Webinar, Feb. 20, 2018. David Newbury discusses how data is modeled and presented in memory institutions. He talks about his experiences with Art Tracks, Linked Art, the American Art collaboration, and other projects, discussing how those experiences helped him better understand data modeling and how we can represent objects.
http://imatge-upc.github.io/telecombcn-2016-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
Presented at the Coalition of Networked Information (CNI) Spring 2024 Project Briefings.
Over the past six years, Getty has been engaged in a project to transform and unify its complex digital infrastructure for cultural heritage information. One of the project’s core goals was to provide validation of the impact and value of the use of linked data throughout this process. With museum, archival, media, and vocabularies in production and others underway, this sessions shares some of the practical implications (and pitfalls) of this work—particularly as it relates to interoperability, discovery, staffing, stakeholder engagement, and complexity management. The session will also share examples of how other organizations can streamline their own, similar work going forward.
In this original Digital Art and Philosophy class, we will become familiar with different forms of digital art and related philosophical issues. Digital art is anything related to computers and art such as using a computer to create art or an art display that is digitized. Philosophical aspects arise regarding art, identity, performance, interactivity, and the process of creation. Students may respond to the material in essay, performance, or digital art work (optional). Instructor: Melanie Swan. Syllabus: www.MelanieSwan.com/PCA
http://imatge-upc.github.io/telecombcn-2016-dlcv/
Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
Presented at the Coalition of Networked Information (CNI) Spring 2024 Project Briefings.
Over the past six years, Getty has been engaged in a project to transform and unify its complex digital infrastructure for cultural heritage information. One of the project’s core goals was to provide validation of the impact and value of the use of linked data throughout this process. With museum, archival, media, and vocabularies in production and others underway, this sessions shares some of the practical implications (and pitfalls) of this work—particularly as it relates to interoperability, discovery, staffing, stakeholder engagement, and complexity management. The session will also share examples of how other organizations can streamline their own, similar work going forward.
In this original Digital Art and Philosophy class, we will become familiar with different forms of digital art and related philosophical issues. Digital art is anything related to computers and art such as using a computer to create art or an art display that is digitized. Philosophical aspects arise regarding art, identity, performance, interactivity, and the process of creation. Students may respond to the material in essay, performance, or digital art work (optional). Instructor: Melanie Swan. Syllabus: www.MelanieSwan.com/PCA
Explain the term "digital humanities," and how it is understood across humanities disciplines.
Describe the research journey as a partnership between researcher and library collections and staff.
List examples of the limits of classification.
Describe the implicit and explicit hierarchies that are created when gathering and analyzing data.
Distinguish between what counts as data and what does not.
Identify different data formats and how they fit into a research workflow.
Getty Scholars’ Workspace: Online collaboration and publication tools for sch...Susan Edwards
Presentation given with Will Lanni at MCN 2013 in Montreal, Canada on November 23, 2013
Presentation recording: http://www.youtube.com/watch?v=cL0_2KUwrCo&feature=youtu.be
People's mode of online engagement: The Many Faces of Digital Visitors and Re...Lynn Connaway
Connaway, L. S. (2018). People's mode of online engagement: The Many Faces of Digital Visitors and Residents. Presented at the iConference, March 26, 2018, Sheffield, United Kingdom.
People's mode of online engagement: The Many Faces of Digital Visitors and R...OCLC
Connaway, L. S. (2018). People's mode of online engagement: The Many Faces of Digital Visitors and Residents. Presented at the iConference, March 26, 2018, Sheffield, United Kingdom.
Knowledge Architecture: Graphing Your KnowledgeNeo4j
Ask any project manager and they will tell you the importance of reviewing lessons learned prior to starting a new project. The lesson learned databases are filled with nuggets of valuable information to help project teams increase the likelihood of project success. Why then do most lesson learned databases go unused by project teams? In my experience, they are difficult to search through and require hours of time to review the result set.
Recently I had a project engineer ask me if we could search our lessons learned using a list of 22 key terms the team was interested in. Our current keyword search engine would require him to enter each term individually, select the link, and save the document for review. Also, there was no way to search only the database, the query would search our entire corpus, close to 20 million URLs. This would not do. I asked our search team if they would run a special query against the lesson database only, using the terms provided. They returned a spreadsheet with a link to each document containing the terms. The engineer had his work cut out for him: over 1100 documents were on the list;.
I started thinking there had to be a better way. I had been experimenting with topic modeling, in particular to assist our users in connecting seemingly disparate documents through an easier visualization mechanism. Something better than a list of links on multiple pages. I gathered my toolbox: R/RStudio, for the topic modeling and exploring the data; Neo4j, for modeling and visualizing the topics; and Linkurious, a web front end for our users to search and visualize the graph database.
