They have left the building: The Web Route to Library UsersRichard Wallis
Keynote Presentation to the ACOC Seminar in Melbourne Australia 1st November 2013.
Reviewing how libraries need to look towards using Linked Data techniques and general vocabularies, such as Schema.org, to share their data with the wider web - helping the search engines to guide users back to library collections.
They have left the building: The Web Route to Library UsersRichard Wallis
Keynote Presentation to the ACOC Seminar in Melbourne Australia 1st November 2013.
Reviewing how libraries need to look towards using Linked Data techniques and general vocabularies, such as Schema.org, to share their data with the wider web - helping the search engines to guide users back to library collections.
Getting Started with Regular Expressions In MarcEditTerry Reese
This is a beginners video developed to give new users to MarcEdit's regular expression syntax a primer and examples on how to use the language. It provides information on strategies, resources, and hopefully, some useful hints to help get people started.
These slides accompanied a youtube video which is available at: https://youtu.be/7YXvS4xBEfw
Inovação com Software usando a metodologia Lean StartupsUFPA
Você já percebeu que as grandes inovações e negócios da atualidade, além de um
modelo de negócios inovador, possuem alguma dependência de tecnologias baseadas
em software? São sites, aplicativos e dispositivos que facilitam a busca e compra de
produtos, parceiros, soluções sustentáveis, entre outras inovações. Apesar destas
facilidades, construir software não é uma tarefa simples, tanto do ponto de vista do
empreendedor que encomenda o software quanto para quem vai produzi-lo. Nesta
palestra abordaremos como a metodologia Lean Startup pode ser utilizada para ajudar
a reduzir os riscos de investimentos em produtos que não inovam no mercado e podem
frustrar os empreendedores em seus projetos
Presentation to SWIB23 in Berlin.
The journey to implement a production Linked Data Management and Discovery System for the National Library Board of Singapore.
Linked Data: from Library Entities to the Web of DataRichard Wallis
Presentation to the ALCTS session "International Developments in Library Linked Data: Think Globally" at the American Library Association Conference in Las Vegas - June 2014
Linked Open Data and The Digital Archaeological Workflow at the Swedish Natio...Marcus Smith
A presentation of two aspects of the linked open data work ongoing at the Swedish National Heritage Board (Riksantikvarieämbetet): Swedish Open Cultural Heritage (SOCH/K-samsök) and the Digital Archaeological Process (DAP).
Delivered at the Smithsonian, Washington, DC, 2014-11-10
A presentation by Richard Wallis, Technology Evangelist at OCLC.
Delivered at the Cataloguing and Indexing Group Scotland (CIGS) Linked Open Data (LOD) Conference which took place Fri 21 September 2012 at the Edinburgh Centre for Carbon Innovation.
It19 20140721 linked data personal perspectiveJanifer Gatenby
A presentation made for Standards Australia's seminar. Outlines the basic aspects of linked data from a personal perspective and where it fits with direct and subject searching.
IWMW 2003: Semantic Web Technologies for UK HE and FE Institutions (Part 2)IWMW
Slides for plenary talk on "Semantic Web Technologies for UK HE and FE Institutions" given by Dave Beckett and Brian Kelly at the IWMW 2003 event held at the University of Kent on 11-13 June 2003.
