Shared Access to Spreadsheet Elements for End User Programming

Spreadsheets are the best-known form of End User Programming. End-user programmers (EUP) write programs, but not as their primary job function. They frequently develop software to perform tabular data visualization and analytics using spreadsheets and spreadsheets' formulas as a general purpose...

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Bibliographic Details
Published in:2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) pp. 1571 - 1572
Main Authors: Camera, Giancarlo, Baglietto, Pierpaolo, Maresca, Massimo
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2018
Subjects:
Access control
Aerospace electronics
Clocks
Collaboration
collaborative analytics
collaborative working
computer supported collaborative work
Distributed databases
Servers
Software
ISSN:2575-8411
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Summary:Spreadsheets are the best-known form of End User Programming. End-user programmers (EUP) write programs, but not as their primary job function. They frequently develop software to perform tabular data visualization and analytics using spreadsheets and spreadsheets' formulas as a general purpose programming language. Recently spreadsheets shifted from personal office tools aimed at improving people productivity to enterprise level tools aimed at supporting distributed analytics and decisions. Distributed analytics often requires data sharing among different processes. The spreadsheet supported distributed analytics poses new challenges in spreadsheet data sharing. As in mainstream programming environments, end user spreadsheet programmers need an efficient way to handle shared data access inside spreadsheets to perform collaborative analysis of data. We propose a solution that focuses on spreadsheet element data sharing and collaboration instead of file sharing and collaboration. We present a distributed end to end encrypted tabular data sharing platform called Spreadsheet Space that supports end user programmers for fine grained spreadsheet element data sharing for collaborative analytics.
ISSN:2575-8411
DOI:10.1109/ICDCS.2018.00172