IMLS Empowering Museums
Empowering Museums by creating open, collaborative, online training and tools to improve digital experiences
The Field Museum technology team with partners from different departments such as Collections, Repatriation, and the Learning Center have created training materials, including an open-source slide deck template and an icon set, encouraging F.A.I.R (findability, accessibility, interoperability and reusability) and C.A.R.E. (Collective Benefit, Authority to Control, Responsibility, Ethics) principles.
Project Details
Item URI:051f268e-6eaf-47b0-87be-7f24ccde6ace
Start Date:September 1, 2021
End Date:2025
Description:Training modules outlined in the IMLS Empowered grant 2021-25, Data Fundamentals, Data Cleaning and Data Assessment.
Credit Line:These presentations have been made possible by the Institute of Museum and Library Services (IMLS) GrantME-249136-OMS-21.
Audience:Museum Staff
Organizers:
- Ms Sharon D. Grant : Field Museum of Natural History - Technology Department
- Ms. Janeen M. Jones : Field Museum of Natural History - Technology Department
- Jenny Flowers : Children's Museum of Illinois
- Sara Furr
- Abigail McArthur-Self : Field Museum of Natural History - Technology Department
- Alexis Ramirez : Field Museum of Natural History - Technology Department
- Kate Webbink : Field Museum of Natural History - Technology Department
- Helen Robbins
Funding:IMLS - Institute of Museum and Library Services - Museums Empowered: Professional Development Opportunities for Museum Staff
Learning Resources
Can Data be Cultured? Cultural Awareness in Museum Data
View moreMuseum collections data are not simply technical records—they capture relationships between people, specimens, collection items, places, events, and knowledge systems. This course helps museum professionals develop practical skills for creating, managing, and sharing,collections data that are scientifically robust, historically contextualized, ethically informed, and useful for diverse audiences. ,,,Across five interactive modules, participants progressively develop competencies in language, self-awareness, systems thinking, communication, and applied decision-making through discussions, reflection, and authentic museum case studies. The curriculum emphasizes that improving,collections data is both a technical and human-centered practice that supports responsible stewardship.
Can Data be Cultured? Self
View moreEveryone brings their own experiences and assumptions to the way they collect, interpret, and describe information. In this module, you'll reflect on how your identity, perspectives, and beliefs influence your work with collections data. By examining your own assumptions and,considering other viewpoints, you'll develop habits that support fair, thoughtful, and evidence-based documentation.
Can Data be Cultured? Language
View moreThe words we use in museum records matter. This module explores how language changes over time, differs between cultures and disciplines, and shapes the way people understand collections data. Through discussions and activities, you'll learn why scientific terms, place names, and,descriptions are not always neutral, and how choosing clear, thoughtful language helps create more accurate and inclusive collections records.
Can Data be Cultured? Communication
View moreCollections data are used by many different audiences. This module explores how to communicate information clearly and responsibly by providing appropriate context. You'll learn when and why museums use explanations, warnings, labels, and other supporting information to help,people understand collections records, particularly when they include sensitive, historical, or culturally significant material.
Can Data be Cultured? Systems
View moreMuseum collections are managed within systems such as policies, standards, databases, and workplace practices. This module explores how these systems influence the information we record and share. You'll learn how processes, priorities, power, people, and perspectives shape,collections data, and consider practical ways to recognize bias and improve systems for both researchers and the communities represented in collections.
Can Data be Cultured? Praxis
View moreThis module synthesizes the other four in the Can Data be Cultured series. You'll apply what you've learned to realistic museum case studies. Working through practical examples, you'll identify different perspectives, recognize bias, consider who is affected by documentation,decisions, and develop thoughtful responses. The goal is to build confidence in making informed, ethical decisions that improve the quality and usefulness of collections data.
Data Cleaning - Tools you Can Use [1]: Spreadsheet Applications
View moreThis module consists of 3 sections to either learn by self-directed teaching or to teach others. How to Clean Data Using Excel; How to Clean Data using OfficeLibre Calc and How to Clean Data using Google Sheets.
