The much-heralded Semantic Web is enabled by an ability for machines to process webpages and certain data intelligently and perform better tasks on behalf of end users. Material is linked together through machine-readable statements of relationships among ideas, people, events, and places. Linked data examples are beginning to abound in the scholarly information environment, appearing from both publishers and libraries. This webinar will showcase several such examples. Presenters will describe their motivations for investment in such projects and discuss interfaces and other early outcomes.
A session delivered at SemTech NYC in Oct 2012. It contains an update to a session earlier in the year at SemTech SF in Jun 2012.
Abstract: As access to a richer set of knowledge and research continues to be critical to the healthcare community, the users of healthcare and life science solutions are demanding the same level of discoverability, integration, and innovation from their professional tools that they enjoy in their personal applications. Through the Smart Content initiative Elsevier seeks to semantically enrich its diverse offerings of health sciences content to both improve the performance of existing online resources as well as to enable the creation of the next generation of digital products. In this session, Alan Yagoda will discuss Elsevier’s efforts in developing Smart Content capabilities to power a new portfolio of strategic product offerings. The journey into smarter search and discovery resulted in a new infrastructure with a rich set of semantic capabilities include the development of a standardized medical taxonomy called EMMeT (Elsevier’s Merged Medical Taxonomy), indexing and content enrichment, and linked data services.
A session from SemTech SF in June 2012
Abstract: As access to a richer set of knowledge and research continues to be critical to the healthcare community, the users of healthcare and life science solutions are demanding the same level of discoverability, integration, and innovation from their professional tools that they enjoy in their personal applications. Through the Smart Content initiative Elsevier seeks to semantically enrich its diverse offerings of health sciences content to both improve the performance of existing online resources as well as to enable the creation of the next generation of digital products. In this session, Alan Yagoda will discuss Elsevier’s efforts in developing Smart Content capabilities to power a new portfolio of strategic product offerings. The journey into smarter search and discovery resulted in a new infrastructure with a rich set of semantic capabilities include the development of a standardized medical taxonomy called EMMeT (Elsevier’s Merged Medical Taxonomy), indexing and content enrichment, and linked data services.
The document discusses the Neuroscience Information Framework (NIF), which aims to provide a portal for finding and utilizing web-based neuroscience resources. NIF provides a consistent framework for describing various resources like databases, literature, and images. It allows simultaneous searches across these different data types and is supported by neuroscience ontologies. NIF currently catalogs over 5,000 resources and is working to integrate these diverse data sources to help answer questions and discover gaps in our knowledge about the brain.
The document outlines an eScience librarianship curriculum that aims to educate librarians for managing research data in the digital era. The curriculum covers key areas like scientific data literacy, data management competencies, and skills for collaborating in eScience initiatives. It consists of core courses in scientific data management and cyberinfrastructure technologies, as well as capstone courses focused on developing the ability to plan and lead eScience librarianship projects. The goal is to produce librarians with expertise in all aspects of the data lifecycle and the ability to support researchers throughout the eScience process.
CNI Fall 2011 Meeting Presentation Margaret Hedstrom & Robert McDonald (Dec. ...SEAD
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Silabus mata pelajaran Prakarya (Rekayasa) membahas tentang pembelajaran pembuatan produk rekayasa berdasarkan komponen elektronika aktif dan pasif, serta produk penghasil bunyi dan gerak menggunakan sumber arus listrik DC. Materi pelajaran mencakup wawasan, jenis, bahan, alat, teknik pembuatan, dan pengujian produk. Siswa diajak untuk mengamati, menanya, mengumpulkan data, mengasosiasi, dan men
The document discusses Elsevier's efforts to make its health and life sciences content "smarter" by applying semantic web technologies like linked data and taxonomies. This will allow the creation of smart content applications that improve discoverability, understanding, and synthesis of knowledge. Key points discussed include developing a merged medical taxonomy called EMMeT, automated indexing with weighted tags, and moving to a more RDF-friendly satellite data format using Turtle serialization.
