This document discusses analyzing and specifying concerns for data as a service (DaaS). It outlines key issues including a lack of standardized models and terminology for describing data quality, context, and other concerns. The document presents examples of how data concerns are important for mashups, open data usage, and smart environments. It also discusses challenges like missing evaluation techniques and APIs for concerns. The document proposes developing linked models, concern evaluation techniques, and APIs to address these issues.

1. Advanced Services Engineering,
WS 2012, Lecture 4
Analyzing and Specifying 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
ASE WS 2012 1

2. Outline
 What are data concerns and why their are
important
 Issues in DaaS concerns
 Analysis and specification of DaaS concerns
ASE WS 2012 2

3. What are data concerns?
data .... .... DaaS data assets
APIs, Querying, Data Management, etc.
Located price?
Quality of data? Privacy
in US?
problem? Service
free? redistribution?
quality?
ASE WS 2012 3

4. 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.
ASE WS 2012 4

5. Why DaaS/data concerns are
important?
 Too much data returned to the
consumer/integrator
 Results are returned without a clear usage and
ownership causing data compliance problems
Ultimate goal: to provide relevant data with
acceptable constraints on data concerns
ASE WS 2012 5

6. Example: Mashup (1)
 Composition of Yahoo! Boss News Search,
Google News Search , and Flickr
 recent news and high-qualified images, but free-
 of charge, related to "Haiti earthquake"
Hong Linh Truong, Marco Comerio, Andrea Maurino, Schahram Dustdar, Flavio De Paoli, Luca Panziera: On
Identifying and Reducing Irrelevant Information in Service Composition and Execution. WISE 2010: 52-66
ASE WS 2012 6

7. Example: Mashup (2)
7

8. If the composer is aware of context
and quality parameters
 Possible mappings of context and quality
requirements
but it is a tedious task and hard to be automated and we
are not sure we have a correct mapping.
ASE WS 2012 8

9. Example: open data (1)
 Retrieve big datasets from RESTful services for further
extraction, transform or data composition activities
http://www.undata-api.org/
ASE WS 2012 9

10. Example: open data (2)
 Example: study the population growth and
literacy rate from 1990-2009 for all countries in
the world
 Without QoD: get datasets and perform mashup
ASE WS 2012 10

11. Example: open data (2)
CountriesYear 1990 ... 2009
223
1
elements ...
 With QoD support: 223
 Population annual growth rate (percent):
 dataelementcompleteness= 0.8654708520179372,
datasetcompleteness=0.7356502242152466;
 Adult literacy rate (percent):
 dataelementcompleteness=0.5874439461883408
 datasetcompleteness=0.04349775784753363
Should we retrieve the data and perform data
composition?
ASE WS 2012 11

12. Example: smart environments
 Smart environments with several low level sensors:
 Recognize human activities: idle, relaxing, and cleaning
up,
 Provide context information for adaptive service
discovery and execution
 E.g., FP7 SM4All, FP7 EU OPPORTUNITY
 Virtual Sensor-as-a-Service provides human activities
ASE WS 2012 12

13. Example: smart environments (2)
PoC: Probability of Correctness
QoC: Quality of Context
VSS: Virtual Sensor Service Atif Manzoor, Hong Linh Truong, Christoph
Dorn, Schahram Dustdar: Service-centric
CMS: Context Management Service Inference and Utilization of Confidence on
CCS: Context Consumer Service Context. APSCC 2010: 11-18
AC: Appliances Control (AC)
AM: Ambiance Management
ASE WS 2012 13

14. Discussion time
WHAT ARE OTHER CASES
WHERE DAAS CONCERNS
ARE IMPORTANT FOR?
ASE WS 2012 14

15. Issues on DaaS concerns (1)
 DaaS concern models
 Unstructured description of context, QoS and
quality of data (QoD)
 Different specifications and terminologies
 Mismatching semantics of information about
services and data concerns
ASE WS 2012 15

16. Issues on DaaS concerns (2)
 DaaS APIs
 No/Limited description of data and service
usage
 No API for retrieving quality and context
information
 No quality and context information associated
with requested data
ASE WS 2012 16

17. Issues on DaaS concerns (3)
 Evaluation techniques
 Missing evaluation of compatibility of context
and concerns for multiple DaaS and data
assets
 Missing evaluation techniques to filter
large/irrelevant data quantity
Require a „holistic integration“ of information models,
APIs and evaluation techniques for DaaS concerns!
ASE WS 2012 17

