This presentation is part of the course "184.742 Advanced Services Engineering" at The Vienna University of Technology, in Winter Semester 2012. Check the course at: http://www.infosys.tuwien.ac.at/teaching/courses/ase/

1. Advanced Services Engineering,
WS 2012, Lecture 5
Evaluating Data Concerns for DaaS
Hong-Linh Truong
Distributed Systems Group,
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://www.infosys.tuwien.ac.at/staff/truong
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2. Outline
 Data concern-aware DaaS service engineering
 Data concern evaluation
 Data concern publishing
 A Proof-of-concept: QoD Framework
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3. Recall -- DaaS Concerns
data .... .... DaaS data assets
APIs, Querying, Data Management, etc.
Data
concerns
Quality of Ownership
data Price
License ....
DaaS concerns include QoS, quality of data (QoD),
service licensing, data licensing, data governance, etc.
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4. Recall -- DaaS design &
implementation
Data resource
Data
items
Consumer
Data Data
Data items items
assets
Consumer
Data resource Data resource
Data resource Data resource
DaaS
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5. HOW TO EVALUATE DATA
CONCENRS FOR DATA
ASSETS IN DAAS?
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6. Patterns for „turning data to DaaS“
data Build Data Deploy
DaaS
Service Data
APIs Service
Storage/Database
-as-a-Service
data DaaS
data
Storage/Databa
se/Middleware DaaS
Things
data
Storage/Database/
Middleware DaaS
People
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7. Data-related activities
Typical activities for data wrapping and publishing
Wrapping Publishing DaaS Provisioning
data interface data
Typical activities for data updating & retrieval
Updating Selecting
data
data data
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8. Typical data concern evaluation
Evaluating data Describing data Populating data
concerns concerns concerns
What do we need in order to perform these activities?
Data Concerns Data Concerns Publishing services
Evaluation Tools Representation Models
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9. Data concern-aware DaaS
engineering process Typical activities
for data wrapping
and publishing
Typical activities
for data updating &
retrieval Hong Linh Truong, Schahram Dustdar: On Evaluating and Publishing
Data Concerns for Data as a Service. APSCC 2010: 363-370
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10. Wrapping, selecting, and updating
data in DaaS (1)
different strategies for structured data and unstructured data
DaaS service operation
Processing
parameter
Data Mapping parameters to Mapping parameters to
Consumer data queires parameter metadata queries
Query content of
data resources Querying metadata of
data resources
Mapping and
returning results
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11. Wrapping, selecting, and updating
data in DaaS (2)
 Different techniques exist for wrapping,
selecting, updating and retrieving data
 How generic data concern evaluation and
publishing techniques can be integrated with
these techniques?
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12. Discussion
WHICH TYPES OF DATA ARE NEEDED FOR
EVALUATING DATA CONCERNS?
WHAT IS THE IMPACT OF DATA
PROVISIONING MODELS (OFFLINE
VERSUS NEAR-REALTIME) ON CONCERN
EVALUATION/PUBLISHING?
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13. Evaluating data concerns – the
three important points
evaluation • At which level the
scope evaluation is performed?
evaluation • When the evaluation is
modes done?
integration • How the evaluation tool
model is invoked?
Hong Linh Truong, Schahram Dustdar: On Evaluating and Publishing Data Concerns for Data as a Service. APSCC
2010: 363-370
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14. Evaluating data concerns –
evaluation scopes
Why multiple evaluation scopes make sense?
enable fine-grained evaluation
 Three scopes
 data resource
 DaaS operations
 DaaS as a whole
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15. Evaluating data concerns –
evaluation modes
Why multiple evaluation modes make sense?
suitable for different types of data
 Off-line
 before the access to data
 On-the-fly
 when the data is requested
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16. Evaluating data concerns –
integration modes
Why multiple integration modes make sense?
suitable for different tool integration strategies
 Push and pull data concerns
 Pass-by-value versus pass-by-reference to data
concerns evaluation tools
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17. Evaluating data concerns – some
patterns (1)
Pull, pass-by-references
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18. Evaluating data concerns – some
patterns (2)
Pull, pass-by-values
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19. Evaluating data concerns – some
patterns (3)
Push, pass-by-values
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20. Discussion time
BASED ON WHICH CRITERIA, AN EVALUATION
SCOPE, EVALUATION MODE OR INTEGRATION
MODE IS SELECTED?
WHY WE DO NOT REALLY DISCUSS HOW TO
IMPLEMENT EVALUATION TOOLS?
