1 Context-based Exploitation of Data Warehouses Yeow Wei Choong 1, Dominique Laurent 2, Arnaud Giacometti 3, Patrick Marcel 3, Elsa Negre 3, Nicolas Spyratos 4 1: HELP University College, Kuala Lumpur, Malaysia 2: ETIS, Université de Cergy-Pontoise, France 3: LI, Université François-Rabelais de Tours, France 4: LRI, Université Paris-Sud, France

2 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

3 Motivations and Intuitions (1) Problem: How to… Describe/exploit an analysis in an OLAP context: Launch/browse queries Organize/reuse/share an analysis Discover authorities, frequently asked queries Provide recommendations to the user

4 Motivations and Intuitions (2) Motivating example: 2 user-analysts: Elsa Yeow Wei 2 data cubes: Tourism Agriculture 1 base of analyses sessions

5 Motivations and Intuitions (3)

6 Motivations and Intuitions (4) The Query over the Context Base

7 Motivations and Intuitions (5) The Navigated Context

8 Motivations and Intuitions (6) The Edited Context

9 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

10 Our Framework The Data Level: Based on the model proposed by Theodorakis, Analyti, Constantopoulos, Spyratos (ER’99, IS 2002) Uses the relational model under the logic programming perspective The System Level: Specifies how the data can be browsed and edited

11 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

12 The Data Level: Model (1) The relations: Objects: 3-ary relation objects(o id, a, v) objects(2,’topic’,’Transport,Year’) Contexts: Binary relation contexts(c id,o id ) contexts(1,2) References: 4-ary relation references(o id1,o id2,a, v) references(2,3,’refines’,’Transport’) 2 3

13 The Data Level: Model (2) The Context Base (CB): Schema: Objects, contexts, references Instance: Finite set of facts Querying the CB: Datalog̚ under the stratified semantic to express recursion and relational division objects contexts references objects_a contexts_a references_a

14 The Data Level: Language Example of Datalog̚ program: « Objects with topic dealing with Tourism but not with Borneo» objects_a(x,’topic’,z) <- objects(x,’topic’,z), substring(z, ‘Tourism’), ¬substring(z, ‘Borneo’) objects_a(x,s,t) <- objects(x,s,t), objects_a(x,’topic’,z) contexts_a(c,x) <- objects_a(x,s,t), contexts(c,x) references_a(x,x1,y1,z1) <- objects_a(x,s,t), references(x,x1,y1,z1)

15 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

16 The System Level: Model System = Base = instance of CB State =

17 The System Level: Language (1) Navigation system operations Operators to change the navigated object Operator to change the set of contexts

18 The System Level: Language (2) Edition system operations Operators to create a new object Operators to add a descriptor or a reference copyObject: Duplicates the navigated object in the edited context Example

19 The System Level: Language (3) copyObject

20 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

21 Exploitation (1) Exploiting the descriptors: Descriptors associated with Objects: Topicadded and updated Codeby the user Launchedadded and updated Browsed by the system Result

22 Exploitation (2) Exploiting the descriptors: Descriptors associated with Objects: Example of use: What queries have been launched more than 10 times: objects_a(o1,a,v) 10, objects(o1,a,v) contexts_a(c,o1) 10, contexts(c,o1) references_a(o1,o2,a,v) 10, references(o1,o2,a,v)

23 Exploitation (3) Exploiting the descriptors: Descriptors associated with References: Intra-context references: Order of importance Query containment Query logs Inter-context references: Comes-from Copied-to

24 Exploitation (4) Exploiting the references: Authority, Hub, Initiator:

25 Exploitation (5) Recommendations: The idea: To exploit particular links between queries Example: What are the recommendations started from o1 ? o2o1o3a Comes-from o3b

26 Outline 1) What is the problem?: Motivations and Intuitions 2) How to deal with the problem?: Our model The Data Level The System Level 3) How to solve the problem?: Exploitation of our model Conclusion and Future work

27 Conclusion and Future work (1) Conclusion: A model for OLAP analysis: Sharing BrowsingOLAP queries Reusing Data Level: To organize OLAP queries System Level: To represent the interface and how the user can interact with the system

28 Future work: Queries as first class citizen Extending the manipulation language and the navigation language Consider other recommendations Implementing our model Conclusion and Future work (2)

29 Thanks for your attention

30 Exploitation Recommendations: Example: What are the recommendations started from o1 ? ans(o2) <- objects(o2,_,_), references(o1,o2,’copied-to’,y) objects_a(o3,a,v) <- ans(o2), references(o2,o3,z,t), objects(o3,a,v) contexts_a(c,o3) <- objects_a(o3,a,v), contexts(c,o3) references_a(o3,o4,w,x) <- objects_a(o3,a,v), objects(o4,_,_), references(o3,o4,w,x) o2o1o3a Comes-from o3b