Improving Collection Understanding in Web ArchivesShawn Jones
We propose using visualization of representative mementos to aide in collection understanding of web archive collections, as inspired by AlNomanay's work.
Data Science in 2016: Moving up by Paco Nathan at Big Data Spain 2015Big Data Spain
The term 'Data Science' was first described in scientific literature about 15 years ago. It started to become a major trend in industry about 7 years ago.
O'Reilly Media surveys the industry extensively each year. In addition we get a good birds-eye view of industry trends through our conference programs and publications, working closely with some of the best practitioners in Data Science.
By now, the field has evolved far beyond its origins eclipsing an earlier generation of Business Intelligence and Data Warehousing approaches. Data Science is moving up, into the business verticals and government spheres of influence where it has true global impact.
This talk considers Data Science trends from the past three years in particular. What is emerging? Which parts are evolving? Which seem cluttered and poised for consolidation or other change?
Session presented at Big Data Spain 2015 Conference
15th Oct 2015
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Abstract: http://www.bigdataspain.org/program/thu/slot-2.html
The LOD Gateway: Open Source Infrastructure for Linked DataDavid Newbury
Presented at the CIDOC conference in Mexico City, 2023, this talk provides a walkthrough of the digital infrastructure behind the LOD Gateway, a critical part of Getty's digital API infrastructure.
It discusses the difference between graphs, documents, and how both are important for different use cases.
As part of MuseWeb 2023 in Washington, DC, this presentation walks through the basics of Linked Data, and then discusses the six levels of implementation of Linked Data, using the Getty's work as examples.
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Explain the term "digital humanities," and how it is understood across humanities disciplines.
Describe the research journey as a partnership between researcher and library collections and staff.
List examples of the limits of classification.
Describe the implicit and explicit hierarchies that are created when gathering and analyzing data.
Distinguish between what counts as data and what does not.
Identify different data formats and how they fit into a research workflow.
Getty Scholars’ Workspace: Online collaboration and publication tools for sch...Susan Edwards
Presentation given with Will Lanni at MCN 2013 in Montreal, Canada on November 23, 2013
Presentation recording: http://www.youtube.com/watch?v=cL0_2KUwrCo&feature=youtu.be
People's mode of online engagement: The Many Faces of Digital Visitors and Re...Lynn Connaway
Connaway, L. S. (2018). People's mode of online engagement: The Many Faces of Digital Visitors and Residents. Presented at the iConference, March 26, 2018, Sheffield, United Kingdom.
People's mode of online engagement: The Many Faces of Digital Visitors and R...OCLC
Connaway, L. S. (2018). People's mode of online engagement: The Many Faces of Digital Visitors and Residents. Presented at the iConference, March 26, 2018, Sheffield, United Kingdom.
Knowledge Architecture: Graphing Your KnowledgeNeo4j
Ask any project manager and they will tell you the importance of reviewing lessons learned prior to starting a new project. The lesson learned databases are filled with nuggets of valuable information to help project teams increase the likelihood of project success. Why then do most lesson learned databases go unused by project teams? In my experience, they are difficult to search through and require hours of time to review the result set.
Recently I had a project engineer ask me if we could search our lessons learned using a list of 22 key terms the team was interested in. Our current keyword search engine would require him to enter each term individually, select the link, and save the document for review. Also, there was no way to search only the database, the query would search our entire corpus, close to 20 million URLs. This would not do. I asked our search team if they would run a special query against the lesson database only, using the terms provided. They returned a spreadsheet with a link to each document containing the terms. The engineer had his work cut out for him: over 1100 documents were on the list;.
I started thinking there had to be a better way. I had been experimenting with topic modeling, in particular to assist our users in connecting seemingly disparate documents through an easier visualization mechanism. Something better than a list of links on multiple pages. I gathered my toolbox: R/RStudio, for the topic modeling and exploring the data; Neo4j, for modeling and visualizing the topics; and Linkurious, a web front end for our users to search and visualize the graph database.
Improving Collection Understanding in Web ArchivesShawn Jones
We propose using visualization of representative mementos to aide in collection understanding of web archive collections, as inspired by AlNomanay's work.
Data Science in 2016: Moving up by Paco Nathan at Big Data Spain 2015Big Data Spain
The term 'Data Science' was first described in scientific literature about 15 years ago. It started to become a major trend in industry about 7 years ago.
O'Reilly Media surveys the industry extensively each year. In addition we get a good birds-eye view of industry trends through our conference programs and publications, working closely with some of the best practitioners in Data Science.
