Making Database Systems Usable

1 .Making Database Systems Usable Presented by: Assma Boughoula CS 598 Fall 2017

2 .“As computer scientists, … we are not typical database users.” DB DB Admin Person User

3 .DB DB Admin Person User “As computer scientists, … we are not typical database users.”

4 .DB DB Admin Person User “As computer scientists, … we are not typical database users.” Google??

5 .Web search vs DB querying More sophisticated queries that make use of DB structure Complete & perfect precision results Structured results Ability to create/update DBs Keyword search is sufficient At least some relevant results Result is set of links

6 .What’s out there today? Visual Interface: Polaris, Zenvisage, ImMens, DataPlay? Form-based Text Interface: keyword search across tuples natural language queries & extracting hidden semantic structure of query Context & Personalization: Mine query logs to discover user characteristics Interpret queries in context of previous queries

7 .What’s out there today? Visual Interface: Polaris, Zenvisage, DataPlay? Form-based Text Interface: keyword search across tuples natural language queries & extracting hidden semantic structure of query Context & Personalization: Mine query logs to discover user characteristics Interpret queries in context of previous queries

8 .What’s out there today? Visual Interface: Polaris, Zenvisage, DataPlay? Form-based Text Interface: keyword search across tuples natural language queries & extracting hidden semantic structure of query Context & Personalization: Mine query logs to discover user characteristics Interpret queries in context of previous queries

9 .What’s out there today? Visual Interface: Polaris, Zenvisage, DataPlay? Form-based Text Interface: keyword search across tuples natural language queries & extracting hidden semantic structure of query Context & Personalization: Mine query logs to discover user characteristics Interpret queries in context of previous queries

10 .The MiMI adventure Started as application for Timber (usability not on the horizon) MiMI integrated several protein interactions DBs

11 .The MiMI adventure Started as application for Timber (usability not on the horizon) MiMI integrated several protein interactions DBs Biologists MiMI Usability Issues

12 .The MiMI adventure MiMI XQuery Form-based UI MQuery Proficient Technophobe Middle

13 .The MiMI adventure MiMI XQuery Form-based UI MQuery MiMI schema too complex …

14 .The MiMI adventure MiMI XQuery Form-based UI MQuery Schema Summary Schema-Free XQuery Some users preferred keyword search …

15 .The MiMI adventure MiMI XQuery Form-based UI MQuery Schema Summary Schema-Free XQuery Key-word based search across tuples Users misspelled keywords …

16 .The MiMI adventure MiMI XQuery Form-based UI MQuery Schema Summary Schema-Free XQuery Key-word based search Autocompletion Users wanted to use English language to query …

17 .The MiMI adventure MiMI XQuery Form-based UI MQuery Schema Summary Schema-Free XQuery Key-word based search Autocompletion NaLIX DaNaLIX Users couldn’t explore data directly in graphical setting

18 .The MiMI adventure MiMI XQuery Form-based UI MQuery Schema Summary Schema-Free XQuery Key-word based search Autocompletion NaLIX DaNaLIX Cytoscape Still: Inconsistencies between interfaces Inputting new data is difficult

19 .Why are DB systems so frustrating for users? The Five P ains: Painful Relations Painful Options Unexpected Pain Unseen Pain Birthing Pain

20 .Painful Relations Normalization is central in RDBMS, but: N o concept of “flight”  painful to locate a specific piece of data Painful to compute joins Painful to express queries across multiple tables

21 .Painful Options Too much functionality leads to: Irrelevant options competing with relevant options Regret for “paths not taken” Must simplify querying for novices & provide experts with necessary tools

22 .Unexpected Pain When users’ mental data model does not match actual data model: Unable to Query: Forced to specify date without knowing why Unexpected Results: Where it came from? Why that result? Must provide explanations to users

23 .Unseen Pain Querying requires prediction by user Prediction is difficult for novices Want WYSIWYG for DB Want query refined as it’s being typed Must shift prediction load from user to system

24 .Birthing Pain Creating/updating DBs is painful Understanding/designing DB schema is painful Final structure may be unknown Structure may be heterogeneous Must provide interfaces to easily create and fluidly manipulate the structure

25 .Which Pain still hurts? Polaris Zenvisage dbTouch Gestural Query Spec DataPlay DataSpread Painful Relations Painful Options Unexpected Pain Unseen Pain Birthing Pain