Rui Pereira, Jácome Cunha, João Paulo Fernandes,and João Saraiva

Graphical Querying of Model-Driven Spreadsheets

HCI International '14Crete, June 2014

Problem: Querying Spreadsheets

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› “poor man’s database”› Have no way to query what data they contain

Spreadsheets are generally used to store information

Attempts to replicate traditional querying systems

› Highly restrict user’s spreadsheet data› Denormalization › Headers present› Column letters ≠ Column labels› Data evolution not support

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Budget Spreadsheet

Question – What was the total per year, in decreasing order, from 2010 onwards?

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Google QUERY Function

Question – What was the total per year, in decreasing order, from 2010 onwards?

=query(A1:E53;”SELECT A, sum(E) WHERE A >= 2010 GROUP BY A ORDER BY sum(E) DESC”)

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QuerySheet

Question – What was the total per year, in decreasing order, from 2010 onwards?

SELECT Year, sum(Total)WHERE Year >= 2010GROUP BY YearOrder BY sum(Total) DESC

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Previous Empirical Study

› Easier to construct queries› Intuitive and Understandable queries› Productive/Faster

Our goal with Model-Driven Querying:

› Semantic errors› Syntax errors› Low SQL knowledge Construction still difficult

Recurring problem among participants:

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Graphical-QuerySheet

› Guide end-users in constructing queries› Reduce number of errors› Based off of spreadsheet model› Continue taking advantage of positive aspects of

QuerySheet

Graphical Model-Driven Querying

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Graphical-QuerySheet

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Empirical Study

› Easier to construct queries› Intuitive and Understandable queries› Productive/Faster› Guide the user to construct queries› Eliminate possible syntax errors› End-user friendly (no SQL knowledge needed)

Our goal with Graphical Model-Driven Querying:

› Google QUERY function vs. Graphical-QuerySheet

Planned and executed a Comparative Usability Study

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Empirical Study

› Information on distributions of (14) products and (85) institutions

› Over 1190 lines of unique information

Spreadsheet from Braga Food-Bank

› Part I – Query Tasks› Part II – Post-Task Questionnaire› Part III – Post-Study Questionnaire

Study consisted of 3 parts:

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Empirical Study

› Consisted of 4 tasks (questions) pertaining to food-bank data

› Alternatively switching between each system for each question› Write down time after reading the question › Write down time after answering the question › Repeat process for the other system

Part I – Query Tasks

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Empirical Study

› User chose which system (or neither) they felt was more:› Intuitive› Faster (to construct the queries)› Easier (to construct the queries)› Understandable (to fully explain and interpret)

Part II – Post-Task Questionnaire

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Empirical Study

› Two questions:› “Which system did you prefer and why?”› “What advantages/disadvantages do you feel exist between

the systems?”

Part III – Post-Study Questionnaire

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Empirical Study

› Ages between 19-28› Masters and PhD Students› Computer Sciences/Informatics/Bioinformatics/Economics› Varying levels of SQL knowledge

7 participants with some previous exposure to SQL

› A tutorial teaching how to use both systems› A series of query solving exercises using both systems› Data denormalized (for GQF system)› Model created (for QuerySheet system)

Before running the study

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Empirical Study – Results (Part I)

› Users spent 65.5% - 89.9% less time using Graphical-QuerySheet

› Average of 79.4% improvement (up from 67.5%)

› 6 with GQF› 1 with QuerySheet

Error rates – out of 7 total errors

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Empirical Study – Results (Part II)

› 104 out of 112 (4 points * 4 questions * 7 participants)

Almost all chose the model-driven query approach

› Felt it was easier to read a continuous line of text, than jump around a graphical interface to “read information”

› Maybe habit? (They were computer science students after all)

6 out of 112 cases, participants preferred GQF

› Question 4 – many clauses were needed to answer› Equally difficult due to having to use many conditions

2 out of 112 cases preferred neither

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Empirical Study – Results (Part III)

All preferred Graphical-QuerySheet

› “No need to know SQL, a normal user like myself can quickly and easily construct queries”

› “I do not need to worry about using group by when I aggregate”

› “Very intuitive, quick, and presents an attractive and easy to use interface”

Comments:

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Interesting Things

› The selection tree-list was believed to be a “perfect” representation of the model

› Felt no need whatsoever to look at the model› Felt selecting list was “enough”

Users did not look at spreadsheet model (after initial look) in the study. Why?

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Interesting Things

› Felt as awkward by the more experienced SQL users› Felt intuitive by the less experienced SQL users

Choosing an attribute to use the Order By option

Why?

› Less experienced SQL users = more abstraction from SQL syntax

› More experienced SQL users = viewed the result view as “Select Clause”

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Conclusions

› Balance of expressability and simplicity› Users continued to be much faster using model-driven

spreadsheet querying

Model-driven querying proven to be much more efficient

Users with less SQL experience have an easier time with the graphical approach

Some users with more SQL experience “still held on to their roots”

› Albeit admitted to preferring graphical approach

Rui Pereira, Jácome Cunha, João Paulo Fernandes,and João Saraiva

Graphical Querying of Model-Driven Spreadsheets

HCI International '14Crete, June 2014