Skip to main content
Kent Academic Repository

The Gamma: Programmatic Data Exploration for Non-programmers

Petricek, Tomas (2022) The Gamma: Programmatic Data Exploration for Non-programmers. In: 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). . pp. 1-7. IEEE ISBN 978-1-66544-215-2. E-ISBN 978-1-66544-214-5. (doi:10.1109/vl/hcc53370.2022.9833134) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:96635)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
https://doi.org/10.1109/vl/hcc53370.2022.9833134

Abstract

Data exploration tools based on code can access any data source, result in reproducible scripts and encourage users to verify, reuse and modify existing code. Unfortunately, they are hard to use and require expert coding skills. Can we make data exploration tools based on code accessible to non-experts? We present The Gamma, a novel text-based data exploration environment that answers the question in the affirmative. The Gamma takes the idea of code completion to the limit. Users create transparent and reproducible scripts without writing code, by repeatedly choosing from offered code completions. The Gamma is motivated by the needs of data journalists and shows that we may not need to shy away from code for building accessible, reproducible and transparent tools that allow a broad public to benefit from the rise of open data.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/vl/hcc53370.2022.9833134
Additional information: ** From Crossref proceedings articles via Jisc Publications Router ** History: ppub 12-09-2022; issued 12-09-2022.
Uncontrolled keywords: data exploration; data journalism
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 02 Sep 2022 15:37 UTC
Last Modified: 02 Sep 2022 15:37 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/96635 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.