By now, the field has evolved far beyond its origins eclipsing an earlier generation of Business Intelligence and Data Warehousing approaches. Data Science is moving up, into the business verticals and government spheres of influence where it has true global impact.
This talk considers Data Science trends from the past three years in particular. What is emerging? Which parts are evolving? Which seem cluttered and poised for consolidation or other change?
Session presented at Big Data Spain 2015 Conference
15th Oct 2015
Kinépolis Madrid
http://www.bigdataspain.org
Event promoted by: http://www.paradigmatecnologico.com
Abstract: http://www.bigdataspain.org/program/thu/slot-2.html
The LOD Gateway: Open Source Infrastructure for Linked DataDavid Newbury
Presented at the CIDOC conference in Mexico City, 2023, this talk provides a walkthrough of the digital infrastructure behind the LOD Gateway, a critical part of Getty's digital API infrastructure.
It discusses the difference between graphs, documents, and how both are important for different use cases.
As part of MuseWeb 2023 in Washington, DC, this presentation walks through the basics of Linked Data, and then discusses the six levels of implementation of Linked Data, using the Getty's work as examples.
USE ME: progressive integration of IIIF with new software services at the GettyDavid Newbury
Two years into the launch of an institution-wide IIIF delivery system and the related ETL pipelines to generate IIIF master images and manifests, two ongoing challenges have been unfolding in the broader Getty Digital development plans: making use of these IIIF services by default, and consequently, improving those services in a continuous fashion.
This 20-minute presentation will offer an overview of the integration of various Getty software development projects with the existing IIIF and Linked Open Data infrastructure, including our public LOD access endpoints, data analysis and annotation projects, and public-facing websites and research tools. The goal is to highlight how Getty Digital has come past the initial investment of building infrastructure and beginning to reap the long-term benefits of such investment.
IIIF Across Platforms | IIIF Community Call, January 2021David Newbury
David Newbury, Head of Software at Getty, presents on Getty's work using the IIIF APIs to provide access to images from the Ed Ruscha Streets of Los Angeles Archive in multiple interfaces, meeting the needs of different audiences, and shares lessons learned in the development of both projects:
https://12sunsets.getty.edu and https://www.getty.edu/research/collections
Thinking through the implications of treating the IIIF canvas as a resource in itself, not just as an internal building block of a IIIF Manifest.
Presented at the Fall 2020 IIIF Working group on December 2nd.
Have you ever wished that IIIF was just a little bit MORE complicated?
While the IIIF specifications provide lots of clever features, sometimes you need to do something outside what the specifications describe. Maybe that's adding "date modified" or "date created" to your Manifests, maybe it's doing palette analysis of your Canvases, or maybe you need to add structured metadata about the objects represented in the image.
These all seem like they should be possible in IIIF, but it can be hard to figure out the correct way to add this kind of custom information using IIIF, particularly if you think other people might want to do the same thing. In the upcoming IIIF 3.0 specifications, we've clarified the various ways that you can extend IIIF.
In this presentation, I'll walk through the extension mechanisms in IIIF: services, extensions, seeAlso, and rendering links. I'll provide examples and guidelines, as well as explain some of the reasoning behind the various mechanisms.
With apologies to Clifford Simak, time is *never* the simplest thing. One of the most common issues with dealing with cultural data is time. The humanities are almost always interested in that which takes place over time, but the way that humanists think about time and dates is fuzzy—full of imprecision, approximations, and generalities.
Unfortunately, while humans are fully capable of dealing with that ambiguity, computers are not: existing software needs a level of temporal precision that is impractical for cultural data. To bridge this gap, we need to precisely express the fuzziness of our dates. Over the past decades, tools and techniques such as Allen's Interval algebra, the Library of Congress's Extended Date Time Format, and the CIDOC CRM's time-span model have been developed to help model this fuzziness, but they are often so complex as to appear unusable by both humanists and technologists.
In this paper, I will present a technique developed as part of the Art Tracks project at the Carnegie Museum of Art for converting natural language statements such as "sometime after the 1970s" or "until at least the 17th century" into precisely defined expressions of temporal fuzziness usable by computers, technologists, and humanists alike.
21st Century Provenance: Lessons Learned Building Art TracksDavid Newbury
This talk, given at the Yale Center for British Art on February 27th, 2017, discusses how Art Tracks, CMOA’s National Endowment for the Humanities-funded digital provenance project, was formed through the combined efforts of technologists, curators, and provenance researchers. We provided an overview of the project, discussed our current research of the Northbrook Collection, and shared insights about the collaboration that resulted from this cross-disciplinary project.
