Clinic Locator: A Mashup Application for Finding Clinics Based on Location and Services

ICT705
Data and System Integration
Task 2

EXECUTIVE SUMMARY
In this report, we discussed about the project in which using the map we can locate the area in
which there is a clinic. The code for this particular project is developed in python language so
that all the data can be integrated into single bundle and different methods of programming is
used in this project. There is total three steps for developing the project. Firstly, cleaning and
merging of data is done. Secondly, RESTful web server is formed and lastly, we will create a
Mashup for the searching activity.
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Contents
EXECUTIVE SUMMARY..........................................................................................................................i
INTRODUCTION......................................................................................................................................1
DATA INTEGRATION..............................................................................................................................2
Data Cleaning:.......................................................................................................................................2
Data Merging:........................................................................................................................................4
RESTful WEB SERVICES............................................................................................................................6
MASHUPS................................................................................................................................................9
DEMO RUNNING INSTRUCTION.......................................................................................................10
CONCLUSION........................................................................................................................................13
BIBLIOGRAPHY.....................................................................................................................................14
APPENDIX...............................................................................................................................................15
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INTRODUCTION
The inspiration of this report is to give the area of Clinic through making software which helps us
in obtaining the location of the clinic. The Mashups are used for evacuating information which
isn't required and go to the server for combining and this procedure known as information
incorporation. This record comprises of various documents with information used for expel and
converges from RESTful web servers which give administration to bringing the information from
CSV documents which is cob=verted from a XML record. This document information will
converge for getting the expected data to find the centre on a guide utilizing python dialect. The
bottle system gives JSON information got from RESTful web servers and this information is
utilized by Mashup programming to make a blip on the guide. The essential learning of this
report is XML record change in CSV document and undesirable information will clean and store
at the server which will get by Mashup programming and the container system utilize this
information in JSON configuration to find the zone or area on the guide by making blip through
Mashup programming.
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DATA INTEGRATION
Data integration is a technique in which data cleaning and data merging is done. The concept is
discussed below:
Data Cleaning:
Each and every time we prepare any data, the data that emerges could be of different
association’s like.TXT (Tab-delimited substance) &.CSV (comma-delimited
characteristics) plan. The planning is prepared to combine or facilitate the various kinds
of data into one. The date could be from similar source or from different source; the
information could be from comparable source.
For this project also, we will first remove the unnecessary data with the help of some
algorithms. For cleaning the data we have to first analyse the data and identify the
unnecessary data from the whole stored information. The cleaning of data is done from
clinic.csv file.
Figure 1 Before data cleaning clinic.csv file
After data cleaning, the output table will be
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Figure 2 After data cleaning the output file
The mentioned code is for the data cleaning of the file
Data Merging:
Clinic.csv: clinic.csv contains all the information and knowledge about the services such
as state, email, suburb as name, postcode, meta data. This record consist every detail
data that should be ready to keep in mind the last objective to complete the desire result
that is collecting the data of clinis.csv with the data through the locations.xml.
Cliniclocatons.xml: it contains the information and knowledge of the location of the clinic.
It consist longitude and latitude of the clinics through the clinicid. In this
cliniclocations.xml information is changed into .csv file.
Data merging code is mentioned below;
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The output of the data
merging is mentioned below
Figure 3clinicserviceslocation.xml file
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RESTful WEB SERVICES
RESTful web server perceives the factors or information by the use of architecture of Virtual
Hierarchical which shows the output of the system as the client want to see.
The RESTful web server stores the web program which is actualized or designed into the
python which is help to locate the required information and execution is done using the
command prompt.
Library used to implement this tasks are:
 Bottle framework
 Petl
Benefits of using Bottle framework
Bottle framework is small in size as it is located in the module of a single file and it size varies in
between 50-60kB. It only contains the useful data and does not pack it more than its limits with
unessential data. It is easy to understand if you have knowledge of python and web
development as this framework uses the combination of both.