Data Cleaning With Open Office Calc
View moreThis module covers how to clean data using Open Office or Libre Office Calc
- Libre Office Calc for Data Cleaning (pptx)
- Post - assessment text for the Libre Office Calc for Data Cleaning (pdf)
- Libre Office Calc for Data Cleaning (pdf)
- Pre-assessment text for the Libre Office Calc for Data Cleaning (pdf)
- Facilitation Guide for How to Clean Data with Spreadsheets: Libre Office Calc (pdf)
Data Cleaning With Excel
View moreThis module covers how to clean data using Excel.
Fundamentals of Museum Data
View moreThis module consists of 2 sections and examines some fundamental things participants need to know before data cleaning can happen.
Terminology and Planning Your Data Cleaning
View moreFundamentals: Terminology: Good data cleaning starts with understanding the language of data. In this module, you'll learn the key terms used to describe data quality, standards, databases, field types, character encoding, tables, relationships, and data structures. You'll,explore why standards such as Darwin Core matter, how different types of data are stored, and how to plan a data migration. This foundation prepares you to clean, organize, and manage collections data with confidence.,,,Wrapping Up: Applying Data Cleaning Fundamentals: This final module brings together everything you've learned about data cleaning. You'll review key concepts including data relationships, field types, planning, standards, and tool selection before applying them in realistic,collections data exercises. By mapping fields, restructuring data, and preparing information for migration into standards such as Darwin Core, you'll strengthen your practical skills and assess your progress through post-course activities.
- Rubric for Fundamentals for Data Cleanup - Terminology (pdf)
- Pre-Assessment text for Fundamentals for Data Cleanup - Terminology (pdf)
- Post-Assessment text for Fundamentals for Data Cleanup - Terminology (pdf)
- Fundamentals for Data Cleanup - Terminology (pdf)
- Fundamentals for Data Cleanup - Terminology (pptx)
- Fundamentals for Data Cleanup - Terminology Wrapping Up (pdf)
- Fundamentals for Data Cleanup - Terminology Wrapping Up (pptx)
- Facilitation guide: Fundamentals for Data Cleanup: Terminology (pdf)
- Facilitation guide: Fundamentals for Data Cleanup: Wrapping Up (pdf)
Media - Rights and Licenses for Museum Professionals
View moreThis module can be used to either learn by self-directed teaching or to teach others, how to document museum multimedia and the rights and licenses that go with them.
Data Cleaning - Tools you Can Use [2]: Scripting and Databases
View moreThis module explores more advanced tools and methods commonly used for data cleaning. Sections includes: Cleaning with MS Access; Cleaning with R and Cleaning with OpenRefine.
Using OpenRefine for Data Cleaning.
View moreThis module explains the basics for use the tool Open Refine to clean Museum data.
- Rubric for How to Use Open Refine for Data Cleaning (pdf)
- Post-Assessment text for How to Use Open Refine for Data Cleaning (pdf)
- How to Use Open Refine for Data Cleaning (pptx)
- Pre-Assessment text for How to Use Open Refine for Data Cleaning (pdf)
- How to Use Open Refine for Data Cleaning (pdf)
- Facilitation Guide for How to Clean Data: Open Refine (pdf)
Using R for Data Cleaning
View moreThis module explains the basics for use the programming language R to clean Museum data.
Data Cleaning using Microsoft Access
View moreThis module contains all the documentation to either self-direct training or teach to a group of staff members how to use Microsoft Access to clean data for use in museums.
Shared data in service of shared goals
In addition to training materials, we are working to build a cohort of Field Museum professionals equipped with new and expanded data management skills — and a mutual understanding of collections data as a shared resource that should be cared for by departments across the Museum.
Leveling up our data standards and practices
These include slide presentations, hands-on data activities, and card games that teach about data accuracy, sharing, and access, so they can be used in online training sessions. A new training section called "Cultural Awareness and Sensitivity in Museum Data." was also developed to help foster a better understanding of F.A.I.R. and C.A.R.E. principles. These training modules have been made publicly available here for download and use by other museums and libraries to encourage findability, accessibility, interoperability and reusability (FAIR) and Collective Benefit, Authority to Control, Responsibility, Ethics (CARE) principles in data.
Meet the team
Image slideshow
Screen reader users can skip the following slideshow buttons by using heading navigation. All slides have been displayed above.
Acknowledgments
The Field Museum gratefully acknowledges the Institute of Library and Museum Services for its generous support of the Field Guides Initiative.
