allows people to collect individual level data. These come in two forms:
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However, patients often go to different clinics for the same thing, and a lot of data is collected offline, without the possibility to check if the patient is already in the system. Therefore, there is a need to A) identify duplicate people and B) reconcile the data belonging to the same person.
 
However, patients often go to different clinics for the same thing, and a lot of data is collected offline, without the possibility to check if the patient is already in the system. Therefore, there is a need to A) identify duplicate people and B) reconcile the data belonging to the same person.
 
The task is to make a webapp which helps administrators to easily identify clear and potential duplicates (e.g. slight misspellings) and mark them for reconciliation (which the app could also assist in). A combination of automated and manual filtering/navigation. You can initially assume the number of persons and events is small enough to be handled in the client. For more advanced functionality, it is also interesting to link to server side procedures.  
 
The task is to make a webapp which helps administrators to easily identify clear and potential duplicates (e.g. slight misspellings) and mark them for reconciliation (which the app could also assist in). A combination of automated and manual filtering/navigation. You can initially assume the number of persons and events is small enough to be handled in the client. For more advanced functionality, it is also interesting to link to server side procedures.  
 
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'''Time schedule'''
'''Pictures'''
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Thursday 10-12
 
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'''How you are dividing tasks within the group'''
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So far:
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Wiki: Åvald
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'''Screenshots and screen flows'''
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'''Documented learning during project'''
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'''Suggested improvements to APIs etc'''
 
'''Link to repository'''
 
'''Link to repository'''
https://github.com/lax1n/INF5750-Project
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https://github.com/lax1n/INF5750-Project
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'''Download link to sample web app'''

Revision as of 10:22, 20 October 2016

List of group members August Haug Hem,

Åvald Åslaugson Sommervoll,

Mahasty Assi

Summary of requirements A Cleaning and Deduplication of Events The DHIS2 Tracker module allows people to collect individual level data. These come in two forms: 1) “Singelton” cases that are recorded only once without registration or follow-up (e.g. Outpatient data). DHIS2 calls this a single event. 2) Events linked to a person (the DHIS2 term is a Tracked Entity Instance - TEI) where you first look up a person (or register a new) who is enrolled in a health program and then follow the patient over a period, with each visit to the doctor recorded as an event, linked to the program (e.g. a TB patient). However, patients often go to different clinics for the same thing, and a lot of data is collected offline, without the possibility to check if the patient is already in the system. Therefore, there is a need to A) identify duplicate people and B) reconcile the data belonging to the same person. The task is to make a webapp which helps administrators to easily identify clear and potential duplicates (e.g. slight misspellings) and mark them for reconciliation (which the app could also assist in). A combination of automated and manual filtering/navigation. You can initially assume the number of persons and events is small enough to be handled in the client. For more advanced functionality, it is also interesting to link to server side procedures. Time schedule Thursday 10-12 How you are dividing tasks within the group So far: Wiki: Åvald Screenshots and screen flows Documented learning during project Suggested improvements to APIs etc Link to repository https://github.com/lax1n/INF5750-Project Download link to sample web app