Data Analysis & Visualization for Conservation Professionals: Part 1

  • Registration Closed

Online course
January 12 - February 23, 2021

The waitlist for this course is currently closed. Please keep an eye out for announcements regarding future programming.

Data Analysis and Visualization for Conservation Professionals is a two-part course designed to introduce conservators and cultural heritage professionals to the fundamentals of working with data sets. Numerous types of projects within conservation and preservation can benefit from data-driven tools and methods. Both small and large data sets are now commonly collected and readily accessible for querying. While many are familiar with conventional tools such as Microsoft Excel, a broader picture of strategy, reasoning, and specific tools will open up the possibilities for more successful projects. 

Part 1 which will teach participants statistical reasoning, ethics and bias in data collection, data formats, data extraction, database design, and data scrubbing. Participants will learn to properly plan for and collect data sets so they can perform statistically sound analysis. Part 2 will introduce tools for analysis of text, numeric, and image data sets, visualization of data, and dissemination. Participants will learn multiple methods for data analysis and visualization with both open-source and proprietary tools using various tools with a focus on open source software. After completion of part one and two of the course participants will be able to collect and organize data in strategic ways, use common open-source data collection and management tools, evaluate data-driven projects and publications in cultural heritage, recognize questions that can be answered with data driven methods, and recognize when to seek a collaborator and how to find one.

This is Part 1 only. Participants are encouraged to participate in both parts, although it is not required. Registration for Part 2 will be available in early 2021 and priority will go to those who participate in Part 1. Those who do not participate in Part 1 may participate in Part 2, but will be required to purchase and complete a self-study version of Part 1. Space is limited in order to allow for discussion and individual feedback from the instructors.

The live sessions for the course will take place in Zoom and live captions will be available.

Introduction to Thinking Quantitatively with Diana Greenwald
January 12: Live session at 1:00 - 3:00 p.m. Eastern Time
January 16: Optional assignment due

Art Data, Past and Present with Diana Greenwald
January 19: Live session at 1:00 - 3:00 p.m. Eastern Time
January 23: Optional assignment due

Data Collection: Object-based methods with Lee Ann Daffner
January 26: Live session at 1:00 - 3:00 p.m. Eastern Time
January 30: Optional assignment due

Data Collection: Social science methods with Lesley Langa
February 2: Live session at 1:00 - 3:00 p.m. Eastern Time
February 6: Optional assignment due

Data Standardization with Kelly Davis
February 9: Live session at 1:00 - 3:00 p.m. Eastern Time
February 13: Optional assignment due

Fundamentals of Databases with Kelly Davis
February 16: Live session at 1:00 - 3:00 p.m. Eastern Time

All live sessions will be recorded and accessible to participants shortly after the session is complete.


This program is an FAIC Collaboration Workshop in Photograph Conservation. This series of workshops was initiated by Debra Hess Norris and Nora Kennedy in 1997, with funding from The Andrew W. Mellon Foundation. The program became part of the FAIC professional development program in 2009, under an endowment grant from The Andrew W. Mellon Foundation.

The FAIC Collaborative Workshops in Photograph Conservation Endowment was created by a grant from The Andrew W. Mellon Foundation and is supported by donations from members of the American Institute for Conservation and its friends. Courses are made possible with the assistance of many AIC members, but no AIC membership dues were used to create or present this course.

Without support, the registration fee for this course would be over $400. FAIC relies on your contributions to support these and its many other programs. Learn more about donating to the foundation here.

Lee Ann Daffner

Lee Ann Daffner is the Andrew W. Mellon Conservator of Photographs at The Museum of Modern Art where she established the museum’s first photograph conservation section in 1998. She received her M.A. in Art Conservation from the University at Buffalo, State University of New York in 1994. Before joining MoMA, she held conservation appointments at The Metropolitan Museum, Harvard University, The Library of Congress, and The Better Image.

 Daffner oversees the conservation and preservation of all the photographs in the museum, located in every curatorial department, library and archives. Daffner promotes materials-based scholarship and assimilation of this content in curatorial, technical art history and academic initiatives. From 2009 to 2015, she directed the conservation portion of the cross-disciplinary study of the Museum’s Thomas Walther Collection of Modernist Photography, co-edited the Object:Photo print and online publications, and has contributed essays to numerous exhibition catalogues. She currently serves as Associate Editor for JAIC.