See http://www.ukoln.ac.uk/web-focus/events/workshops/webmaster-2003/sessions/#talk-5
The Power of Sharing Linked Data - ELAG 2014 WorkshopRichard Wallis
Presentation to set the scene and stimulate discussion in the Workshop "The Power of Sharing Linked Data" at ELAG 2014 - Bath University, UK June 10/11 2014
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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French:
18
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Spanish:
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Chinese:
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Dutch:
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with
hubs
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of
congress
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33. Structured
Data
Objectives
• Linking
with
hubs
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authority
on
the
web
• viaf.org
–
persons
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of
congress
–
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34. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
35. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
36. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
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• Standard
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access
patterns
37. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
38. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
in
search
engines
39. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
40. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
41. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
42. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
43. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
• Schema.org
44. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
• Schema.org
• Backed
and
recognized
by
Google,
Bing,
Yahoo!,
Yandex
45. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
• Schema.org
• Backed
and
recognized
by
Google,
Bing,
Yahoo!,
Yandex
• Widely
adopted
&
understood
–
20%
of
web
46. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
obvious
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
• Schema.org
• Backed
and
recognized
by
Google,
Bing,
Yahoo!,
Yandex
• Widely
adopted
&
understood
–
20%
of
web
fairly
y
47. Structured
Data
Objectives
• Linking
with
hubs
of
authority
on
the
web
• viaf.org
–
persons
• Library
of
congress
–
subjects
• Dewey.info
–
classifications
• Dbpedia
–
most
things
• Widely
distributed
&
understood
• Standard
data
access
patterns
• Common
vocabularies
• Visibility
obvious
Conclusions
in
search
engines
• Linked
Data
• RDF
–
RDFa,
RDF/XML,
JSON-‐LD,
Turtle,
nTriples
• Canonical
URIs
• Schema.org
• Backed
and
recognized
by
Google,
Bing,
Yahoo!,
Yandex
• Widely
adopted
&
understood
–
20%
of
web
fairly
y
51. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
52. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
53. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
54. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
55. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
56. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
57. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
58. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
59. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
60. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
61. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
• Share
the
way
the
web
does
62. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
• Share
the
way
the
web
does
• Linked
Data
63. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
• Share
the
way
the
web
does
• Linked
Data
• Schema.org
64. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
• Share
the
way
the
web
does
• Linked
Data
• Schema.org
Phase
3
65. Introducing
Linked
Data
Phase
1
• First
mine
the
data
• Records
held
in
Marc
• Identify
the
entities
• Person,
Organization,
CreativeWork,
etc.
• Match
strings
to
things
• People/Organization
names
–
viaf.org,
etc
• Subjects
–
Library
of
Congress
Phase
2
• Model
what
is
of
interest
to
the
Web
• All
our
data
is
important
to
us
• What
will
draw
people
to
our
resources?
• Share
the
way
the
web
does
• Linked
Data
• Schema.org
Phase
3 -‐
Try
it
out!
66.
67.
68. library
data:
stored
as
records
author location
edition
holding
title
source
classification
publisher
ISBN
date
of
publication
69. library
data:
stored
as
records
person place
author location
edition
holding
title
source
object concept
classification
publisher
ISBN
date
of
publication
organization work
78. Commercial data stored as entities
person place
FRBR: Work/Expression
object concept
organization work
FRBR: Manifestation
79. Entities
and
library
workflows:
• Knowledge
cards
• Fixes
Discovery
problem
of
“representative
record”
• It’s
what
users
expect
in
discovery
80. Entities
and
library
workflows:
• Improve
Cataloging
data
quality
– Cascading
updates
• A
new
approach
to
cataloging
– Point
and
click
cataloging
– Managing
entities
instead
of
managing
records
• Consistent
with
RDA
81. Günter Grass
Born:
16
October
1927
Gdańsk,
Poland
German
novelist,
poet,
playwright,
illustrator,
graphic
artist,
sculptor
and
recipient
of
the
1999
Nobel
Prize
in
Literature.
Works
Subjects
Germany
|
German
literature
|
Historical
fiction
War
stories
|
Black
humor
|
Fantasy
Quotes
“Even
bad
books
are
books
and
therefore
sacred.”—The
Find
Günter
Grass
works
at:
Libraries
near
me
|
Online
Retailers
Tin
Drum
82. Günter Grass
Born:
16
October
1927
Gdańsk,
Poland
German
novelist,
poet,
playwright,
illustrator,
graphic
artist,
sculptor
and
recipient
of
the
1999
Nobel
Prize
in
Literature.