Video is available at http://britishart.yale.edu/multimedia-video/27/4261
Art Tracks: From Provenance to Structured DataDavid Newbury
This keynote presentation was given by David Newbury and Louise Lippincott as part of the Smithsonian Provenance Research Institute's PREP program at the Metropolitan Museum of Art in New York on February 7th, 2017
This is an Ignite talk given at MCN 2016 on my views and opinions around Linked Data in the museum field.
This talk was recorded and is available on YouTube: https://www.youtube.com/watch?v=0RysOdsZtf8
These are slides for a workshop on D3 given at the Studio for Creative Inquiry at Carnegie Mellon University on October 28th, 2016.
For more context, see http://d3.workergnome.com
This presentation was given as part of the 2016 Digital Provenance Symposium at the Carnegie Museum of Art on October 14th, 2016.
It describes the current state of the technology of the Art Tracks project, a digital standard for museum provenance in Linked Data.
Using Linked Data: American Art Collaborative, Oct. 3, 2016David Newbury
Linked Data is a interesting topic in museums, but how do we actually use it? This talk profiles several ways the Carnegie Museum of Art uses Linked Data, and talks about when and where Linked Data can be useful.
Data 101: Making Charts from SpreadsheetsDavid Newbury
The fundamental tools of data visualization are the spreadsheet and the chart. Modern spreadsheet software like Microsoft Excel or Google Sheets make generating charts easy, but there are so many types of charts and ways to configure them that it can be difficult to know how to get started, or how to choose the best chart to help tell your story. In this workshop, we will explore the types of charts available, describe the differences between them, when each is appropriate, and work through creating and customizing a chart to help tell a specific story.
This workshop is designed for people with basic spreadsheet skills, but no previous experience with making charts is required. If you’re comfortable reading and entering data using spreadsheet software like Excel or Google Sheets, you are ready for this workshop!
Given August 30th at the East Liberty Branch of the Pittsburgh Public Library
IIIF, or the International Image Interoperability Framework, is an emerging Linked Open Data standard for image interoperability. It defines metadata standards for dealing with high-resolution images, providing a consistent API for accessing both images, the metadata that surrounds them, and how to present and associate images together. It is being used at the Internet Archive as well as major museums and national libraries around the world.
By employing this emerging digital standard to host image metadata, it allows image resources to be easily shared, incorporated, and recontextualized without loss of authority or human intervention.
While the standard is comprehensive and extremetly useful, often the infrastructure requirements to deploy IIIF appear to be out of the scope of smaller projects and institutions. As part of the new archival website at the Carnegie Museum of Art, we have identified techniques and developed open source tools that allow institutions and projects to implement the base profile of IIIF on a shoestring budget, using Amazon S3, spreadsheets, and other simple tools.
I propose a short presentation providing an overview of IIIF, a demonstration of its use at other institutions, a review of how CMOA is using this tool to facilitate sharing of images, and an brief explanation of how other institutions can use our tools to facilitate sharing their images using IIIF.
Presented at Keystone DH 2016.
http://keystonedh.network/2016/abstracts/#submission-9
Authority Cascades: A presentation strategy for Linked Open DataDavid Newbury
As Linked Open Data is increasingly embraced throughout the cultural heritage sector, we are moving from an environment of data scarcity to an environment of data overload. For example, often we no longer have a single authority for the names and identities of the participants in some activity or event, but two, three, or even more. Getty ULAN, VIAF, Wikidata, and other authorities provide a wealth of information about important people throughout history. However, no authority is comprehensive, and due to the Open World Assumption different authorities may provide conflicting or inconsistent information about a single participant.
While Linked Open Data is designed to accomodate these conflicts at the data level, this new profusion of authority records presents problems and requires new strategies for dealing with overlaps and conflicts in the presentation of Linked Open Data. Also, often there exist records that do not exist in any authority, but that emerge through research and must be incorporated in any given project.
I propose a short presentation on authority cascades, a practical technique for both querying and accomodating these inconsistencies in a logical, easily understandable way. This technique allows for institutions or projects to leverage Linked Open Data, while remaining their own “authority of last resort”. By cascading down a implementation-defined list of authority sources, a single, comprehensive presentation of information can be created.
Presented at Keystone DH, June 23, 2016. http://keystonedh.network/2016/abstracts/#submission-10
Data 101: Introduction to Data VisualizationDavid Newbury
Do you want to make pictures using data but don't know where to start? Would you like to learn how data visualization works, and how to tell stories with data?
This workshop by David Newbury explores the history of data visualization from the first maps to the latest interactive tools from the New York Times.The workshop will also discuss the hows and whys of storytelling with data. It finshes with a collaborative exploration of data visualization using Sharpies, Post-It notes, and things that begin with "S".
No computers will be used in this class, and there are no prerequisites. As a result of this workshop, you'll have a stronger foundation in understanding how to communicate information more-effectively.
