Tag Archives: Love Data Week

Visualizing your love for data

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This post is in celebration of the love data week between Feb-13-Feb 17, 2023. 

Analytics screen graph.
Photo by Luke Chesser on Unsplash 

What is Data visualization?  

For this author, it was love at first sight. Well, technically, it was love at first Visualization. So many say seeing is believing, and data visualization helps us accomplish that, especially at the rate at which data is increasing exponentially in our world. The truth is that data is everywhere, and for us to draw meaning from it, we need to present it in a clear and concise manner.  

Data visualization is the graphical representation of data. Data can be represented in various forms and shapes, such as maps, charts, infographics, graphs, heat maps, or sparklines. When data is presented through visual elements, it is easy to understand and analyze. It helps you to derive meaning from the data and make better decisions. Visualizing your data involves using certain tools; these tools help you fall more in love with data.  

Data Visualization tools are software that allow you to create graphical representations of your data.  

Here are some tools to help you get started. These have been selected based on their ease of use, features (such as capacity for large volumes of data), cost, and popularity.

  1. Data Wrapper: If you are just starting out with data Visualization and you are looking for a free tool to help you get started, Data wrapper is your plug. Data Wrapper is a beginner-friendly tool with a clean and intuitive user interface accessible online. It is straightforward to navigate and great for creating charts and maps that can be easily embedded into reports. It also allows you to upload your files in various formats such as CSV, .tsv, and .txt 

Pros: 

  • Great for beginners.
  • Free to use.
  • Accessible online tool.

Cons:  

  • It can be challenging to build complex charts. 
  • Limited features. 
  • Security is not guaranteed as it is an online tool.
  1. Infogram: If you are not super design-inclined, this visualization tool should be your best friend. It has an editor drag-and-drop feature that makes it super easy to create beautiful designs without having to worry about where you are with your design skills. Infographics, marketing reports, maps, social media posts, and many more are examples of what you can create with this powerful tool. In addition, your data output can be exported in various formats, such as. JPG, GIF, PNG, HTML, and . PDF.  

Pros:

  • Web-based. 
  • Drag-and-drop editor.
  • Easy to use.
  • Highly customizable.

Cons: 

  • Built-in data sources are limited.
  • Not suitable for complex visualization.
  1. Google charts: Google Charts is another free data visualization tool that is user-friendly and compatible with all browsers and platforms. If you like to play around with codes, then Google Charts provides you with that option. Google Charts are coded with SVG and HTML5, allowing it to produce several graphic and pictorial data visualizations, ranging from simple visualization such as pie charts, bars, charts, histograms, maps, and scatter graphs to more complex ones such as hierarchical tree maps, timelines, and gauges. Google fusion tables, spreadsheets, and SQL databases are examples of data sources that can be used with Google Charts.  

Pros:

  • It is free.
  • It is compatible with various browsers.
  • Compatible with google products.

Cons:

  • Technical support is limited.
  • It requires network connectivity for visualization. 
  • There is no room for customization. 
  1. Tableau: This is one of the most popular data visualization tools, mainly because of the free public version that this software provides. Tableau provides the option of a desktop app, server, and online versions. In addition, this software has several data importation options, such as CSV files for google ads. Similarly, if you are looking into presenting your data in various formats, such as multiple chart formats and mapping, then Tableau is the one for you.  

Pros:

  • Provides several options for data import. 
  • It is available for free (public version).

Cons:

  • Lack of Privacy in the public version. 
  • Paid versions are costly. 

5. Dundas BI: Although this is one of the oldest data visualization tools, it is still standing strong as one of the most powerful tools for visualizing data with interactive charts, tree maps, gauges, smart tables, and scorecards. This interactivity allows users to understand the data quickly. Dundas BI is also highly customizable. Dundas BI operates on the ground of responsive HTML5 web technology that allows users to connect, analyze and interact with their data on any device. This powerful tool also provides a built-in feature for extracting data from many data sources.  

Pros:

  • Highly flexible.
  • Provides a variety of visualization options.

Cons: 

  • It lacks predictive analysis. 
  • Does not support 3D charts.  

There you have it! Now you know the tools to ask out on a date when you are ready to visualize your data. As much as you love data, these tools can help make others fall in love with your data, too.   

Going Down the Jane Austen Rabbit Hole

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This post is part of a series for Love Data Week, which takes place February 14-18 2022.

Written by Heidi Imker, Director of the Library Research Data Service

When you think of data, your mind probably doesn’t jump right to Pride and Prejudice. That is, unless you’re Heidi Imker, Director of the Research Data Service and amateur Jane Austen internet sleuth. “In late 2020,” Heidi says, “I was in desperate need of a post-Outlander spiritual cleanse. Naturally, I turned to Pride and Prejudice. Over a year later, I’m still in the midst of a fantastic, out-of-control Jane Austin binge, and I’ve got oodles of related resources worthy of Love Data Week.”

Join Heidi on a virtual tour of some of her favorite data resources about Austen, her works, and historical England.

  1. janeaustenr: Jane Austen’s Complete Novels

In this fabulous R package, data scientist Julia Silge used text data for the Austen novels available from the also fabulous Project Gutenberg. The package offers cleaned data, documentation, and scripts to play with and analyze the novels.

  1. Word Frequencies in English-Language Literature, 1700-1922

Randomly, sifting through the janeaustenr dataset gave me a new level of appreciation for the word “ignore.” Austen didn’t use “ignore” once in any of her novels. It turns out that no one was really using it because it hadn’t caught on yet. In fact, according to Google’s ngram viewer, “ignore” didn’t start getting traction until circa 1845. And now you might be thinking word frequency data is fun, and it is! Like this word frequencies dataset available from the HathiTrust Research Center.