A session delivered at SemTech NYC in Oct 2012. It contains an update to a session earlier in the year at SemTech SF in Jun 2012.
Abstract: As access to a richer set of knowledge and research continues to be critical to the healthcare community, the users of healthcare and life science solutions are demanding the same level of discoverability, integration, and innovation from their professional tools that they enjoy in their personal applications. Through the Smart Content initiative Elsevier seeks to semantically enrich its diverse offerings of health sciences content to both improve the performance of existing online resources as well as to enable the creation of the next generation of digital products. In this session, Alan Yagoda will discuss Elsevier’s efforts in developing Smart Content capabilities to power a new portfolio of strategic product offerings. The journey into smarter search and discovery resulted in a new infrastructure with a rich set of semantic capabilities include the development of a standardized medical taxonomy called EMMeT (Elsevier’s Merged Medical Taxonomy), indexing and content enrichment, and linked data services.
A session from SemTech SF in June 2012
Abstract: As access to a richer set of knowledge and research continues to be critical to the healthcare community, the users of healthcare and life science solutions are demanding the same level of discoverability, integration, and innovation from their professional tools that they enjoy in their personal applications. Through the Smart Content initiative Elsevier seeks to semantically enrich its diverse offerings of health sciences content to both improve the performance of existing online resources as well as to enable the creation of the next generation of digital products. In this session, Alan Yagoda will discuss Elsevier’s efforts in developing Smart Content capabilities to power a new portfolio of strategic product offerings. The journey into smarter search and discovery resulted in a new infrastructure with a rich set of semantic capabilities include the development of a standardized medical taxonomy called EMMeT (Elsevier’s Merged Medical Taxonomy), indexing and content enrichment, and linked data services.
The document discusses the Neuroscience Information Framework (NIF), which aims to provide a portal for finding and utilizing web-based neuroscience resources. NIF provides a consistent framework for describing various resources like databases, literature, and images. It allows simultaneous searches across these different data types and is supported by neuroscience ontologies. NIF currently catalogs over 5,000 resources and is working to integrate these diverse data sources to help answer questions and discover gaps in our knowledge about the brain.
The document outlines an eScience librarianship curriculum that aims to educate librarians for managing research data in the digital era. The curriculum covers key areas like scientific data literacy, data management competencies, and skills for collaborating in eScience initiatives. It consists of core courses in scientific data management and cyberinfrastructure technologies, as well as capstone courses focused on developing the ability to plan and lead eScience librarianship projects. The goal is to produce librarians with expertise in all aspects of the data lifecycle and the ability to support researchers throughout the eScience process.
CNI Fall 2011 Meeting Presentation Margaret Hedstrom & Robert McDonald (Dec. ...SEAD
SEAD is a new NSF-funded project that aims to provide sustainable data services for sustainability science research. It will integrate existing technologies and tools to address the needs of researchers working on "long tail" sustainability problems. SEAD is in its initial phase of developing prototypes and will not be ready to accept data until after October 2012. It is a collaboration between researchers at the University of Michigan, Indiana University, University of Illinois, and Rensselaer Polytechnic Institute.
Silabus mata pelajaran Prakarya (Rekayasa) membahas tentang pembelajaran pembuatan produk rekayasa berdasarkan komponen elektronika aktif dan pasif, serta produk penghasil bunyi dan gerak menggunakan sumber arus listrik DC. Materi pelajaran mencakup wawasan, jenis, bahan, alat, teknik pembuatan, dan pengujian produk. Siswa diajak untuk mengamati, menanya, mengumpulkan data, mengasosiasi, dan men
The document discusses Elsevier's efforts to make its health and life sciences content "smarter" by applying semantic web technologies like linked data and taxonomies. This will allow the creation of smart content applications that improve discoverability, understanding, and synthesis of knowledge. Key points discussed include developing a merged medical taxonomy called EMMeT, automated indexing with weighted tags, and moving to a more RDF-friendly satellite data format using Turtle serialization.