Kelly Davis

Kelly Davis is a data manager of the Getty Provenance Index, a database for the field of collecting and provenance. She completed her Master’s from Pratt Institute in 2014, in the fields of Library Science and Art History. Her work is focused on updating and maintaining an excellent research tool by standardizing metadata, conforming to internal schema and reconciling entities. She’s known as an “Open Refine guru” at the Getty, and works frequently with that program and other data science methods.

Diana Greenwald

Diana Seave Greenwald is an art historian and economic historian. Her work uses both statistical and qualitative analyses to explore the relationship between art and broader social and economic change during the nineteenth and early twentieth centuries, particularly in the United States and France. Her first book, Painting by Numbers: Data-Driven Histories of Nineteenth Century Art, will be published by Princeton University Press in February 2021. 

Diana is currently the Assistant Curator of the Collection at the Isabella Stewart Gardner Museum in Boston. Prior to joining the Gardner, she was an Andrew W. Mellon Postdoctoral Curatorial Fellow at the National Gallery of Art in Washington, D.C., working in the departments of American and British Paintings and Modern Prints and Drawings.

She received a D.Phil. in History from the University of Oxford. Before doctoral study, Diana earned an M.Phil. in Economic and Social History from Oxford and received a Bachelor’s degree in Art History from Columbia University.

Lesley Langa

Dr. Langa is a strategic research and program manager with over 15 years of experience managing national initiatives that address the needs of libraries, museums and other heritage institutions. Her work focuses on the big picture of cultural heritage, including an individual's experience with it, how we protect it, how we support the cultural sector, how we care for it and evaluating the mechanisms we use to do all of this. Her work has spanned several areas including digital collections, metadata management, evaluation and research, and user experience across the cultural heritage sector in museums, federal cultural agencies, and small nonprofits. Using this diverse background, Dr. Langa sets out to find the answers to questions that can affect practice in the field and deliver practical solutions for cultural heritage professionals. She runs a consulting firm, NovaKultura, and recently completed a PhD at the University of Maryland's iSchool. 

Key:

Complete
Failed
Available
Locked
Participant List
Open to download resource.
Open to download resource.
Lesson 1: Overview / Readings / Assignment
Overview: Lesson 1
Open to download resource.
Open to download resource.
Pre-reading: Collective Style and Personal Manner, Materials and Techniques of High-Life Genre Painting
Open to download resource.
Open to download resource. E. Melanie Gifford and Lisha Deming Glinsman, “Collective Style and Personal Manner, Materials and Techniques of High-Life Genre Painting” in Adriaan E. Waiboer, et al. (ed.) Vermeer and the Masters of Genre Painting: Inspiration and Rivalry (Washington: National Gallery of Art, 2017)
Pre-reading: The Description of Craquelure Patterns
Open to download resource.
Open to download resource. Spike Bucklow, “The Description of Craquelure Patterns,” Studies in Conservation 42, no. 3 (1997): 129-140
Assignment: Lesson 1
Graded as Pass/Fail | Due Date: 01/16/2021
Graded as Pass/Fail | Due Date: 01/16/2021 Think about and write down 1-3 research questions that you think could be addressed with quantitative methods. Why do you think this is a good question for a quantitative approach? Which of the approaches we discussed today do you find most interesting? Start to think about the data you may need to answer this question, as data gathering will be the focus on much of the rest of this course.
Introduction to Thinking Quantitatively
Recorded Session: Introduction to Thinking Quantitatively
01/12/2021 at 1:00 PM (EST)   |  120 minutes
01/12/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Introduction to Thinking Quantitatively
Open to download resource.
Open to download resource.
Lesson 2: Overview / Readings / Assignment
Overview: Lesson 2
Open to download resource.
Open to download resource.
Pre-reading: What Can Data Teach Us About Museum Collections?
Select the "View" button to begin.
Select the "View" button to begin. Diana Seave Greenwald, “What Can Data Teach Us About Museum Collections?” American Alliance of Museums Blog, April 27, 2020, URL https://www.aam-us.org/2020/04/27/what-can-data-teach-us-about-museum-collections/
Assignment: Lesson 2
Graded as Pass/Fail | Due Date: 01/23/2021
Graded as Pass/Fail | Due Date: 01/23/2021 With your research questions from last week in mind, write several bullet points about any datasets you have access to (it’s all right if it is not yet digitized) that could address your questions. What is the scope of the data? What variables does the dataset include? Is it time series, cross-sectional, or panel data?
Additional Resource: iPEHD—The ifo Prussian Economic History Database
Open to download resource.
Open to download resource. Sascha O. Becker, Francesco Cinnirella, Erik Hornung & Ludger Woessmann “iPEHD—The ifo Prussian Economic History Database,“ Historical Methods: A Journal of Quantitative and Interdisciplinary History, 47:2, 57-66, 2014, DOI: 10.1080/01615440.2013.852370 [This source is not art historical at all, but it is one of the few accounts of all the work involved with transcribing historical data]
Art Data, Past and Present
Recorded Session: Art Data, Past and Present
01/19/2021 at 1:00 PM (EST)   |  120 minutes
01/19/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Art Data, Past and Present
Open to download resource.
Open to download resource.
Slides: Case Study with Kari Rayner
Open to download resource.
Open to download resource.
Lesson 3: Overview / Readings / Assignment
Overview: Lesson 3
Open to download resource.
Open to download resource.
Pre-reading: Image Isn’t Everything: Revealing Affinities across Collections through the Language of the Photographic Print
Select the "View" button to begin.
Select the "View" button to begin. Paul Messier. “Image Isn’t Everything: Revealing Affinities across Collections through the Language of the Photographic Print.” In Mitra Abbaspour, Lee Ann Daffner, and Maria Morris Hambourg, eds. Object:Photo. Modern Photographs: The Thomas Walther Collection 1909– 1949. An Online Project of The Museum of Modern Art. New York: The Museum of Modern Art, 2014. https://www.moma.org/interactives/objectphoto/assets/essays/Messier.pdf
Pre-reading: Material Forms in Nature: The Photographs of Karl Blossfeldt
Select the "View" button to begin.
Select the "View" button to begin. Hanako Murata. “Material Forms in Nature: The Photographs of Karl Blossfeldt.” In Mitra Abbaspour, Lee Ann Daffner, and Maria Morris Hambourg, eds. Object:Photo. Modern Photographs: The Thomas Walther Collection 1909–1949. An Online Project of The Museum of Modern Art. New York: The Museum of Modern Art, 2014. https://www.moma.org/interactives/objectphoto/assets/essays/Murata.pdf
Pre-reading: Object:Photo Homepage
Select the "View" button to begin.
Select the "View" button to begin. https://www.moma.org/interactives/objectphoto/#home
Pre-reading: Object:Photo Materials Analysis Section
Select the "View" button to begin.
Select the "View" button to begin. Click on red “action” buttons and text to access data
Pre-reading: Object:Photo XRF Section
Select the "View" button to begin.
Select the "View" button to begin.
Pre-reading: Characterization and Dating of Historic Silver Gelatin Fiber Based Photographic Papers Using X-ray Fluorescence Spectroscopy and Chemometrics
Open to download resource.
Open to download resource. Ana Martins, et al. Characterization and Dating of Historic Silver Gelatin Fiber Based Photographic Papers Using X-ray Fluorescence Spectroscopy and Chemometrics. Denver X-Ray Conference August 6-10, 2012. Denver Marriott Tech Center Hotel, Denver, Co.