We’re excited to partner with the Carnegie Library of Pittsburgh on a “Data 101” training series designed to build information literacy, mapping, and data visualization skills for people looking to get started in using data, or more-experienced users looking to brush-up on their skills. The training sessions will be offered monthly at one of the Library’s branches, and will be followed by ample time to practice what you’ve learned.
This first class on data visualization was offered on the morning of May 10, 2016 at the East Liberty Branch.
A process server is a authorized person for delivering legal documents, such as summons, complaints, subpoenas, and other court papers, to peoples involved in legal proceedings.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Russian anarchist and anti-war movement in the third year of full-scale warAntti Rautiainen
Anarchist group ANA Regensburg hosted my online-presentation on 16th of May 2024, in which I discussed tactics of anti-war activism in Russia, and reasons why the anti-war movement has not been able to make an impact to change the course of events yet. Cases of anarchists repressed for anti-war activities are presented, as well as strategies of support for political prisoners, and modest successes in supporting their struggles.
Thumbnail picture is by MediaZona, you may read their report on anti-war arson attacks in Russia here: https://en.zona.media/article/2022/10/13/burn-map
Links:
Autonomous Action
http://Avtonom.org
Anarchist Black Cross Moscow
http://Avtonom.org/abc
Solidarity Zone
https://t.me/solidarity_zone
Memorial
https://memopzk.org/, https://t.me/pzk_memorial
OVD-Info
https://en.ovdinfo.org/antiwar-ovd-info-guide
RosUznik
https://rosuznik.org/
Uznik Online
http://uznikonline.tilda.ws/
Russian Reader
https://therussianreader.com/
ABC Irkutsk
https://abc38.noblogs.org/
Send mail to prisoners from abroad:
http://Prisonmail.online
YouTube: https://youtu.be/c5nSOdU48O8
Spotify: https://podcasters.spotify.com/pod/show/libertarianlifecoach/episodes/Russian-anarchist-and-anti-war-movement-in-the-third-year-of-full-scale-war-e2k8ai4
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
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This session provides a comprehensive overview of the latest updates to the Uniform Administrative Requirements, Cost Principles, and Audit Requirements for Federal Awards (commonly known as the Uniform Guidance) outlined in the 2 CFR 200.
With a focus on the 2024 revisions issued by the Office of Management and Budget (OMB), participants will gain insight into the key changes affecting federal grant recipients. The session will delve into critical regulatory updates, providing attendees with the knowledge and tools necessary to navigate and comply with the evolving landscape of federal grant management.
Learning Objectives:
- Understand the rationale behind the 2024 updates to the Uniform Guidance outlined in 2 CFR 200, and their implications for federal grant recipients.
- Identify the key changes and revisions introduced by the Office of Management and Budget (OMB) in the 2024 edition of 2 CFR 200.
- Gain proficiency in applying the updated regulations to ensure compliance with federal grant requirements and avoid potential audit findings.
- Develop strategies for effectively implementing the new guidelines within the grant management processes of their respective organizations, fostering efficiency and accountability in federal grant administration.
Understanding the Challenges of Street ChildrenSERUDS INDIA
By raising awareness, providing support, advocating for change, and offering assistance to children in need, individuals can play a crucial role in improving the lives of street children and helping them realize their full potential
Donate Us
https://serudsindia.org/how-individuals-can-support-street-children-in-india/
#donatefororphan, #donateforhomelesschildren, #childeducation, #ngochildeducation, #donateforeducation, #donationforchildeducation, #sponsorforpoorchild, #sponsororphanage #sponsororphanchild, #donation, #education, #charity, #educationforchild, #seruds, #kurnool, #joyhome
Transit-Oriented Development Study Working Group Meeting
NDSR Learning Enrichment: Data Models and Linked Data
1. Learning Enrichment Session
David Newbury
Software & Data Architect
J. Paul Getty Trust
February 20th, 2018
Learning Enrichment Session — David Newbury (@workergnome) 1
2. My job is to bring together:
• an Archive
• a Library
• a Conservation science lab
• a Publishing house
• a Museum
• a Foundation
...through software and data.
Learning Enrichment Session — David Newbury (@workergnome) 2
14. On Modeling & Mapping the Real
When we create data,
we're creating an
abstraction of reality.
Learning Enrichment Session — David Newbury (@workergnome) 14
15. "When you design and build a
computer system, you first
formulate a model of the problem
you want it to solve, and then
construct the computer program
in its terms."
- Brian Cantwell Smith, The Limits of Correctness (1985)
Learning Enrichment Session — David Newbury (@workergnome) 15
16. On October 5, 1960, the
American Ballistic Missile Early-
Warning System indicated Soviet
missiles headed towards the
United States.