Works
Subjects
Germany
|
German
literature
|
Historical
fiction
War
stories
|
Black
humor
|
Fantasy
Quotes
“Even
bad
books
are
books
and
therefore
sacred.”—The
Find
Günter
Grass
works
at:
Libraries
near
me
|
Online
Retailers
Tin
Drum
MARC
RECORD
83. Entities
and
library
workflows:
Cataloging
The Tin Drum
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
84. Entities
and
library
workflows:
Cataloging
The Tin Drum
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
Person Editor
85. Entities
and
library
workflows:
Cataloging
The Tin Drum
Person Editor
Person
Summary:
Authority
Acclaimed
as
the
greatest
• Günter Grass
• SameAs ➾
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
<dbpedia.org>
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
86. Entities
and
library
workflows:
Cataloging
The Tin Drum
Person Editor
Person
Summary:
Authority
Acclaimed
as
the
greatest
• Günter Grass
• SameAs ➾
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
<dbpedia.org>
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
LC
NAF
87. Entities
and
library
workflows:
Cataloging
The Tin Drum
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
88. Entities
and
library
workflows:
Cataloging
The Tin Drum
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
Work Editor
89. Entities
and
library
workflows:
Cataloging
The Tin Drum
Work Editor
Work
Authority
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
• Title
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
• Creator a
mental
institution.
➾ <Person>
Subjects
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Books
|
Audio
Books
Other
Languages
!
90. Entities
and
library
workflows:
The Tin Drum
Work Editor
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Expression
Books
|
Audio
Books
Cataloging
Subjects
Other
Languages
!
Manifestation
1
Manifestation
2 Manifestation
3
Cascading
Updates
Work
Authority
• Title
• Creator ➾ <Person>
91. Entities
and
library
workflows:
The Tin Drum
Work Editor
Summary:
Acclaimed
as
the
greatest
German
novel
since
the
end
of
World
War
II.
The
Tin
Drum
is
the
story
of
thirty
year
old
Oskar
Matzerath
who
has
lived
through
the
long
Nazi
nightmare
and
who
is
being
held
in
a
mental
institution.
Germany
-‐
History
|
German
literature
|
Political
fiction
Borrowing
Options
Ebooks
|
Printed
Expression
Books
|
Audio
Books
Cataloging
Subjects
Other
Languages
!
Manifestation
1
Manifestation
2 Manifestation
3
MARC21
Output
Cascading
Updates
Work
Authority
• Title
• Creator ➾ <Person>
93. Entities
and
library
workflows:
Other
applications
• Interlibrary
Loan
– Borrow
at
the
Work
level
– Manifestations/Items
are
detail
94. Entities
and
library
workflows:
Other
applications
• Interlibrary
Loan
– Borrow
at
the
Work
level
– Manifestations/Items
are
detail
• Analytics
– Fixes
“holdings
scatter”
across
manifestations
95. Entities
and
library
workflows:
Other
applications
• Interlibrary
Loan
– Borrow
at
the
Work
level
– Manifestations/Items
are
detail
• Analytics
– Fixes
“holdings
scatter”
across
manifestations
• Other
third
party
applications
– Discovery
API
exposes
library
entities
97. • Be
Entities
and
library
workflows:
Web
exposure
found
on
the
web
98. • Be
Entities
and
library
workflows:
Web
exposure
found
on
the
web
• Connect
your
users
to
unique
content
99. • Be
Entities
and
library
workflows:
Web
exposure
found
on
the
web
• Connect
your
users
to
unique
content
• What
the
web
requires
for
web
exposure
– Aggregation
– Familiar
structures
– A
Network
of
Links
– Entity
Identifiers
102. WorldCat
Entities
Works
• 197+
million
Work
descriptions
and
URIs
• Schema.org
• RDF
Data
formats
–
RDF/XML,
Turtle,
Triples,
JSON-‐LD
• Links
to
WorldCat
manifestations
• Links
to
Dewey,
LCSH,
LCNAF,
VIAF,
FAST
• Open
Data
license
• Released
April
2014
103.
104.
105.
106.
107.
108. Bibliographic
Entities
Work Place
Event Concept
Organization Person
Intuitive
searching
Cataloging
Integration
with
the
web
Cascading
updates More
options
111. Bibliographic
Entities -‐
In
the
Web
of
Data
person place
object concept
organization work
Entity
Based
Data
Architecture…
112. What
About
Linked
Data?
https://www.flickr.com/photos/rileyroxx/169900848/
113. WhWahatt
Aabbouot
uLitn
kLedin
ked
Data?
Data?
Yeah!
–
what
about
Linked
Data?
