Session recordingThe infrastructures undergirding linked data projects are complex and varied. As the technological stacks and social infrastructures come into greater maturity, the general landscape has grown in complexity too, possibly to the point of being overwhelming for GLAM institutions. As a result it can be difficult to separate out what tools are essential for linked data initiatives from what are not. Similarly, complexity has increased in these projects possibly to the point of obfuscating their practical ends. The framework of minimal computing provides a useful lens for interpreting the role of technologies with an aim towards identifying needless complexity and increasing access through concretely asking what is actually needed for a successful project. Further, it seeks to tie these efforts to their social impacts and how it can build capacity for those working in non-Western societies. By exploring specifically the concepts of minimal design, dependencies, and maintenance and others, we may be able to more effectively examine those aspects of linked data that could be reconfigured or disbanded. Hopefully, this would lead towards an environment that purposefully addresses the challenges that arose in previous decades of GLAM metadata without introducing newer forms of complexity As so many decisions cascade from how the real world is defined in ontologies, minimal computing has much to offer towards simplifying the infrastructures and conditions that they necessarily outline. This session applies principles of minimal computing to ontology design using the example of a glacier ontology in development at the University of Colorado Boulder. Specifically we will address how using minimal computing is in line with a more materialist approach to data modeling that seeks to aim linked data initiatives within concrete realities and away from unwarranted abstraction. Practical advice for how to apply minimal computing principles to other areas of linked data projects will also be addressed.