The moon had risen, and was
reflecting radar signals back to
earth. Needless to say, this lunar
reflection hadn't been predicted
by the system's designers.
Learning Enrichment Session — David Newbury (@workergnome) 16
17. Whose fault was it?
Learning Enrichment Session — David Newbury (@workergnome) 17
18. "...every act of conceptualization,
analysis, categorization, does a
certain amount of violence to its
subject matter, in order to get at the
underlying regularities that group
things together.""
- Brian Cantwell Smith, The Limits of Correctness (1985)
Learning Enrichment Session — David Newbury (@workergnome) 18
19. On Exactitude in Science
A 1:1 scale map
is not a useful
abstraction.
Learning Enrichment Session — David Newbury (@workergnome) 19
20. There will never be
a correct data model.
Learning Enrichment Session — David Newbury (@workergnome) 20
21. There will only be
useful data models.
Learning Enrichment Session — David Newbury (@workergnome) 21
22. What is a useful Data Model?
As memory institutions,
we structure and record
information about objects.
We do this because objects
are representations of
shared cultural knowledge.
Learning Enrichment Session — David Newbury (@workergnome) 22
23. Seven ways to look at objects.
Learning Enrichment Session — David Newbury (@workergnome) 23
24. Objects are Things.
Objects exist in space and time.
They have weight, and size, and are made of materials.
They are conserved, moved, bought, sold, and described.
These objects are related to people, events, and places
through physical, legal, or social interaction.
Example Data Models:
LIDO, CIDOC-CRM, Schema.org, CDWA, MARC
Learning Enrichment Session — David Newbury (@workergnome) 24
25. Objects exist in Context.
Objects are grouped, ordered, described, & summarized.
These intellectual structures provide context and
meaning to the objects as part of a larger whole.
Example Data Models:
EAD, ISAD(G), Dewey Decimal, RiC
Learning Enrichment Session — David Newbury (@workergnome) 25
26. Objects can be Reproductions.
Objects have shared heritage with other objects.
The physical or intellectual connections between a
specific instance and an abstract work it reproduces can
be essential to our understanding of that object.
Example Data Models:
FRBR, Bibframe
Learning Enrichment Session — David Newbury (@workergnome) 26
27. Objects have Proxies.
Objects are represented as structured data.
This includes data and digitized representations of an
object. Proxies often have their own metadata
describing the characteristics and context of the proxy.
Example Data Models:
IIIF, METS, Dublin Core, EXIF
Learning Enrichment Session — David Newbury (@workergnome) 27
28. Objects are Managed.
Policies and rules govern interaction with objects.
These codify how an object should be stored and what
environment it should be kept in, who can access the
object, and what restrictions apply to that access.
Example Data Models:
Rightsstatement.org, PREMIS
Learning Enrichment Session — David Newbury (@workergnome) 28
29. Objects can contain or embody Representations.
Objects often depict or describe referents. These may be
real times, places, objects, and people, or they may be
fictitious.
Example Data Models:
GeoJSON, EAC, Iconclass,TEI
Learning Enrichment Session — David Newbury (@workergnome) 29
30. Objects are Intellectual Works.
Objects interpret of the world around them.
They are made with intent, within intellectual
frameworks and genres, and others assign meaning and
value to them. They can both participate in and
engender argumentation and scholarship.
Example Data Models:
???
Learning Enrichment Session — David Newbury (@workergnome) 30
31. It's a little overwhelming,
isn't it?
Learning Enrichment Session — David Newbury (@workergnome) 31
32. If you wish to make an apple pie
from scratch, you must first
invent the universe.
— Carl Sagan
Learning Enrichment Session — David Newbury (@workergnome) 32
33. When eating an elephant take
one bite at a time.
— Creighton Williams Abrams Jr.
Learning Enrichment Session — David Newbury (@workergnome) 33
34. Lessons Learned: Art Tracks
How do you design a data model
that represents the history of an object,
and how do you express it using Linked Data?
Learning Enrichment Session — David Newbury (@workergnome) 34
35. Art TracksFunded by the Institute of Museum and Library Services.
ca. 2013-2015
National Endowment for the Humanities,
Kress Foundation,
Paul Mellon Center
ca.2016-2017
Originally, Art Tracks was
a data visualization project.
Only, we didn't have data.