Benefits of using Petl library
In petl framework it has code which has already been built and already been tested which
makes the application more reliable and does not require that much effort in programming and
testing. It can be upgraded by the person who created it which will help in providing
functionalities which are new and improved performance. It does not require time for testing
Following is the code for the RESTful web services:
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Figure 4 code of clinic_locator.py file
The URL to fetch the JSON data is given below1:
http://localhost:8080/getclinics?serviced=x
Suppose userput http://localhost:8080/ getclinics?serviced=2
Screenshot for the above code is mentioned below
Figure 5 localhost:8080 web page
Figure 6 output for service ID= 4
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For this web server used in this project, I influenced a python to design the file named as
clinic_locator.py which will invoke the RESTful web server when the user enters into the
connection which is composed already.
Web organization will continue running on any desired web program. For starting the RESTful
web we will be starting when the file named as "clinic_locator.py" is continue running on
Command Prompt dependent upon the necessities.
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MASHUPS
We can consider the mashup as the web application which takes the information from the more
than one sources to design the single service which is displayed as the single GUI (graphical
user interface).
The term suggests simple, quick mix, much of the time utilizing open API and information
sources to deliver improved outcomes that were not really the first purpose behind the raw data
from the different source. In the given task, the mashup is related as follows:
1. For handling the information, the web services is designed which takes the information
from python code which is composed on the given framework.
2. Now the output from the web service is continued to the application as JSON and the
handling of information is finished.
3. Now the html document is prepared using the CSS or java script. The final document is
named as clinic_map.html. Hence, we can say that the main aim of mashup is to design
the html document which takes the data from the client as the postcode.
4. This html document also takes the information the RESTful web services and used to
show the boundaries of the area in the map. This web page also used to show the
location of the searched clinic on the Google Map.
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DEMO RUNNING INSTRUCTION
The two most famous modules named as ‘Bottle Framework’ and ‘Petl’ has been used to design
the given application.
The whole project is divided into the four sub tasks. Firstly, the data cleaning of the file is done
and then data merging of the records is done. Thirdly, RESTful web server is created and lastly,
mashup is created.
Step 1: File named as data_merger is run
Step 2: File named as clinic_locator.py is run
The output displayed on the command prompt is as follows:
On double clicking the clinic_map.Html file the mashup web services is run and the requires
application is opened.
After user entered into the postcode, he will select the required medical services from the given
list and the clinic will be allocated by the application.
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Figure 7 enter postcode and service
Figure 8 flag for location for the entered postcode and service
Figure 9clinic location details when clicks on flag
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CONCLUSION
This given project is on to find the location of the clinic which is suitable for the user. The user
will select the diseases from the given list and according to the user requirement, the application
will allocate the clinic and its geographical area.
This record utilizes the different kind of software as Bottle structure, Mashups and RESTful web
server which is used to change the XML record into the CSV and after that produce JSON data
to make a blip on the guide by making the information from documents which comprise of
undesirable information data.
And for this, there are various steps in which the first step is to clean the unwanted data and
then merger the resultant record. Then we will create the RESTful web service and then we will
design the mashups in which the data from the different sources are stored in one single file.
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BIBLIOGRAPHY
 Kulathuramaiyer, N., 2007. Mashups: Emerging application development paradigm for a
digital journal. J. UCS, 13(4), pp.531-542.
 Hamad, H., Saad, M. and Abed, R., 2010. Performance Evaluation of RESTful Web
Services for Mobile Devices. Int. Arab J. e-Technol., 1(3), pp.72-78.
 Rahm, E. and Do, H.H., 2000. Data cleaning: Problems and current approaches. IEEE
Data Eng. Bull., 23(4), pp.3-13.
 Fischer, C.C., Tibbetts, K.J., Morgan, D. and Ceder, G., 2006. Predicting crystal
structure by merging data mining with quantum mechanics. Nature materials, 5(8),
p.641.
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APPENDICES
Code screenshots:
Data_Merger.py:
Clinic_locator.py
Figure 10 Clinic_locator.py
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