Work presented at the International Workshop on Engineering Open Data (WEOD), held in conjunction with 18th International Conference on Web Engineering (ICWE 2018) in Cáceres, Spain on 5th June 2018.

1. Elena Planas
eplanash@uoc.edu
Open University of Catalonia
Model-Driven Analytics
for Open Data APIs
David Baneres
dbaneres@uoc.edu
Open University of Catalonia
International Workshop on Engineering Open Data (WEOD)
Held in conjunction with 18th International Conference on Web Engineering (ICWE 2018)
Cáceres, Spain - 5th June 2018

3. goal of the open data movement:
empower end-users
to
exploit and benefit
from
open-data

4. Citizens ask:
How can we access and
manipulate open data?

5. Citizens ask:
How can we access and
manipulate open data?
Data providers ask:
How our data is used
by end-users?

6. Data providers ask:
How our data is used
by end-users?
Citizens ask:
How can we access and
manipulate open data?

7. we provide a
Model-Driven Analytical tool for Open Data APIs

8. we provide a
Model-Driven Analytical tool for Open Data APIs
our goal is to
visualize
how
end-users interact
with
open data
sources
regarding several
metrics

9. we provide a
Model-Driven Analytical tool for Open Data APIs

10. we provide a
Model-Driven Analytical tool for Open Data APIs
Log gathering
Log
Transformation
Computing &
Visualizing
metrics
Step 1 Step 2 Step 3

11. Step 1: Log gathering

12. Record all the
REQUESTS
made by users to the different API end-points
in a
LOG FILE

13. Record all the
REQUESTS
made by users to the different API end-points
in a
LOG FILE

14. general
REST
request
specific
REST
sub-request
specific
REST
sub-request
specific
REST
sub-request
* Hamza Ed-Douibi, Javier Luis Canovas Izquierdo and Jordi Cabot.
OpenAPItoUML: A tool to generate UML models from OpenAPI definitions
ICWE 2018 Demo: 6th Wednesday. 09.00 - 10.30
API1 API2 API3

15. http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
http://restcountries.eu/rest/v2/all http://battuta.medunes.net/api
/country/all?key=be8135f3cddb0
277a4c67711f8c0cd29
general
REST
request
specific
REST
sub-requests

16. Record all the
REQUESTS
made by users to the different API end-points
in a
LOG FILE

17. LOG structure
Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request

18. Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request
#1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
Example
LOG structure

19. Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request
#1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
Example
LOG structure

20. Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request
#1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
Example
LOG structure

21. #1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
LOG structure LOG information
Example
Time
Requested APIs
Server response
Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request

22. #1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
LOG structure LOG information
Example
Time
Requested APIs
Server response
Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request

23. #1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
LOG structure LOG information
Example
Time
Requested APIs
Server response
Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request

24. #1 2017-11-10 11:02:20 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries
#2 2017-11-10 11:02:23 - 200 http://restcountries.eu/rest/v2/all 2208
#3 2017-11-10 11:02:24 - 200 http://battuta.medunes.net/api/country/all?key=... 1076
#4 2017-11-10 11:02:24 - http://localhost:8080/OpenDataForAll/ODataService.svc/Countries yes
LOG structure LOG information
Opening: general request
specific sub request 1
…
specific sub request n
Closing: general request
Example
Time
Requested APIs
Server response

25. Step 2: Log Transformation

26. TRANSFORM
the initial
LOG FILE
to enrich its information

27. TRANSFORMED LOGINITIAL LOG

28. TRANSFORMED LOGINITIAL LOG
Input timestamp
general / for sub-query
Output timestamp
general / for sub-query
Response time
for each request and sub-request
Total time
for resolving a request
Time

29. TRANSFORMED LOGINITIAL LOG
Input timestamp
general / for sub-query
Output timestamp
general / for sub-query
Response time
for each request and sub-request
Total time
for resolving a request
Time
General request
Specific sub-requests
Number of sub-requests
for each general request
Number of requested APIs
in each general request
Requested
APIs

30. TRANSFORMED LOGINITIAL LOG
Input timestamp
general / for sub-query
Output timestamp
general / for sub-query
Response time
for each request and sub-request
Total time
for resolving a request
Time
General request
Specific sub-requests
Number of sub-requests
for each general request
Number of requested APIs
in each general request
Requested
APIs
Reliability
of each request and sub-request
Server
response
Reliability
of each request and sub-request

31. Step 3: Computing &
Visualizing metrics

32. COMPUTE
and
VISUALIZE
several
USAGE METRICS

33. COMPUTE
and
VISUALIZE
several
USAGE METRICS

34. COMPUTE
and
VISUALIZE
several
USAGE METRICS
PERFORMANCE
METRICS
SEMANTIC
METRICS

35. the aim of the
is to
measure and report
performance and volumes
of manipulated APIs
PERFORMANCE METRICS

36. API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

37. Response time by API:
Response time by request / sub-request:
%
%
%
%
%
%
API1
API2
API3
Request1
Sub-request1.1
Sub-request1.2
%
API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

38. Accessed APIs for each request:
%
%
Request1
Request2
Request3
%
API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

39. Generated sub-requests for each request:
%
%
Request1
Request2
Request3
%
API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

40. Collecting response codes of each sub-request:
Successfully served
Error: Bad request
Error: not found
API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

41. Performance metrics can be filtered by
several criteria:
API RELIABILITY
Average RESPONSE TIME
- by API
- by request / sub-requests
Average number of
ACCESSED APIs
for each request
Average number of
GENERATED SUB-REQUESTS
for each request
QUERY HISTORY
PERFORMANCE
METRICS

42. the aim of the
is to
analyze the consumed data
in the context of the
UML model
representing the requested APIs
SEMANTIC METRICS

43. HEAT UML MODEL
ENTITY/FIELD CONSUMPTION
QUERY DIAGRAM
SEMANTIC METRICS

44. Entities consumption is highlighted
using different colours:
High
demand
Low
demand
HEAT UML MODEL
ENTITY/FIELD CONSUMPTION
QUERY DIAGRAM
SEMANTIC METRICS

45. Show the number of requests to an
specific entity / field: HEAT UML MODEL
ENTITY/FIELD CONSUMPTION
QUERY DIAGRAM
SEMANTIC METRICS

46. Show the navigability to resolve the performed query:
HEAT UML MODEL
ENTITY/FIELD CONSUMPTION
QUERY DIAGRAM
SEMANTIC METRICS

47. COMPUTE
and
VISUALIZE
several
USAGE METRICS

48. Search Processing Language (SPL)
based on SQL
index = TransformedLog | stats avg(timeForRequest)
Example

49. COMPUTE
and
VISUALIZE
several
USAGE METRICS

50. dashboard (I)
Average response time by API

51. dashboard (II)
Average response time by request

52. dashboard (III)
Reliability

53. dashboard (IV)
Query history

54. dashboard (V)
Heat Map & Consumption

55. Conclusions

56. we provide a
Model-Driven Analytical tool for Open Data APIs
the monitoring and visualization of the open data consumption report
highly valuable information to data providers
Improve data
- Data precision
- Avoiding overlapping
- Removing non-accessed-data
Infer new knowledge
- New content to be published
- Potential partnerships

57. Elena Planas
eplanash@uoc.edu
Open University of Catalonia
Model-Driven Analytics
for Open Data APIs
David Baneres
dbaneres@uoc.edu
Open University of Catalonia
Questions?
* All the images of this presentation have been acquired from http://pixabay.com