Paper Info
Title
ViDeTTe Interactive Notebooks
Abstract
Interactive notebooks allow the use of popular languages, such as python, for composing data analytics projects. The interface they provide, enables data scientists to import data, analyze them and compose the results into easily readable report-like web pages, that can contain re-runnable code, visualizations and textual description of the entire process, all in one place. Scientists can then share such pages with other users in order to present their findings, collaborate and further explore the underlying data. However, as we show in this work, interactive notebooks lack in interactivity for the reader of the resulting notebook. Users can rerun or extend the code included in a notebook but cannot directly interact with the generated visualizations in order to trigger additional computation and further explore the underlying data. This means that only code-literate readers can further interact with and extend such notebooks, while the rest can only passively read the provided report. This comes in stark contrast to OLAP data cube interfaces, which utilize user interaction to trigger additional data exploratory capabilities. Adding OLAP-like reactive functionality in notebooks further increases the required technical expertise as event-driven logic has to be added by the data analyst. To address these issues, we propose ViDeTTe1, an engine that enhances notebooks with capabilities that benefit both data scientists and non-technical notebook readers. ViDeTTe uses a declarative language that simplifies data retrieval and data visualization for analysts. The generated visualizations are capable of collecting the reader's input and reacting to it. As the user interacts with the visualizations, ViDeTTe identifies subsequent parts of the notebook that depend on the user's input, causes reevaluation of the affected computations and propagates changes to the visualization units. By doing this, ViDeTTe offers enhanced data exploratory capabilities to readers, without requiring any coding skills, while at the same time lowering the technical expertise needed for the development of reactive notebooks.
Year
DOI
Venue
2018
10.1145/3209900.3209907
HILDA@SIGMOD
Keywords
DocType
ISBN
Jupyter Notebooks, Reactive Visualizations, Data Exploration
Conference
978-1-4503-5827-9
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Konstantinos Zarifis100.34
Yannis Papakonstantinou25657837.56