I
thought
Linked
Data
was
going
to
solve
all
our
problems!
https://www.flickr.com/photos/rileyroxx/169900848/
115. • A
Linked
Data
Technology
• Standard
on
the
Web
–
RDF,
URIs,
Vocabularies
• Identifying
and
Linking
resources
on
the
Web
• Important
powerful
enabling
technology
116. • A
Linked
Data
Technology
• Standard
on
the
Web
–
RDF,
URIs,
Vocabularies
• Identifying
and
Linking
resources
on
the
Web
• Important
powerful
enabling
technology
• But
only
a
technology…
117. • A
Linked
Data
Technology
• Standard
on
the
Web
–
RDF,
URIs,
Vocabularies
• Identifying
and
Linking
resources
on
the
Web
• Important
powerful
enabling
technology
• But
only
a
technology…
for
the
systems
folks
to
worry
about
118. • A
Linked
Data
Technology
• Standard
on
the
Web
–
RDF,
URIs,
Vocabularies
• Identifying
and
Linking
resources
on
the
Web
• Important
powerful
enabling
technology
• But
only
a
technology…
for
the
systems
folks
to
worry
about
• Real
benefits
flow
from:
Entity
Based
Data
Architecture
119. • A
Linked
Data
Technology
• Standard
on
the
Web
–
RDF,
URIs,
Vocabularies
• Identifying
and
Linking
resources
on
the
Web
• Important
powerful
enabling
technology
• But
only
a
technology…
for
the
systems
folks
to
worry
about
• Real
benefits
flow
from:
Entity
Based
Data
Architecture
Powered
by
Linked
Data
131. Why
is
the
Web
Adopting
This?
(Entities,
Semantic
Search,
Linked
Data)
132. Why
is
the
Web
Adopting
This?
(Entities,
Semantic
Search,
Linked
Data)
• To
get
their
products/resources
in
front
of
users
- Next
Generation
SEO
133. Why
is
the
Web
Adopting
This?
(Entities,
Semantic
Search,
Linked
Data)
• To
get
their
products/resources
in
front
of
users
- Next
Generation
SEO
• It
is
a
shared
approach
from
the
Search
Engines
- But
not
exclusive
to
them
136. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
137. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
• Publish
details
to
syndication
partners
- WorldCat:
Amazon,
Google
Scholar,
EasyBib,
EBSCO,
OpenLibrary,
FindMyLibrary,
RedLaser,
Yelp,
…
138. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
• Publish
details
to
syndication
partners
- WorldCat:
Amazon,
Google
Scholar,
EasyBib,
EBSCO,
OpenLibrary,
FindMyLibrary,
RedLaser,
Yelp,
…
• Links
from
aggregators
to
individual
libraries
- Find
in
a
library
139. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
• Publish
details
to
syndication
partners
- WorldCat:
June
Amazon,
Google
Scholar,
EasyBib,
EBSCO,
OpenLibrary,
FindMyLibrary,
RedLaser,
Yelp,
…
• Links
Million
from
Million
from
aggregators
to
individual
libraries
- Find
in
a
library
Syndication
WorldCat
Year
to
2013
!
• 77
referrals
partners
• 8.7
to
click-‐through
libraries
140. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
• Publish
details
to
syndication
partners
- WorldCat:
Amazon,
Google
Scholar,
EasyBib,
EBSCO,
OpenLibrary,
FindMyLibrary,
RedLaser,
Yelp,
…
• Links
from
aggregators
to
individual
libraries
- Find
in
a
library
Today
141. Syndication
For
Libraries
• Aggregate
to
a
central
site
- National
Library,
Consortia,
WorldCat.org
• Publish
details
to
syndication
partners
- WorldCat:
Amazon,
Google
Scholar,
EasyBib,
EBSCO,
OpenLibrary,
FindMyLibrary,
RedLaser,
Yelp,
…
• Links
from
aggregators
to
individual
libraries
- Find
in
a
library
Today
Efficient
but
indirect
145. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
146. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
147. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
148. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
- Google,
Bing,
Yahoo!,
Yandex,
etc.
- Where
our
users
are!
149. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
- Google,
Bing,
Yahoo!,
Yandex,
etc.
- Where
our
users
are!
