B2: Bridging code and interactive visualization in computational notebooks
© 2020 Owner/Author. Data scientists have embraced computational notebooks to author analysis code and accompanying visualizations within a single document. Currently, although these media may be interleaved, they remain siloed: interactive visualizations must be manually specified as they are divor...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
ACM
2021
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| Online Access: | https://hdl.handle.net/1721.1/137497 |
| _version_ | 1826189972716126208 |
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| author | Wu, Y Hellerstein, JM Satyanarayan, A |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Wu, Y Hellerstein, JM Satyanarayan, A |
| author_sort | Wu, Y |
| collection | MIT |
| description | © 2020 Owner/Author. Data scientists have embraced computational notebooks to author analysis code and accompanying visualizations within a single document. Currently, although these media may be interleaved, they remain siloed: interactive visualizations must be manually specified as they are divorced from the analysis provenance expressed via dataframes, while code cells have no access to users' interactions with visualizations, and hence no way to operate on the results of interaction. To bridge this divide, we present B2, a set of techniques grounded in treating data queries as a shared representation between the code and interactive visualizations. B2 instruments data frames to track the queries expressed in code and synthesize corresponding visualizations. These visualizations are displayed in a dashboard to facilitate interactive analysis. When an interaction occurs, B2 reifies it as a data query and generates a history log in a new code cell. Subsequent cells can use this log to further analyze interaction results and, when marked as reactive, to ensure that code is automatically recomputed when new interaction occurs. In an evaluative study with data scientists, we find that B2 promotes a tighter feedback loop between coding and interacting with visualizations. All participants frequently moved from code to visualization and vice-versa, which facilitated their exploratory data analysis in the notebook. |
| first_indexed | 2024-09-23T08:33:04Z |
| format | Article |
| id | mit-1721.1/137497 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T08:33:04Z |
| publishDate | 2021 |
| publisher | ACM |
| record_format | dspace |
| spelling | mit-1721.1/1374972023-03-29T19:13:35Z B2: Bridging code and interactive visualization in computational notebooks Wu, Y Hellerstein, JM Satyanarayan, A Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory © 2020 Owner/Author. Data scientists have embraced computational notebooks to author analysis code and accompanying visualizations within a single document. Currently, although these media may be interleaved, they remain siloed: interactive visualizations must be manually specified as they are divorced from the analysis provenance expressed via dataframes, while code cells have no access to users' interactions with visualizations, and hence no way to operate on the results of interaction. To bridge this divide, we present B2, a set of techniques grounded in treating data queries as a shared representation between the code and interactive visualizations. B2 instruments data frames to track the queries expressed in code and synthesize corresponding visualizations. These visualizations are displayed in a dashboard to facilitate interactive analysis. When an interaction occurs, B2 reifies it as a data query and generates a history log in a new code cell. Subsequent cells can use this log to further analyze interaction results and, when marked as reactive, to ensure that code is automatically recomputed when new interaction occurs. In an evaluative study with data scientists, we find that B2 promotes a tighter feedback loop between coding and interacting with visualizations. All participants frequently moved from code to visualization and vice-versa, which facilitated their exploratory data analysis in the notebook. 2021-11-05T14:57:08Z 2021-11-05T14:57:08Z 2020 2021-01-29T20:03:24Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137497 Wu, Y, Hellerstein, JM and Satyanarayan, A. 2020. "B2: Bridging code and interactive visualization in computational notebooks." UIST 2020 - Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. en 10.1145/3379337.3415851 UIST 2020 - Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf ACM ACM |
| spellingShingle | Wu, Y Hellerstein, JM Satyanarayan, A B2: Bridging code and interactive visualization in computational notebooks |
| title | B2: Bridging code and interactive visualization in computational notebooks |
| title_full | B2: Bridging code and interactive visualization in computational notebooks |
| title_fullStr | B2: Bridging code and interactive visualization in computational notebooks |
| title_full_unstemmed | B2: Bridging code and interactive visualization in computational notebooks |
| title_short | B2: Bridging code and interactive visualization in computational notebooks |
| title_sort | b2 bridging code and interactive visualization in computational notebooks |
| url | https://hdl.handle.net/1721.1/137497 |
| work_keys_str_mv | AT wuy b2bridgingcodeandinteractivevisualizationincomputationalnotebooks AT hellersteinjm b2bridgingcodeandinteractivevisualizationincomputationalnotebooks AT satyanarayana b2bridgingcodeandinteractivevisualizationincomputationalnotebooks |