This document proposes techniques for exchanging data agreements in data-as-a-service (DaaS) models and cloud-based data marketplaces. It develops a metamodel for representing data agreements and techniques for associating agreements with data assets. An interaction model and Data Agreement Exchange as a Service (DAES) are proposed to facilitate agreement exchange. Examples illustrate inserting agreements in data assets and linking agreements to geospatial data provided by DaaS. Future work includes integrating DAES with data contracts and a data marketplace prototype.

1. Exchanging Data Agreements in the
DaaS Model
Hong-Linh Truong1, Schahram Dustdar1, Joachim Goetze2,
Tino Fleuren2, Paul Mueller2, Salah-Eddine Tbahriti3, Michael
Mrissa3, Chirine Ghedira3
1
Distributed Systems Group, Vienna University of Technology
2
Department of Computer Science, University of Kaiserslautern
3
Universite de Lyon, CNRS, Universite Lyon 1
truong@infosys.tuwien.ac.at
http://www.infosys.tuwien.ac.at/Staff/truong
APSCC 2011, 12 Dec, 2011, Jeju, Korean

2. Outline
 Background and motivation
 Our approach
 Techniques for data agreements exchange
 Prototype and illustrative examples
APSCC 2011, 12 Dec, 2011, Jeju, Korean

3. Background
 Emerging data-as-a-service and on-demand data
provisioning in cloud-based data marketplaces
 Rich data concerns associated with data assets
 Dynamic interactions within data marketplaces
Data consumer DaaS provider Data provider
Data marketplaces quality1
DaaS quality2
Consumer
DaaS privacy1
DaaS
privacy2
Sensor
APSCC 2011, 12 Dec, 2011, Jeju, Korean

4. Motivation
 Lack of models and protocols for data agreement
in data marketplaces
 Constraints for data usage are not clear
 Inadequate data/service description → hindering data
selection and integration
 Existing techniques are not adequate for dynamic
data agreement exchange in data marketplaces
Our work: developing generic exchange models
suitable for different ways of data provisioning in
data marketplaces
APSCC 2011, 12 Dec, 2011, Jeju, Korean

5. Our approach
 Develop metamodel for data agreement
exchange
 Investigate techniques for enriching and
associating data assets with agreement terms
 Develop interaction models for data agreement
exchange
 Develop Data Agreement Exchange as a
Service (DAES)
APSCC 2011, 12 Dec, 2011, Jeju, Korean

6. Metamodel for data agreements
 Different category
of agreements
 Licensing,
privacy, quality of
data
 Extensions
 Languages
 Different types of
agreements
 Different
specifications
APSCC 2011, 12 Dec, 2011, Jeju, Korean

7. Associating data with data
agreements
 Solutions
 (a) directly inserting agreements into data assets
 (b) providing two-step access to agreements and data assets
 (c) linking data agreements to the description of DaaS
 (d) linking data agreements to the message sent by DaaS
APSCC 2011, 12 Dec, 2011, Jeju, Korean

8. Possible interaction models for data
enriched with data agreements
APSCC 2011, 12 Dec, 2011, Jeju, Korean

9. DAES – conceptual architecture
 Jersey, JAX-RS Restful WS Weblogic
 Using URIs to identify agreements
APSCC 2011, 12 Dec, 2011, Jeju, Korean

10. DAES – managed information
 Specific applications: agreement creation, agreement validation,
agreement compatibility analysis, agreement management
 Implementation: Jersey, JAX-RS Restful WS Weblogic
APSCC 2011, 12 Dec, 2011, Jeju, Korean

11. Illustrating examples – insert
agreement into data asset
 A pay-per-use consumer uses dataAPI of DaaS
search for data
 The consumer pays the use APIs
 Each call can return different types of data
Example with
People Search in
Infochimps
But a strong
consequence for data
service engineering
techniques: dealing with
elastic requirements!
APSCC 2011, 12 Dec, 2011, Jeju, Korean

12. Illustrating examples – link
agreements to geospatial data
 Domain-specific DaaS: different agreements for different data requests
 Vector data of geographic features via Web-Feature-Service (WFS)
 Terrain elevation data via Web-Coverage Services (WCS)
APSCC 2011, 12 Dec, 2011, Jeju, Korean

13. Illustrating examples – link
agreements to geospatial data
Consumers can interpret
and reason if the data
can be used for specific
purposes
APSCC 2011, 12 Dec, 2011, Jeju, Korean

14. Illustrative examples – develop an
app for policy compliance
Configuration
Results
APSCC 2011, 12 Dec, 2011, Jeju, Korean

15. Conclusions and future work
 Dynamic data provisioning in DaaS/data marketplaces
need new models and techniques for data agreement
exchange
 We present
 Models and interactions for data agreement exchange
 Data Agreement Exchange Service (DAES)
 Data agreement is not just “data licensing”!
 Future work
 Integrate DAES with data contracts [another paper in
APSCC 11]
 Integrate DAES with DEMODS ([AINA 2012])
APSCC 2011, 12 Dec, 2011, Jeju, Korean

16. Thanks for your attention!
Hong-Linh Truong
Distributed Systems Group
Vienna University of Technology
Austria
truong@infosys.tuwien.ac.at
http://www.infosys.tuwien.ac.at/staff/truong
APSCC 2011, 12 Dec, 2011, Jeju, Korean