WHICH ARE OTHER COMPONENTS INTERACTING
WITH EVALUATION TOOLS?
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21. Publishing data concern
information (1)
 Off-line publishing of data concerns
 suitable for static data concerns
 the publishing of data concerns of a data
resource is separated from the service
operation which provides the access to the
data resource
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22. Publishing data concern
information (2)
 On-the-fly publishing of data concerns
 associating concerns with retrieved data
resources
 the resulting data resources (e.g., via queries)
are annotated with data concerns evaluated
by data concerns evaluation tools.
 suitable for providing dynamic data concerns
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23. Publishing data concern
information (3)
 On-the-fly publishing of data concerns through
queries
 the use of different service operation
parameters to query data concerns of data
resources
 suitable for validating data concerns before
accessing data resources
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24. Discussion time
WHAT ARE THE RELATIONSHIPS BETWEEN
CONCERN EVALUATION AND PUBLISHING
WHEN DATA IS DYNAMICALLY UPDATED?
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25. How do we utilize the data concern-
aware service engineering process?
 Using this model we can determine and publish
several concerns
 Our “a proof-of-concept”
 A framework for evaluating and publishing QoD of
DaaS
 A proof-of-concept implementation of data concern-
aware service engineering process
 Another example: model and publish privacy
concerns for DaaS [ECOWS 2010]
Michael Mrissa, Salah-Eddine Tbahriti, Hong-Linh Truong, "Privacy model and annotation for DaaS", The 8th European
Conference on Web Services (ECOWS 2010), (c)IEEE Computer Society, 1-3 December, 2010, Ayia Napa, Cyprus
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26. QoD framework (1)
 Pull QoD Evaluation Models for DaaS
 Pass-by-references and pass-by-value
 References of data resources: URI
 Values: any object
 Third-party data evaluation tools
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27. QoD framework (2)
http://www.infosys.tuwien.ac.at/prototype/SOD1/dataconcerns/
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28. QoD framework: publishing
concerns (1)
 Off-line data concern
publishing
 a common data concern
publication specification
 a tool for providing data concerns
according to the specification
 supported by external service
information systems
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29. QoD framework: publishing
concerns (2)
 On-the-fly querying data concerns associated with data
resources
 Using REST parameter convention
 Based on metric names in the data concern
specification
Hong Linh Truong, Schahram Dustdar, Andrea Maurino, Marco Comerio: Context, Quality and Relevance:
Dependencies and Impacts on RESTful Web Services Design. ICWE Workshops 2010: 347-359
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30. QoD framework: publishing
concerns (3)
 Specifying requests by using utilizing query parameters
the form of metricName=value
GET/resource?crq.accuracy="0.5"&crq.location=’’Europe”
 Obtaining contex and quality by using context and quality
parameters without specifying value conditions
curl http://localhost:8080/UNDataService/data/query/Population annual growth rate
(percent)?crq.qod
{”crq.qod” : {
”crq.dataelementcompleteness ”: 0.8654708520179372,
”crq.datasetcompleteness”: 0.7356502242152466,
...
}}
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31. QoD framework: QoD monitoring
and composition
 QoD concerns monitoring and composition are
useful for the evaluation of aggregated data
resources
 Our approach
 Utilizing monitoring rules
 QoD metrics of data resources are passed to an rule
engine
 Rules are user-defined for monitoring and composing
QoD metrics
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32. QoD framework experiments
 Implementation
 Java, JAX-RS/Jersey, Drools
 Utilizing UNDataAPI - www.undata-api.org
 XML data sets without QoD
 Illustrating examples: check data from 1990-
2009
 datasetcompleteness: the completeness of the list of
countries
 dataelementcompleteness: the completeness of data
elements in the list metrics
 RESTful services wrapping to UNDataAPI
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33. QoD framework experiment:
evaluating and annotating QoD
metrics
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34. QoD framework experiments:
publishing QoD with data
resources
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35. QoD framework experiments:
simple rules for monitoring and
composing QoD
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36. Discussion time
HOW TO DEAL WITH OTHER
CONCERNS?
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37. Exercises
 Read mentioned papers
 Identify and analyze the relationships between
data concerns evaluation tools and types of data
 Analyze trade-offs between on-line and off-line
evaluation and when we can combine them
 Analyze how to utilize evaluated data concerns
for optimizing data compositions
 Analyze situations when software cannot be
used to evaluate data concerns
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38. Thanks for
your attention
Hong-Linh Truong
Distributed Systems Group
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://www.infosys.tuwien.ac.at/staff/truong
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