18. Solutions needed
Developing meta-model and domain-dependent semantic
representations for quality and context information specifications
Reconciliation of DaaS concern
Linked DaaS concerns models
terms
Developing context and DaaS concerns that can be accessed via open
APIs
APIs extension External DaaS information service
Developing techniques for context and DaaS concerns evaluation
On-the-fly data concerns Concerns compatibility evaluation
evaluation and composition
ASE WS 2012 18

19. Discussion time
WHY CONTEXT IS
IMPORTANT?
ASE WS 2012 19

20. DaaS concerns analysis and
specification
 Which concerns are important in which
situations?
 How to specify concerns?
Hong Linh Truong, Schahram Dustdar On analyzing and specifying concerns for data as a service. APSCC 2009: 87-
94
ASE WS 2012 20

21. The importance of concerns in
DaaS consumer‘s view – data
governance
Storage/Database
-as-a-Service
data DaaS
Data governance
Important factor, for example, the security and
privacy compliance, data distribution, and auditing
ASE WS 2012 21

22. The importance of concerns in DaaS
consumer‘s view – quality of data
Read-only DaaS CRUD DaaS
 Important factor for the  Expected some support
selection of DaaS. to control the quality of
 For example, the the data in case the data
accurary and is offered to other
compleness of the data, consumers
whether the data is up-to-
date
ASE WS 2012 22 22

23. The importance of concerns in
DaaS consumer‘s view– data and
service usage
Read-only DaaS CRUD DaaS
 Important factor, in  Important factor, in
particular, price, data paricular, price, service
and service APIs APIs licensing, and law
licensing, law enforcement
enforcement, and
Intellectual Property
rights
ASE WS 2012 23

24. The importance of concerns in
DaaS consumer‘s view – QoD
Read-only DaaS CRUD Daas
Important factor, in Important factor, in
particular availability and particular, availability,
response time response time,
dependability, and security
ASE WS 2012 24

25. The importance of concerns in DaaS
consumer‘s view– service context
Read-only DaaS CRUD DaaS
Useful factor, such as Important factor, e.g.
classification and service location (for regulation
type (REST, SOAP), compliance) and versioning
location
ASE WS 2012 25

26. Discussion time
WHAT ARE OTHER
IMPORTANT ISSUES? ADD
YOUR FINDING!
ASE WS 2012 26

27. Conceptual model for DaaS
concerns and contracts
ASE WS 2012 27

28. Capability concerns
Data Quality capabilities
Based on well-established research on data quality
Timelineness, uptodate, free-of-error, cleaning, consistency,
completeness, domain-specific metrics, etc.
We mainly support the specification of QoD metrics for the whole
DaaS but possible to extend to the service operation level
Data Security/Privacy capabilities
Data protection within DaaS, e.g. encryption, sensitive data
filtering, and data privacy
Many terms are based on the W3C P3P
ASE WS 2012 28

29. Capability concerns (2)
Auditing capabilities
Logging, reporting (e.g., daily, weekly, and monthly),
and warning
Support system maintenance, SLA monitoring, billing,
and taxation
Data lifecycle
Backup/recovery, distribution (e.g., a service is in
Europe but data is stored in US), and disposition
Support system maintenance but also regulation on
data
ASE WS 2012 29

30. Capability concerns (3)
Data and service license
Usage permission: for data (distribution, transfer,
personal use, etc.) and for service APIs (adaptation,
composition, derivation, etc.)
We utilize some terms from ODRL/ODRL-S
Copyrights
Liability: e.g., who is reponsible for the loss due to a
network disruption?
Law enforcement (e.g., US or European court)
Domain specific Intellectural property rights
ASE WS 2012 30

31. Data source concerns
A DaaS may utilize data from many sources.
Similar DaaSs may utilize data from the same source
Data source properties
Name: e.g. ddfFlus or DataFlux
Size
Timespan: the duration of collected data,
Update Frequency: how offen the data is updated
etc
ASE WS 2012 31

32. Service context concerns
Location:
Selecting a DaaS in Amazon US Zone or European Zone?
Service Type: REST or SOAP?
Level of Service
Service Classification
Based on UNSPSC Code Classification Services
Data Classification
Service/data versioning
ASE WS 2012 32