Learning Enrichment Session — David Newbury (@workergnome) 35
36. Traditional Provenance
Durand-Ruel, Paris, August 23, 1872 [1];
Catholina Lambert, New Jersey;
Lambert sale, American Art Association, Plaza Hotel, New York, NY,
February 21, 1916 until February 24, 1916, no. 67;
Durand-Ruel, Paris, until at least 1930;
purchased by Simon Bauer, Paris, by June 1936 [2];
anonymous sale, Parke-Bernet Galleries, Inc., February 25, 1970, no. 19 [3];
Sam Salz, Inc., New York, NY;
purchased by Museum, May 1971.
Notes:
[1] bought from the artist.
[2] Listed and illustrated in "List of Property Removed from France
during the War 1939-1945" (no. 7114, as belonging to Simon Bauer).
[3] "Highly Important Impressionist, Post-Impressionist &
Modern Paintings and Drawings", illustrated.
Learning Enrichment Session — David Newbury (@workergnome) 36
42. Are we
Publishers?
Yes.
But we do more than publish
information—we generate our own.
Learning Enrichment Session — David Newbury (@workergnome) 42
43. Are we
Researchers?
Yes.
But we don't generate random
information, we research specific
objects.
Learning Enrichment Session — David Newbury (@workergnome) 43
44. We are
Collections.
We don't just collect.
We research, collect, and preserve
information about our objects, as
well as the events, people, and
topics that give them context.
Learning Enrichment Session — David Newbury (@workergnome) 44
45. The Promise of Linked Data:
[The] creation of a common framework that allows data
to be shared and reused across application, enterprise,
and community boundaries, to be processed
automatically by tools as well as manually, including
revealing possible new relationships among pieces of
data.
— W3C Semantic Web Working Group
Learning Enrichment Session — David Newbury (@workergnome) 45
46. Linked Data:
Where is this
magical future?
Learning Enrichment Session — David Newbury (@workergnome) 46
47. What doesn't Linked Data do?
Enable
Web Scale AI
Learning Enrichment Session — David Newbury (@workergnome) 47
48. What doesn't Linked Data do?
Create Easy
Interoperability
Learning Enrichment Session — David Newbury (@workergnome) 48
49. What doesn't Linked Data do?
Automate
Reconciliation
Learning Enrichment Session — David Newbury (@workergnome) 49
50. What doesn't Linked Data do?
Reduce
our Workload
Learning Enrichment Session — David Newbury (@workergnome) 50
51. An awkward
moment goes here.
(This could be a very short talk.)
Learning Enrichment Session — David Newbury (@workergnome) 51
52. Linked Data is
not a magic bullet.
It's one of a many possible abstract
data models, each of which have
tradeoffs.
Learning Enrichment Session — David Newbury (@workergnome) 52
53. Art Tracks, Phase II
Funded by the National Endowment for the Humanities.
ca. 2016-2017
How to express provenance information as:
• Linked Open Data
• JSON data structure
• Standardized text
All three forms must contain
the same information, and
we must be able to convert
between them.
Learning Enrichment Session — David Newbury (@workergnome) 53
60. Mary Cassatt, Young Women Picking Fruit.
Carnegie Museum of Art.
Learning Enrichment Session — David Newbury (@workergnome) 60
61. Mary Cassatt, Young Women Picking Fruit.
Carnegie Museum of Art, 1894.
Mary Cassatt [1844-1926], France; Galeries Durand-Ruel,
Paris, France, by August 1892 [1]; Durand-Ruel Galleries,
New York, NY, 1895; purchased by Department of Fine
Arts, Carnegie Institute, Pittsburgh, PA, October 1922.
Notes:
[1]. Recorded in stock book in August 1892.
Learning Enrichment Session — David Newbury (@workergnome) 61
63. Mary Cassatt, Young Women Picking Fruit.
Carnegie Museum of Art, 1894.
Mary Cassatt [1844-1926], France; Galeries Durand-Ruel,
Paris, France, by August 1892 [1]; Durand-Ruel Galleries,
New York, NY, 1895; purchased by Department of Fine
Arts, Carnegie Institute, Pittsburgh, PA, October 1922.
Notes:
[1]. Recorded in stock book in August 1892.
Authorities:
Mary Cassatt: see http://viaf.org/viaf/2478969/
Galeries Durand-Ruel: see http://viaf.org/viaf/153354503
Durand-Ruel Galleries: see http://viaf.org/viaf/134060200
Department of Fine Arts, Carnegie Institute: see http://viaf.org/viaf/147742484
France: see http://vocab.getty.edu/tgn/1000070
Paris, France: see http://vocab.getty.edu/tgn/7008038
New York, NY: see http://vocab.getty.edu/tgn/7007567
Pittsburgh, PA: see http://vocab.getty.edu/tgn/7013927
Learning Enrichment Session — David Newbury (@workergnome) 63
64. Reason #1:
Linking to Other
Authorities
and the Local Heroes Problem
Learning Enrichment Session — David Newbury (@workergnome) 64
65. Authority,
Identity, & Trust.
