 Documentic data about human artists in the universe have suffered that connection. I will trade you through my process for this project and the outcomes where any collection can adapt this methodology. One of my aims was to create awareness of the women artists in the collection. I addressed this by collecting data and exploring ways to make this information accessible to a broader audience. I am conducting this work mindful of the art and feminism initiative within the Wikimedia movement. This project involved the process of understanding data and exploring the possibilities for preserving the data, primarily through the use of the Wikimedia platforms, using Wikidata, Wikimedia Commons and Wikipedia. To understand the collection better, I started by analyzing data through offline lists of all the works in the collection. I had also explored the art collection online presence. The formation was gathered mostly from the University of Salt Lake website, where the data was derived from other websites about the artists or by the artists, including online versions of exhibition catalogs, found through Google searches. This enabled the creation of standard-facing information about each artist's such own space of birth, date of death, where applicable, and the significant point that their work is in the University of Salt Lake art collection. However, I should point out here that I chose not to contact artists to collect missing information, but instead perform basic data, ecology, and editing what is already out there on the internet, including with kit platforms. I did this as a proof of concept to show that even with little information readily available on the internet, such findings can be made. Of course, for such projects to continue growing, work would be best developed in direct collaboration with the collection curators. I started by enabling Wikidata records about individual artists to include a statement about the fact that their work is in the University of Salt Lake art collection. A Wikidata entry for the collection itself needed to be created first. Data entries included location and owned by the University of Salt Lake. Taking this work forward required attention to Wikidata entries for individual artists with a basic standard item structure. I'm being ahead to the way I'll be processing these records from Wikidata in a minute. I have performed what is known as the Wikidata query in combination with the data visualization tool available also through Wistropedia. This one simple and visual way helped me to identify ways to improve the data set. For example, by removing duplicate entries or fixing incomplete or inaccurate dates. Once all the women artists in the University of Salt Lake art collection had individual Wikidata records, they could also be collectively represented by a new list of identifiers. But since the initial amount of data has been organized through Wikidata, it is possible to tabulate information to queries on the database. This involves basic data science techniques of filtering the correlating data. In the case of Wikidata, this is performed through a process that involves Sparkle commands, which derive data from the database. By having dates associated with the query, Wikidata query service can render this result as a table or interactive timer. Or by having the place of birth statement, you can even generate data queries on a map. Sparkle queries help to identify missing data with the female artists. A more visual way to identify and find gaps in data, which can be addressed accordingly, downloaded as an Excel file, CSV, among other formats. This is a simple list of women that have worked present in the University of Salt Lake art collection generated through the data available in Wikidata. For example, I'm adding optional to show all the women artists in the collection, regardless of whether they have a date of birth, data entry. The same query for the women in the collection who have a data entry for the place of birth can be visualized as a map. As you can see, it is very effective and interactive, showing with red dots where the artist whose work is in the collection are from. Things get even more interesting when you see the links with separate institutions or art collections sharing their collection data. If that data is in Wikidata, users can see which work are collected by specific museums and even determine a specific date range. As with so much on Wikidata, there is a great potential to reveal new insights about collections. These can also be combined with other visualization tools. I have selected to use such a visualization tool from Listeropedia. This works best for records that include images. It also highlights gaps in the image holdings associated with specific records. I can demonstrate it here by showing specific diamonds associated with the collection, such as the date of birth of women artists in the collection. We are encoding them according to the place of birth. This tool provides interactivity with zooming possibilities, showing always the artist in front as the artist for which there is the largest amount of data present in the database. This can also show gaps in the timeline, depending on the available data about the collection. Wikidata allows for powerful queries to reveal insights about artists' gender, material use, exhibition information, and provenance of works. In conclusion, through the work I have conducted on this project, I have aimed to show how use of Wikidata can help art collection managers keep track of the collection. Specifically, I have shown a method to create better awareness of women artists, identify gaps, increase visibility, potentially address the gender gap in the collection, and create and improve Wikipedia articles about women artists, engage further with Wikipedia project for the collection more broadly regardless of gender. An analysis of this data enables collection managers to get a fuller picture and enables them to work towards specific goals within their collection, such as achieving gender bands or addressing historical gaps. I discussed with the collection assistant curator also the possibility to amend acquisition forms that artists, women, and artwork is collected so that more specific data used for such work for Wikidata queries is collected. Data is the source to shape new ways of seeing things, new ways to understand collections, when data is curated and or navigated with sensitivity to line and space with data visualization, you start to experience a new kind of language, a more visual language. Thank you.