1. Research on Personal Dataspace Management
Yukun Li
Renmin University of China

2. Outline Introduction Related work Research work
OrientSpace: A prototype system
Ongoing work
Conclusions

3. Introduction Information explosion Information islands
In 1945, Vannevar Bush predicted Personal Information Managemant Will become a serious problem. Today it comes into being…
Information explosion
Information islands

4. Introduction (Example)
Where is it?
My God, I forgot it!
Distributed Storage
Information island 4

5. Outline Introduction Related work CoreSpace based Framework for PDS
OrientSpace: A prototype system
Ongoing work
Conclusions

6. Related work Concepts [PIM workshop2005 report] Personal dataspace
- From databases to dataspaces. [Franklin M, etc SIGMOD Record, 2005]
- Principles of dataspace systems [Halevy A ,etc. In PODS2006]
- Data model: iDM [Dittrich J-P and Salles MAV…,VLDB 2006]
Systems of personal data management
- iMemex[L. Blunschi, J.-P. Etc . In CIDR, 2007]
- Semex[X. Dong and A. Halevy. In CIDR 2005]
- Others
Systems for special data source management
- data management
- Desktop Search Engine

7. Related work The performance of personal data operation is still slow.
The characters of personal dataspace are not modeled well.
Components:
Owner entity, Data Set, Service
Attributes of Personal Dataspace
Correlation, Controllable
Characters:
Versatile data sources
From data to schema
Pay-as-you-go
Others
The characters of user may be the key factor to improve the performance of data operation.

8. Outline Introduction Related work Research work
OrientSpace: A prototype system
Ongoing work
Conclusions

9. Research work User-centered framework for PDS
CoreSpace of personal dataspace
CoreSpace Query Strategy 9

10. Research Work A User-Centered Framework for PDS
The characters of user may be the key factor to improve the performance of data operation.

11. Research Work Observation
The personal data is always distributed,
rough-and-tumble, personalized, heterogenous and evolutionary.
But, are there some rules or patterns in the PDS? If the answer is yes, What are them?
Observations:
-Importance of objects are always different.
-Importance of a certain object is dynamic.
-People tend to visit a small data set in a period.

12. Research Work CoreSpace
Two concepts :
Object Weight (OW)
Personal CoreSpace (PCS)
Object Weight: To describe relation between the object and the owner, it can be defined as possibility that the object will be accessed in the future.
Personal CoreSpace: It consists of the objects which OW is bigger than a given threshold. On the opposite, the full space of a person is made up of all objects with relation to the owner.

13. Research Work Preliminary experience
Real personal data of three months
Visited object number vs. Totle object number
VisiteTime based object number

14. Research work ObjectWeight Computing(1)
The features which will affect OW as below:
- FileType
- FileModifyTime
- FileAccessFrequency
- FileOwner
- Personal Task
- Association Between objects

15. Research Work ObjectWeight Computing(2)
VF : Visit frequency
It is described with visit times in a day
S: an attenuation factor.

16. Research work More advantages of the concepts
Data integration (ObjectWeight > 0)
Data query (Scanning CoreSpace is enough in most cases)
Data Indexing (Different strategies for Indexing CoreSpace and FullSpace )
Data Backup (Corespace-based backup strategy)

17. Research work CoreSpace-based Query Strategy
Query Interface{ [attribute\\[keyword]*]*, K }
f.g. “Title\\integration, uncertain" .
It means "Please tell me the objects whose title contain the words Integration and and uncertain".

18. Outline Introduction Related work CoreSpace based Framework for PDSMS
OrientSpace: A prototype system
Ongoing work
Conclusions

19. OrientSpace Functions
Integration
- Manual integration
- Automatic integration
Query
- Extend Keyword Query
- Results-based Navigation
- CoreSpace explorer

20. OrientSpace Data Storage(vertical model)
Oid
Attribute
Value A1
Name
Mike A2
Jone P1
Class
paper
Title
‘Index Database’
Author P2
‘Data stream…’
reference P3
‘Mining …’
class E1
attachment
Advantages: An universal model to describe any object.
Question: A great number of join operation lead to low performance.

21. Outline Introduction Related work CoreSpace based Framework for PDSMS
OrientSpace: A prototype system
Ongoing work
Conclusions

22. Ongoing work ObjectWeight Computing
- Computing Model of OW
- Data set
ObjectWeight based Data Operation Strategy
- Integration, Backup, Query, Consistency, etc.
OrientSpace Systems

23. Outline Introduction Related work CoreSpace based Framework for PDSMS
OrientSpace: A prototype system
Ongoing work
Conclusions

24. Conclusions
Propose a new concept CoreSpace for PDS. It will result in many research issues including index, integration, storage, backup, query and so forth.
The following topics will be focused on in my PhD project
User-centered data model (CoreSpace)
CoreSpace-based Data Operation(Query)
Implement a prototype system

25. Thanks, Questions ?

26. A Framework for Integration of PDS

27. Main Interface of OrientSpace

28. Wrapper-based Integration

29. From Data to Schema Integration

30. Personal CoreSpace Explorer