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+---
+title: "Smallset Timelines for Communicating Data Preprocessing Decisions"
+description: "Data preprocessing is messy and nuanced but full of consequential decisions, a cartoon strip can be generated for your preprocessing to help understanding and reproduction."
+date: "2024-11-18"
+draft: false
+categories:
+  - "research"
+tags:
+  - "visualisation"
+  - "data"
+  - "integratedAI"
+---
+
+##### Posted by _Lexing Xie_ and _Lydia Lucchesi_.
+
+<br/>
+<figure class="asn-fig asn-left" style="max-width: 200px;">
+    <img src="https://github.com/lydialucchesi/smallsets/blob/main/man/figures/hex_sticker.png">
+</figure>
+Smallset Timelines, and the associated [R package](https://cloud.r-project.org/web/packages/smallsets/index.html) [smallsets](https://lydialucchesi.github.io/smallsets/), faciliate visual documentation of data preprocessing. 
+
+<!--more-->
+
+<br/>
+
+Data preprocessing is a crucial intermediate stage in quantitative data analysis. During this stage, data practitioners decide how to resolve dataset issues and transform, clean, and format the dataset(s). It
+can be a challenging stage, full of decisions that have the potential to influence analytical outcomes. Yet, data preprocessing is often treated as behind-the-scenes work and overlooked in research dissemination. This discrepancy, in the practice and presentation of data analytics,
+is limiting when it comes to replicating, interpreting, and utilising research outputs.
+
+<br/>
+
+The two central contributions in [Lydia's 2024 PhD Thesis](https://lydialucchesi.github.io/thesis/thesis_LydiaLucchesi.pdf) are Smallset Timelines and smallsets. The Smallset Timeline is a static
+and compact visualisation, documenting the sequence of decisions in a preprocessing pipeline;
+it is composed of small data snapshots of different preprocessing steps. The smallsets software builds a Smallset Timeline from a user’s data preprocessing script, containing structured
+comments with snapshot instructions. Together, Smallset Timelines and smallsets are designed to support the production of accessible data preprocessing documentation. 
+
+This post illustrates these contributions with four examples, along with an example notebook that produces them. 
+
+1. <a href="#EX1">Ebirds data in citizen science</a>
+1. <a href="#EX2">HMDA homeloan data, reflecting nuances in defining and reporting on race</a>
+1. <a href="#EX3">Examining fairness in income classification from American Community Survey</a>
+1. <a href="#EX4">NASA software defect data</a>
+
+We will conclude this overview with <a href="#notebook">an example notebook</a> to illustrate the ease of using smallsets in exisitng data-preprocessing code, along with an <a href="#faq">FAQ</a>.
+
+<h5 id="EX1"></h5>
+
+#### **Example 1: Ebirds Data in Citizen Science**
+
+<figure class="asn-fig asn-left" style="max-width: 750px;">
+    <img src="/img/smallset/ebird.png">
+</figure>
+
+
+<br/>
+
+<h5 id="EX2"></h5>
+
+#### **Example 2: HMDA Homeloan Data - Nuances in Defining and Processing Race**
+
+<figure class="asn-fig asn-left" style="max-width: 750px;">
+    <img src="/img/smallset/hmda_A.png">
+</figure>
+
+<figure class="asn-fig asn-left" style="max-width: 750px;">
+    <img src="/img/smallset/hmda_B.png">
+</figure>
+
+
+<h5 id="EX3"></h5>
+
+#### **Example 3: Examining Fairness in Income Classification**
+
+
+<figure class="asn-fig asn-left" style="max-width: 550px;">
+    <img src="/img/smallset/acs.png">
+    <figcaption>
+     Smallset Timeline of ACS California data preprocessed with the validity-median
+setting. Smallset selected with random sampling. The preprocessing script and smallsets
+code for this figure are in the code section <a href="#notebook">below</a>.
+    </figcaption>
+</figure>
+
+<figure class="asn-fig asn-left" style="max-width: 550px;">
+    <img src="/img/smallset/fairness.png">
+    <figcaption>
+    The effect of four different preprocessing settings on data and prediction. Plot
+a) shows dataset imbalance by gender. Plots b) and c) show group fairness measures in predictions from a logistic regression model. Error bars refer to 95% Newcombe intervals. 
+    </figcaption>
+</figure>
+
+<h5 id="EX4"></h5>
+
+#### **Example 4: A widely-used dataset of software defects**
+
+<figure class="asn-fig asn-left" style="max-width: 750px;">
+    <img src="/img/smallset/gray_general.png">
+</figure>
+
+
+<h5 id="notebook"></h5>
+
+#### **Example notebook for the fairness example**
+
+<figure class="asn-fig asn-left" style="max-width: 550px;">
+    <img src="/img/smallset/notebook1.png">
+</figure>
+
+<figure class="asn-fig asn-left" style="max-width: 550px;">
+    <img src="/img/smallset/notebook2.png">
+</figure>
+
+<h5 id="faq"></h5>
+
+#### **FAQ** (detailed answers coming soon, new questions most welcome)
+
+* _Will smallsets automate data-preprocessing?_  In short, no. 
+* _Is Python code supported?_ Yes, in ipython notebooks.
+* _Will smallsets support preprocessing code across different scripts?_ Not yet. 
+* _Will smallsets support word embeddings, large language models and the like?_  Not yet, let us know what you think are important to support. 
+
+<br/>
+
+#### **Resources**
+
+* [Smallset Timelines: A Visual Representation of Data Preprocessing Decisions](https://arxiv.org/abs/2206.04875), Lydia R. Lucchesi, Petra M. Kuhnert, Jenny L. Davis, and Lexing Xie, Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 2022
+<h5 id="thesis"></h5>
+* [Visualisation and Software to Communicate Data Preprocessing Decisions](https://lydialucchesi.github.io/thesis/thesis_LydiaLucchesi.pdf), Lydia R. Lucchesi, PhD Thesis, The Australian National University, 2024