  1. Napoleon Series

One of the things I learned during this binge was that dating the events in Pride and Prejudice has been a subject of debate for some time (as in, about a century). I found it downright fascinating that scholars could map parts of the book to the 1811 calendar year and others to the year 1794. I had never really thought about the characters existing in a specific year, but now I wondered what else was happening in those years? I discovered the Waterloo Association, a community of military historians behind the Napoleon Series. This immense archive contains articles on military history, biographies, and documentation of thousands of officers and soldiers (such as Challis’s Peninsula Roll Call).

  1. London Lives

Provides searchable access to >240,000 digitized pages of archival documents, with special focus on crime, poverty, and social policy. Not only is the source material available, but the people behind London Lives have made it a point to keep humanity at the forefront by constructing biographies of the individuals caught in the crime and poverty cycle in London between 1690 and 1800.

  1. Calendar of London Concerts 1750-1800

My favorite dataset of all time, it was thoughtfully and painstakingly created by Professor Simon McVeigh at Goldsmiths, University of London over many decades. It lists 4,001 concert events, as found through locating and documenting adverts in archival newspapers—by hand. When Lady Catharine tells Elizabeth that “it will be in my power to take one of you as far as London, for I am going there early in June, for a week,” what could that self-professed music aficionado have heard in June 1794? Voila! Perhaps it was Handel’s Messiah at St Margaret’s Church in Westminster on Thursday, June 5th.

I appreciate the Calendar of London Concerts dataset for my odd little hobby, but I love it as an information professional. The sheer dedication it took assemble the data, especially with such strict attention to detail, is incredible. Let me explicitly gush about the documentation for a moment. Context! References! Abbreviations! All explained! What’s “HM”? His Majesty’s something or other? No, it’s the Half-Moon Tavern in Cheapside. Currency conversions! Syntax for nearly impossible to standardize programme content! It’s forty-four glorious pages! Swoon!

Related resources on London concerts

What started out as a casual, online-friendly hobby ended up introducing me to a wealth of enlightening open data resources, and I’m in love with every one of them. Since my Austen binge is apparently nowhere near over, you may well get another link-laden post for next year’s Love Data Week. <3

Headshot of HeidiHeidi Imker is the Director of the Research Data Service (RDS) and an Associate Professor at the University of Illinois at Urbana-Champaign. The RDS helps researchers across the Urbana-Champaign campus manage and share research data, and in her role as Director, she ensures the RDS takes a collaborative, user-oriented, and practical approach to research support. Heidi holds a Ph.D. in Biochemistry from the University of Illinois and did her postdoctoral research at the Harvard Medical School.

OpenRefine: a Cinderella Story but for Data

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This post is part of a series for Love Data Week, which takes place February 14-18 2022.

Written by Dena Strong

Ever wish you could call on a fairy godmother who could wave a magic wand and make all your data problems disappear? Luckily for us at the University of Illinois, we can call on Senior Information Design Specialist Dena Strong. Dena can solve data problems so fast it seems downright magical. For Love Data Week 2022, check out Dena’s story about OpenRefine, the data tool she loves beyond all reason:

“I once had a consultation with a person who presented me with two Excel files and a data cleaning dilemma that he estimated was going to take him 200 hours of manual labor to repair. It took me 15 minutes of conversation to understand what he needed to do with the files to get them clean and integrated – and then it took me 5 minutes in OpenRefine to do the data cleaning and teach him how to do the same so he could do it again whenever he wanted. The other 199.6 hours of his time went to more productive uses. He and I have both been OpenRefine cheerleaders ever since. When I did a Caffeine Break session about it, an attendee said it was the most useful 45 minutes of training he’d ever had.”

As of the time of this writing, none of Dena’s datasets have turned back into pumpkins.

Headshot of DenaDena Strong (MLIS) is a member of the Web Hosting team at Technology Services; she also serves as a liaison with the Research Data Service at the Library. With 20 years of experience in usability, accessibility, information architecture, and workflows, Dena enjoys collaborating and consulting with people across campus. She’s also been spotted studying six languages, reproducing Heian-era Japanese dye techniques, and occasionally burning Kool-aid in search of new fabric colors.

When did you first fall in love with data?

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This post is part of a series for Love Data Week, which takes place February 14-18 2022.

Written by Lauren Phegley

Picture it – North Central College, Illinois, 2018. Twenty-one-year-old sociology major Laurent Phegley takes her seat in Professor Corsino’s class with no idea that she’s about to fall in love…with data. At the time, Dr. Corsino studied occupational attainment of Italian immigrants in Chicago Heights during the 1900’s. Lauren and her classmates sifted through census data to piece together the career tracks of (mostly male) Italian Americans. These data weren’t just checkmarks on a form. They were glimpses into entire families, glimpses that when pieced together told a story about how the American dream operates on the basis of social class. “For me, tracking the individuals through the census was a large puzzle,” Lauren says. Since then, Lauren has focused on helping other researchers solve their data puzzles. “Social science students are often not taught about data management because they don’t see their research as relating to ‘data’. I make a concerted effort now in my work and teaching to target fields that are often forgot about in terms of data management. Research is a labor of love. It is well worth a few hours of time to make sure that your data stays useable and understandable!”

Headshot of LaurenLauren Phegley is a graduate assistant for the Library Research Data Service pursuing her Masters of Science in Library and Information Science at the University of Illinois iSchool. Once she graduates in May 2022, she hopes to work as an academic librarian helping researchers manage their data and research.