Assignment: Lesson 3
Graded as Pass/Fail | Due Date: 01/30/2021
Graded as Pass/Fail | Due Date: 01/30/2021 How would you apply one of the methods talked about in this lesson to plan for or design a data collection project working with objects to support your research questions? Are there any material variables you think you should be aware of in advance? Think about how a simple measurement or condition assessment, when collected en masse, might provide insight to the unique material constituents in your area of interest.
Data Collection: Object-based methods
Recorded Session: Data Collection: Object-based methods
01/26/2021 at 1:00 PM (EST)   |  120 minutes
01/26/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Data Collection: Object-based Methods
Open to download resource.
Open to download resource.
Lesson 4: Overview / Readings / Assignment
Overview: Lesson 4
Open to download resource.
Open to download resource.
Pre-reading: Conducting a Systematic Literature Review
Select the "View" button to begin.
Select the "View" button to begin. Research Shorts. “Conducting a Systematic Literature Review.” Research Shorts, May 24, 2017. YouTube video, 3:17. https://www.youtube.com/watch?v=WUErib-fXV0&ab_channel=ShadyAttia
Pre-reading: Questionnaire design
Select the "View" button to begin.
Select the "View" button to begin. Pew Research, (n.d.). “Questionnaire design.” https://www.pewresearch.org/methods/u-s-survey-research/questionnaire-design/
Pre-reading: Writing Interview Protocols and Conducting Interviews: Tips for Students New to the Field of Qualitative Research
Select the "View" button to begin.
Select the "View" button to begin. Stacy A. Jacob and S. Paige Furgerson. (2012). Writing Interview Protocols and Conducting Interviews: Tips for Students New to the Field of Qualitative Research. The Qualitative Report 17. https://files.eric.ed.gov/fulltext/EJ990034.pdf
Assignment: Lesson 4
Graded as Pass/Fail | Due Date: 02/06/2021
Graded as Pass/Fail | Due Date: 02/06/2021 How would you apply one of the methods talked about today to plan for or design a data collection project that helps to fill the gaps beyond objects or collections databases?
Data Collection: Social Science Methods
Recorded Session: Data Collection: Social Science Methods
02/02/2021 at 1:00 PM (EST)   |  120 minutes
02/02/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Data Collection: Social Science Methods
Open to download resource.
Open to download resource.
Recorded Case Study with Ben Zweig
Open to view video.
Open to view video.
Case Study: Wikidata Links
Open to download resource.
Open to download resource.
Lesson 5: Overview / Readings / Assignment
Overview: Lesson 5
Open to download resource.
Open to download resource.
Pre-reading: Download OpenRefine
Select the "View" button to begin.
Select the "View" button to begin. Download OpenRefine to your computer: https://openrefine.org/download.html Contact the instructor, Kelly Davis, if you have issues so she can guide you prior to the live session.
Pre-reading: Cleaning Data with OpenRefine: Preamble
Select the "View" button to begin.
Select the "View" button to begin. Little, John. “Cleaning Data with OpenRefine: Preamble.” (2018), https://libjohn.github.io/openrefine/preamble.html [Watch the 6:47 minute video, not the workshop video]
Assignment: Lesson 5
Open to download resource.
Open to download resource. Use this dataset to perform the following ‘recipes’ of OpenRefine functions and monitor their outcomes. This data set includes bibliographic information on a set of scientific journal articles. Recipe 1: Cluster and standardize author names in column 2. Recipe 2: Cluster and standardize journal names in column 5. Recipe 3: Use the join function to concatenate columns 7-10, using a column separator of your choosing. Recipe 4: Undo the above, then replicate that function with a GREL expression. Recipe 5: *extra credit* Clean Column 5/Journal names, splitting out any extraneous information on the separators to achieve high quality data. Reconcile to Wikidata (API: https://openrefine-wikidata.toolforge.org/en/api).
Data Standardization
Recorded Session: Data Standardization
02/09/2021 at 1:00 PM (EST)   |  120 minutes
02/09/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Data Standardization
Open to download resource.
Open to download resource.
Lesson 6: Overview / Readings
Overview: Lesson 6
Open to download resource.
Open to download resource.
Pre-reading: Linked Data for Smart People Who Just Haven’t Learned about it Yet
Select the "View" button to begin.
Select the "View" button to begin. Miriam Posner, “Linked Data for Smart People Who Just Haven’t Learned about it Yet,” YouTube video, December 8, 2020. 18:43 https://www.youtube.com/watch?v=VZBpFiLbi-Y
Pre-reading: Relational Data Model
Select the "View" button to begin.
Select the "View" button to begin. w3schools.in, “Relational Data Model,” DBMS Tutorials. URL: https://www.w3schools.in/dbms/relation-data-model/
Pre-reading: Data Management Glossary
Select the "View" button to begin.
Select the "View" button to begin. SAP Insights, “Data Management Glossary.” URL: https://insights.sap.com/data-management-glossary/
Fundamentals of Databases
Recorded Session: Fundamentals of Databases
02/16/2021 at 1:00 PM (EST)   |  120 minutes
02/16/2021 at 1:00 PM (EST)   |  120 minutes
Slides: Fundamentals of Databases
Open to download resource.
Open to download resource.