2023:Program/Submissions/Experiencing GLAM through Wikidata - 8KGUFU

The following is a mirror of what are publicly available details of submission made at the call for proposal platform, Pretalx. Any changes here may be overwritten by a bot while syncing updates from Pretalx ([1]). Changes are monitored and may be updated into Pretalx if they do not change the context of the submission (i.e. correcting typographical errors).

Title: Experiencing GLAM through Wikidata

Speakers:

Enrique Tabone

Enrique Tabone is an artist and designer. She is also the program coordinator for Wikimedia Community Malta, an affiliated user group of the Wikimedia Foundation. Her Wikimedia work is mainly on Wikidata and relates to exploring ways to engage with GLAM organisations through data visualisation and other creative data art opportunities.

Pretalx link

Etherpad link

Room:

Start time:

End time:

Type: Lightning talk

Track: GLAM, Heritage, and Culture

Submission state: submitted

Duration: 10 minutes

Do not record: false

Presentation language: en

Abstract & description

Abstract

As an open database, Wikidata can be used freely for artistic exploration. It is not always easy to extract useful knowledge from the structured data held in Wikidata. SPARQL query language enables such extraction, to extract information and visualise data. Data visualization tools are largely used to generate charts, trees, and maps. There are also possibilities for artistic creation through GLAM collections. This is the basis for data art.

Description

My dataset for this project comes from Heritage Malta’s collection of prehistoric female figurines. These are held at the National Museum of Archaeology in Valletta and the Ġgantija Archaeological Park in Gozo. Through Wikidata I have processed the raw data on this collection and applied FAIR data principles to it. This enabled the analyses of the visual descriptive data to ensure opportunities for open interpretations, including for feminist points of view that have frequently been disregarded, overlooked, or completely excluded. In 2020 a network of women involved in data science coalesced around the idea of data feminism. Their aim is to lead a cultural movement to promote equitable and gender-sensitive data systems for more inclusive decision making. This is also considered in the context of this project.

Complementing the visualisation of the dataset, I have also employed a technique of data sonification. This method involves the representation of aspects of the dataset in sound. I have created a series of art objects to analyse the possibilities of working with this type of data in an artistic context. The practical work provides a method for researching new insights into the dataset, which otherwise remains a flat document containing basic information about very ancient objects that have frequently been overlooked. Ultimately, this research project proposes ways to make otherwise forgotten archaeological museum objects more noticeable through artistic interpretation.

Further details

Qn. How does your session relate to the event themes: Diversity, Collaboration Future?

By exploring the use of Wikidata within GLAM in small countries such as Malta this session delates directly to the event theme of diversity. Furthermore, in terms of Collaboration Future, it touches on the ways small entities may collaborate with larger ones in a transparent and open way in the future, especially through platforms such as Wikidata and other Wikimedia projects.

Qn. What is the experience level needed for the audience for your session?

Everyone can participate in this session

Qn. What is the most appropriate format for this session?

• Onsite in Singapore
• Remote online participation, livestreamed
• Remote from a satellite event
• Hybrid with some participants in Singapore and others dialing in remotely
• Pre-recorded and available on demand