• Users
referred
directly
to
resources
in
the
library
150. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
- Google,
Bing,
Yahoo!,
Yandex,
etc.
- Where
our
users
are!
• Users
referred
directly
to
resources
in
the
library
Direct
and
Effective
151. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
- Google,
Bing,
Yahoo!,
Yandex,
etc.
- Where
our
users
are!
• Users
referred
directly
to
resources
in
the
library
Direct
and
Effective
152. Syndication
For
Libraries
• Individual
On
the
Web
of
Data
libraries
publish
resource
data
- Linked
Data
in
local
discovery
interfaces
- Links
to
authoritative
hubs
–
set
global
context
• VIAF,
LoC,
WorldCat
Works,
…
• Recognized
and
identified
on
the
Web
- Google,
Bing,
Yahoo!,
Yandex,
etc.
- Where
our
users
are!
• Users
referred
directly
to
resources
in
the
library
Direct
and
Effective
153. Tell them about our resources…
http://www.flickr.com/photos/boston_public_library/6220572487
154. Tell them about our resources…
…using their language and methods
http://www.flickr.com/photos/boston_public_library/6220572487
161. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
162. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
163. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
164. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
165. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
• Describe
the
relationships
between
them
166. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
• Describe
the
relationships
between
them
• Place
them
in
a
global
context
–
link
to
authoritative
hubs
167. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
• Describe
the
relationships
between
them
• Place
them
in
a
global
context
–
link
to
authoritative
hubs
• Liberate
the
value
in
your
data!
168. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
• Describe
the
relationships
between
them
• Place
them
in
a
global
context
–
link
to
authoritative
hubs
• Liberate
the
value
in
your
data!
ENTITIES
169. Don't throw the baby out with the bath water
Sharing
for
discovery
on
the
web
As
part
of
a
Global
Knowledge
Graph
Entification
Identify
the
entities
in
your
data:
• Describe
them
using
appropriate
vocabularies
• Describe
the
relationships
between
them
• Place
them
in
a
global
context
–
link
to
authoritative
hubs
• Liberate
the
value
in
your
data!
And
also
share
them
on
the
web
–
a
job
for
Schema.org
ENTITIES
176. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
2010
Publish
Linked
Data
177. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
2012
–
using
Schema.org
2010
178. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
2010
2012
2013
179. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
2010
2012
2013
2014
180. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2013
2014
181. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2013
2014
182. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2013
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
183. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
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➢Event
➢Concept
2013
184. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
➢New
Services
2013
2016
185. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
➢Continuing
Evangelism
➢New
Services
➢Continuing
Innovation
2013
2016
186. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
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Evangelism
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Services
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Innovation
2013
2016
187. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
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API
➢Cataloging
2015
➢More
Entities
Released
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➢Organization
➢Event
➢Concept
➢New
Products
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Services
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2016
188. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
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mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
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Schema.org
✓Schema.org
added
to
VIAF
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2012
2014
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Integration
➢WorldCat
Discovery
➢Analytics
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API
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2015
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Entities
Released
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➢Organization
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Products
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Innovation
2013
2016
189. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
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mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
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API
➢Cataloging
2015
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Entities
Released
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➢Organization
➢Event
➢Concept
➢New
Products
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Evangelism
➢New
Services
➢Continuing
Innovation
2013
2016
190. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
➢Continuing
Evangelism
➢New
Services
➢Continuing
Innovation
2013
2016
191. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
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Evangelism
➢New
Services
➢Continuing
Innovation
2013
2016
192. OCLC
Entity
Based
Data
Strategy
✓VIAF,
ISNI,
FAST
Publish
Linked
Data
✓WorldCat.org
Linked
Data
Release
–
using
Schema.org
✓Data
mining
of
WorldCat
resources
✓WorldCat
Works
Released
–
using
Schema.org
✓Schema.org
added
to
VIAF
RDF
2010
2012
2014
➢Application
Integration
➢WorldCat
Discovery
➢Analytics
➢Discovery
API
➢Cataloging
2015
➢More
Entities
Released
➢Person
➢Organization
➢Event
➢Concept
➢New
Products
➢Continuing
Evangelism
➢New
Services
➢Continuing
Innovation
2013
2016