33. XML Diagram for the DaaS
capability specification
ASE WS 2012 33 33

34. XML Diagram for DaaS specification
ASE WS 2012 34

35. From capability/context to
DaaS contract
Search Define and
properties of negotiate contract Contracts
DaaSs terms
DaaS Capabilities,
Context, Data Consumer-specific
35 concerns
Source
A DaaS contract includes a set of generic, data-
specific and service-specific conditions established
based on concerns
ASE WS 2012 35

36. Recall -- stakeholders in data
provisioning
Data Provider
• People
(individual/crowds/org
anization)
• Software, Things
Service Provider
Data Assessment • Software and people
• Software and
people
Data
Data Consumer
Data Aggregator/Integrator • People, Software,
• Software Things
• People + software
ASE WS 2012 36

37. Populating DaaS concerns
The role of stakeholders in the most trivial view
Data
Consumer
Data Provider
evaluate, specify, Data
publish and manage Aggregator/Integrator
Service Provider
specify, select,
monitor, evaluate
DaaS
Concerns
monitor and
evaluate
Data
Assessment
ASE WS 2012 37

38. Support DaaS concerns selection
Data SECO2
Consumer
DeXIN
Service Information
Management
Service
SEMF-based External
information, including sources
concerns
1. Muhammad Intizar Ali, Reinhard Pichler, Hong Linh Truong, Schahram Dustdar: Data Concern Aware Querying
for the Integration of Data Services. ICEIS (1) 2011: 111-119
2. Marco Comerio, Hong Linh Truong, Flavio De Paoli, Schahram Dustdar: Evaluating Contract Compatibility for
Service Composition in the SeCO2 Framework. ICSOC/ServiceWave 2009: 221-236
ASE WS 2012 38

39. Implementation (1)
Check http://www.infosys.tuwien.ac.at/prototyp/SOD1/dataconcerns
39

40. Implementation (2)
 Data privacy concerns are annotated with WSDL
and MicroWSMO
40

41. Implementation (3)
Michael Mrissa, Salah-Eddine Tbahriti, Hong Linh
Truong: Privacy Model and Annotation for
DaaS. ECOWS 2010: 3-10
 Joint work with
http://infochimps.org/datasets/twitter-haiti-earthquake-data
41

42. Some Studies
 We are not aware of any provider that publishes
DaaS‘s concerns in a well-defined form
 Mainly in HTML
 Our studies examines the description of DaaSs
 Enterprising computing
 StrikeIron, Xignite, serviceobjects.NET, WebserviceX,
XWebServices, AERS, Amazon
 E-science
 GBIF (Global Biodiversity Information Facility), EBI
(European Bioinformatics Institute) Web Services,
EMBRACE Service Registry, and BioCatalogue
ASE WS 2012 42

43. 0
5
10
15
20
25
30
35
Completeness
Uptodate
94
Correctness
Cleaning
Standard output
Privacy
based
ASE WS 2012
Logging
Reporting
Warning
Backup
Response Time
Availability
Network Latency
Packet Loss
Network Security
Price Model
43
Service Credit
Usage Permission
Copyright
Liability
Law Enforcement
Domain-specific IPR
Location
Service Type
Data Classification
Data Source Name
Data Source Size
Concerns in HTML descriptions
Data Source Update Freq.
 29 services from 7 providers, most are SOAP-
Hong Linh Truong, Schahram Dustdar On analyzing and specifying concerns for data as a service. APSCC 2009: 87-
Mentioned
Not mentioned/clear

44. Concerns of DaaSs in E-science
From the DaaS description point of view
Service Registries DQ QoS Business Licensing
Ownership Usage
permission
GBIF No No No unstructured unstructured
EBI Web Services No No No No No
EMBRACE Service No No No No No
Registry
BioCatalogue No No unstructured unstructured unstructured
Hong Linh Truong, Schahram Dustdar On analyzing and specifying concerns for data as a service. APSCC 2009: 87-
94
ASE WS 2012 44

45. Discussion time
WHAT CAN WE DO MORE
WITH INFORMATION ABOUT
DAAS CONCERNS?
ASE WS 2012 45

46. Exercises
 Read mentioned papers
 Visit DaaS mentioned in previous lectures
 Analyze existing DaaS concerns
 Examine how they specify and publish concerns
 Investigate possible concerns when merging
data from different types of DaaS
 Open government data and near-realtime data from
sensors
ASE WS 2012 46

47. 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
ASE WS 2012 47