We're making authoritative
assertions about identity.
We want to be the "source of truth"
for the objects in our collections.
Learning Enrichment Session — David Newbury (@workergnome) 65
66. Authority isn't free.
Maintaining authority takes
enormous time and resources.
Learning Enrichment Session — David Newbury (@workergnome) 66
67. The world is vast.
To fully describe everything that
connects to our collection, we
must describe the universe.
Learning Enrichment Session — David Newbury (@workergnome) 67
68. Budgets are...less vast.
How can we be authoritative
without being encyclopedic?
Learning Enrichment Session — David Newbury (@workergnome) 68
69. Asserted Authority.
When you want to be
the authority of record
for something or someone.
Learning Enrichment Session — David Newbury (@workergnome) 69
71. Delegated Authority.
When you want to point to
someone who you trust to be
the authority of record.
Learning Enrichment Session — David Newbury (@workergnome) 71
72. Getty Vocabularies
Shared Authority files
One source of authority maintained
by an trusted institution.
Learning Enrichment Session — David Newbury (@workergnome) 72
73. Reluctant Authority.
When you cannot find
an authority you trust.
Learning Enrichment Session — David Newbury (@workergnome) 73
75. Mary Cassatt, Young Women Picking Fruit.
Carnegie Museum of Art, 1894.
Mary Cassatt [1844-1926], France;
Galeries Durand-Ruel, Paris, France, by August 1892 [1];
Durand-Ruel Galleries, New York, NY, 1895;
purchased by Department of Fine Arts, Carnegie Institute,
Pittsburgh, PA, October 1922.
Notes:
[1]. Recorded in stock book in August 1892.
Authorities:
Mary Cassatt: see http://viaf.org/viaf/2478969/
Galeries Durand-Ruel: see http://viaf.org/viaf/153354503
Durand-Ruel Galleries: see http://viaf.org/viaf/134060200
Department of Fine Arts, Carnegie Institute: see http://viaf.org/viaf/147742484
France: see http://vocab.getty.edu/tgn/1000070
Paris, France: see http://vocab.getty.edu/tgn/7008038
New York, NY: see http://vocab.getty.edu/tgn/7007567
Pittsburgh, PA: see http://vocab.getty.edu/tgn/7013927
Learning Enrichment Session — David Newbury (@workergnome) 75
76. Reason #2:
Shared Semantics
How do we know we're talking about the same thing?
Learning Enrichment Session — David Newbury (@workergnome) 76
77. JSON Data
Structure
This is understandable,
If you're me.
But you're not me.
Learning Enrichment Session — David Newbury (@workergnome) 77
78. Linked Data as
Documentation
When I say "Transfer of Custody",
I mean...
Learning Enrichment Session — David Newbury (@workergnome) 78
79. JSON-LD &
CIDOC-CRM
This is more complex,
but that complexity
is documented.
Learning Enrichment Session — David Newbury (@workergnome) 79
83. Galeries Durand-Ruel, Paris, France, by August 1892 [1];
Notes:
[1]. Recorded in stock book in August 1892.
Authorities:
Durand-Ruel Galleries: #1 http://viaf.org/viaf/134060200
Paris, France: see http://vocab.getty.edu/tgn/7008038
Learning Enrichment Session — David Newbury (@workergnome) 83
91. To Recap:
1. Shared Authority
2. Shared Understanding
3. Easy Collaboration
4. Planning for the Future
Learning Enrichment Session — David Newbury (@workergnome) 91
92. Two parts to my job:
Data
Software
Learning Enrichment Session — David Newbury (@workergnome) 92
93. What is Software?
Software automates practice,
allowing us to be more efficient.
Learning Enrichment Session — David Newbury (@workergnome) 93
94. Digital data and
software are
utterly
intertwined.
We digitize data so that software
can interact with it.
Learning Enrichment Session — David Newbury (@workergnome) 94
96. Which of these is truer?
— Probably born 1950.
— Likely born 1950.
Humans don't think about "Truer" that way...
but computers do.
Learning Enrichment Session — David Newbury (@workergnome) 96
98. American Art
Collaborative
Modeling the collections of
14 institutions so that software can
interact with them.
Learning Enrichment Session — David Newbury (@workergnome) 98
99. Linked Art:
A standardized data model using
CIDOC-CRM that describes the
objectness of objects, designed
to enable software development
against Linked Open Data.
http://linked.art
Learning Enrichment Session — David Newbury (@workergnome) 99
100. Thank you for listening!
Questions?
Learning Enrichment Session — David Newbury (@workergnome) 100