The document proposes a solution to improve querying of spreadsheet data. Currently, spreadsheet querying is limited as it requires data to be in a tabular format with headers in the first row. The proposed solution models spreadsheet data and allows more intuitive queries that are not constrained by the data structure. It demonstrates querying profit by client from a sample order spreadsheet. The solution takes advantage of Google query functions while adding functionality like supporting evolved data structures. It aims to automatically structure data for querying and handle problems of querying denormalized data.

1. Supervised by:
Prof. Dr. João Alexandre Saraiva
Prof. Dr. Orlando Manuel Belo
Rui Alexandre Afonso Pereira
Querying SpreadSheets

2. Problem: Querying Spreadsheets
• Spreadsheets are generally used to store
information
• Much like database systems
• Have no way to query what data they contain
• Attempts have been made to replicate traditional
querying systems for spreadsheets
• MS-Query
• Google QUERY Function

3. Problem: Querying Spreadsheets
• Highly restrict user’s spreadsheet data
• Requires data to be in a tabular format
• Requires headers to be present (in first
row)
• Column letters ≠ Column labels
• Counter intuitive queries
• Data evolution not supported

4. Proposed Solution: Example

5. Proposed Solution: Example
• Model-Driven spreadsheet representing
orders, clients, and products

6. Proposed Solution: Example
• Spreadsheet data

7. Proposed Solution: Example
• Query: How much have we profited from
each client?

8. Proposed Solution: Example
Google QUERY Function :
Denormalization

9. Proposed Solution: Example
• Google Query:
Google QUERY Function :

10. Proposed Solution: Example
• Proposed Query:
Proposed Solution:

11. Proposed Solution: Example
Proposed Solution:

12. Proposed Solution: Example
Results:
• Query: How much have we profited from
each client?

13. Recap

14. Recap
• Take advantage of the powerful Google query engine
while adding extra functionality
• Allow more humanized queries
• Have ClassSheets supported
• Automatically structure the data into the needed
format
• Automatically deal with problems caused by
denormalized data querying
Not to reinvent the wheel

15. Architecture

16. Architecture

17. Demonstration

18. Demonstration

19. Future Work

20. Future Work
• Incremental Denormalization
• Integration of ClassSheet Inference
• Spreadsheet Synchronization
• Empirical Evaluations

21. Publications

22. Publications
• QuerySheet: A Bidirectional Query Environment for Model-Driven
Spreadsheets. Orlando Belo, Jácome Cunha, João Paulo Fernandes, Jorge
Mendes, Rui Pereira and João Saraiva. In proceedings of the IEEE
Symposium on Visual Languages and Human-Centric Computing
(VL/HCC’13), San Jose, CA, USA, September 15–19, 2013. IEEE
Computer Society, Showpieces paper. (to appear)
• Querying Model-Driven Spreadsheets, Jácome Cunha, João Paulo
Fernandes, Jorge Mendes, Rui Pereira, João Saraiva. In proceedings of the
IEEE Symposium on Visual Languages and Human-Centric Computing
(VL/HCC’13), San Jose, CA, USA , September 15–19, 2013. IEEE
Computer Society. (to appear)

23. Mulțumesc 