Carnegie Mellon University in Qatar
Department of Social and Decision Science, Carnegie Mellon University
Supported by the Qatar National Research Fund


Usable automated data inference for end-users

Project Description

Nowadays, data are more easily accessible than ever, yet support for correlating base data into interesting consequences is often unavailable, or too expensive, or too technical for many users. We have designed NEXCEL, a possible solution to this problem which revolves around extending the spreadsheet paradigm to enable users to define useful forms of correlation among their data. Spreadsheets are widely available to users, already allow them to routinely define complex custom calculations on numerical data, and are easy to use productively with little or no training. However they are unable to deal with the kind of recursive relational calculations needed for many common types of data correlation problems. NEXCEL's design exploits techniques from logic programming and database theory to solve these issues.
This project has the objective of developing a matching user interface for these functionalities. A specific challenge is to retain the cognitive simplicity, ease to use and gentle learning curve of today's spreadsheet applications. The project will develop an advanced prototype of NEXCEL and perform extensive usability studies to understand how to best present the extended functionalities to interested users.
This work was funded by the Qatar National Research Fund as project NPRP 4-341-1-059 (Usable automated data inference for end-users) for an amount of $1,017,624 over 3 years.


Past members


2016 2015
2014 2013
2015 2014 2011


An advanced prototype of the deductive spreadsheet concept. It support the traditional spreadsheet metaphor inclusive of the most common operations. It integrates a full deductive engine inclusive of evaluation, update and explanation within the traditional user interface.

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