About

Assets:
The Feminist and Marxist Analysis of the Art in the Tate Museum is a research project that analyzes data from the Tate Museum dataset provided through Corgis. The Tate Museum collection is a digital system that holds a large selection of over 65,000 artworks from 1500 to the present day. The collection includes all media in all art forms like painting, film, prints, sculpture, and etc. The archive’s main goal is to spread art and creativity and, therefore, to reach a broader audience of influence. Through careful selection of different datasets, we decided that the Tate collection would be the most flexible and effective in our research as it is not purely just a collection of images. From Corgis, we are able to access a CSV file of the artworks, making the dataset easy to analyze and iterate visualizations from. The dataset includes many demographic and contextual information surrounding each art piece including the gender of the artist, the year it was made and/or presented, and many more. All pieces of information are included in the CSV dataset and made useful for the analysis tools we used throughout the research process. Upon diving deeper into each row/artwork of the file, the dataset is seen to include a URL to the website collection that hosts the art. Each page consists of a scan(s) or photo of the art piece and goes more in-depth into each, presenting metadata like a catalog entry and artist description.
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Services:
Our project provides a project presentation page that provides an in-depth demonstration of the full project, along with an accompanying narrative that displays the project’s research questions, hypothesis/thesis, data visualizations, and extensive passages on research findings. The annotated bibliography page gives viewers an in-depth analysis of each source that were drawn from academic journals and digital library systems. This About page goes into each part of the digital humanities project and also ensures that we, as researchers/scholars provide the right and best information through this project. In addition, this project also includes a data critique that explains the pros and cons of our dataset, as well as our dataset’s ontology. Our website includes easy access and analysis of the Tate database, utilizing public data to argue and present the relationship between theory and art. All of these pages and content provide full transparency of sources, processes, and credited individuals and sources.
In analyzing the Tate database, we did minimal data cleaning as the data was clear and all values were strings or integers. We only removed one row of the dataset when creating a plot/graph for gender analysis. We also categorized artworks into multimedia, paintings, and sculptures. In creating data visualizations, we utilized Matpoltlib (a plotting library for the Python language) to graph point, line, and bar graphs. In addition, we utilized the ArcGIS StoryMaps program to create map visualizations based on location information provided in the dataset.
Interface/Display:
This project website is powered by Wix, a website builder with a powerful domain that supports and runs the site. Wix sites are scrapable, meaning content is open/accessible to the public and available for use. This project is also open-sourced, providing transparent code and data analysis processes. In addition, this website is organized and designed with the intention and thought of creating an easily navigable platform through the organization and division of content and information. Prior to designing the final website interface, we created a storyboard that highlighted the content we would be showcasing; this process helped us organize and accurately develop a website that included all aspects of the project in an arranged manner. Additionally, our group created a wireframe design/sketch in Figma that focused on the layout of the website and prioritized user experience while navigating through our content. Our homepage is both concise and visually pleasing to draw in users and present a good first impression. The page introduces our project in a short description and includes quick links to other pages that are highly visible and make our site easier to navigate; each quick link provides a description of each page so that users understand the content present in the sections of the website. Above each page, a navigation bar at the top makes all pages accessible at any point. Throughout the project website, a consistent interface design is maintained to ensure a simple/minimal, yet recognizable design. Each page (about, narrative, data critique, and bibliography page) consists of legible information and images that appear with ease for all users to easily comprehend. Graphs and images are clear and high quality to ensure legibility in all aspects.
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The Team

Cassandra Calciano
Cassandra is a senior, majoring in Data Science and Slavic literature and languages. She wrote an outline for the narrative for the storyboard and helped with the final draft of the narrative with minor contributions to exploratory data analysis. She is interested in learning languages and has aspirations to go to graduate school.

Haokai Pan
Haokai is a senior majoring in Data Science. Haokai worked on exploratory data analysis, visualization, and data critical narrative. He loves to watch basketball and play video games.

Joanna Wong
Joanna is an incoming Architecture major at UC Berkeley, beginning her minor in Digital Humanities. For this project, Joanna worked on writing the About page and designing / building the website. She also has interests in UX/UI Design, photography, and graphic design.

Joanne Shin
Joanne is a Senior Cognitive Science major with a minor in Data Science at UC Berkeley. Joanne helped draft the bare bones of the website layout and helped write the Narrative. In her free time, Joanne loves to do fashion photoshoots.

Ravpreet Grewal
Ravpreet is a rising senior majoring in Data Science and Economics. Ravpreet helped with initial exploratory data analysis, visualization, and the annotated bibliography. In his free time, he enjoys watching basketball, cricket, and Formula 1.