![\"\"](\"https:\/\/world.edu\/wp-content\/uploads\/2023\/12\/Kids-in-museums_7.jpeg\")
<\/p>\n<\/p>\n
Ice cores in freezers, dinosaurs on display, fish in jars, birds in boxes, human remains and ancient artifacts from long gone civilizations that few people ever see \u2013 museum collections are filled with all this and more.<\/p>\n
These collections are treasure troves that recount the planet\u2019s natural and human history, and they help scientists in a variety of different fields such as geology, paleontology, anthropology and more. What you see on a trip to a museum is only a sliver of the wonders held in their collection.<\/p>\n
Museums generally want to make the contents of\u00a0their collections available<\/a>\u00a0for teachers and researchers, either physically\u00a0or digitally<\/a>. However, each collection\u2019s staff has its own way of organizing data, so navigating these collections can prove challenging.<\/p>\n Creating, organizing and distributing the digital copies of museum samples or the information about physical items in a collection requires\u00a0incredible amounts of data<\/a>. And this data can feed into machine learning models or other artificial intelligence\u00a0to answer big questions<\/a>.<\/p>\n Currently, even within a single research domain,\u00a0finding the right data<\/a>\u00a0requires navigating different repositories. AI can help organize large amounts of data from different collections and pull out information to answer specific questions.<\/p>\n But using AI isn\u2019t a perfect solution. A set of shared practices and systems for data management between museums could improve the data curation and sharing necessary for AI to do its job. These practices could help both humans and machines make new discoveries from these valuable collections.<\/p>\n As an\u00a0information scientist<\/a>\u00a0who studies scientists\u2019 approaches to and opinions on\u00a0research data management<\/a>, I\u2019ve seen how the world\u2019s physical collection infrastructure is a patchwork quilt of objects and their\u00a0associated metadata<\/a>.<\/p>\n AI tools can do amazing things, such as\u00a0make 3D models<\/a>\u00a0of\u00a0digitized versions<\/a>\u00a0of the items in museum collections, but only if there\u2019s enough well-organized data about that item available. To see how AI can help museum collections, my team of researchers started by\u00a0conducting focus groups<\/a>\u00a0with the people who managed museum collections. We asked what they are doing to get their collections used by both humans and AI.<\/p>\n When an item comes into a museum collection, the collection managers are the people who describe that item\u2019s features and generate data about it. That data, called metadata, allows others to use it and might include things like the collector\u2019s name, geographic location, the time it was collected, and in the case of geological samples, the epoch it\u2019s from. For samples from an animal or plant, it might include\u00a0its taxonomy<\/a>, which is the set of Latin names that classify it.<\/p>\n All together, that information adds up to a mind-boggling amount of data.<\/p>\n But combining data across domains with different standards is really tricky. Fortunately, collection managers have been working to standardize their processes\u00a0across disciplines<\/a>\u00a0and for\u00a0many types of samples<\/a>. Grants have helped science communities build tools for standardization.<\/p>\n In biological collections,\u00a0the tool Specify<\/a>\u00a0allows managers to quickly classify specimens with drop-down menus prepopulated with standards for taxonomy and other parameters to consistently describe the incoming specimens.<\/p>\n A common metadata standard in biology is\u00a0Darwin Core<\/a>. Similar well-established metadata and tools exist across all the sciences to make the workflow of taking real items and putting them into a machine as easy as possible.<\/p>\n Special tools like these and metadata help collection managers make data from their objects reusable for research and educational purposes.<\/p>\nCollection managers<\/strong><\/h4>\n