Sci Know Mine 2013: What can we learn from topic modeling on 350M academic do...William Gunn
This document discusses topic modeling on 350 million documents from Mendeley. It describes how topic modeling can be used to categorize documents into topics and subcategories, though categorization is imperfect and topics change over time. It also discusses how topic modeling and metrics can help with fact discovery and reproducibility of research to build more robust datasets.
ASIST 2013 Panel: Altmetrics at MendeleyWilliam Gunn
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Part of the SciDataCon14 workshop on "Data Papers and their applications" run by myself and Brian Hole to help attendees understand current data-publishing journals and trends and help them understand the editorial processes on NPG's Scientific Data and Ubiquity's Open Health Data.
This document summarizes a presentation by Timothy Hoctor, VP of Professional Services at Elsevier, about Elsevier's strategic vision and professional services. The key points are:
1) Elsevier aims to increase R&D productivity by linking data across the development spectrum and increase return on information through enhanced search and visualization tools.
2) Elsevier's Professional Services team leverages Elsevier's capabilities to provide customized data management and analysis solutions.
3) Elsevier's strategic objective is to become a leading collaborator in R&D data management through services like data mapping, gap analysis, data governance, and integrated data management.
SciBite is an award-winning leading provider of semantic solutions for the life sciences industry. Our fast, scalable easy-to-use semantic technologies understand the complexity and variability of content within life sciences. We can quickly identify and extract scientific terminology from unstructured text and transform it into valuable machine-readable data for your downstream applications. Our hand-curated ontologies ensure accuracy and reliability of high-quality results. Headquartered in the UK, we support our customers with additional sites in the US and Japan.
More infos at: www.scibite.com
Presentation on the Warsaw Conference on National Bibliographies August 2012nw13
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This document discusses factors that affect how readers, especially those learning English as a second language, comprehend hypertext documents. It explores how reader characteristics like language proficiency and topic familiarity interact with text characteristics like linear structure and available reading aids to influence comprehension. The research aims to identify which text factors can disrupt or support comprehension for ESL readers and whether hypertexts can promote deep understanding in those with lower language abilities or background knowledge. Specifically, it examines the roles of reader and text variables in determining different levels of comprehension from hypertexts.
This document discusses using HTML5 as an interchange format for scholarly content. It can support multiple facets of information like metadata, structure, semantics, and encapsulation. HTML5 combined with Relax NG can define constraining profiles using attributes, supporting different operational models. The document outlines 9 capabilities of HTML5 as an interchange format, including validation, transformation to other formats, and extracting RDF triple data. It concludes that HTML5 provides a powerful, adaptive, light-weight content format that supports flexible authoring and dynamic delivery while allowing for validation and transformation against formal models.
2013 DataCite Summer Meeting - Elsevier's program to support research data (H...datacite
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http://datacite.eventbrite.co.uk/
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This document discusses topic modeling on 350 million documents from Mendeley. It describes how topic modeling can be used to categorize documents into topics and subcategories, though categorization is imperfect and topics change over time. It also discusses how topic modeling and metrics can help with fact discovery and reproducibility of research to build more robust datasets.
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William Gunn discusses altmetrics from Mendeley's perspective. He outlines what Mendeley knows and still needs to understand about altmetrics, including how to predict impact, capture all mentions, and adjust for cultural differences. Gunn also discusses Mendeley's work with the Reproducibility Initiative to replicate highly cited papers, and their focus on improving recommendations, data quality, and building relationships with developers.
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1) Elsevier aims to increase R&D productivity by linking data across the development spectrum and increase return on information through enhanced search and visualization tools.
2) Elsevier's Professional Services team leverages Elsevier's capabilities to provide customized data management and analysis solutions.
3) Elsevier's strategic objective is to become a leading collaborator in R&D data management through services like data mapping, gap analysis, data governance, and integrated data management.
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This document discusses using HTML5 as an interchange format for scholarly content. It can support multiple facets of information like metadata, structure, semantics, and encapsulation. HTML5 combined with Relax NG can define constraining profiles using attributes, supporting different operational models. The document outlines 9 capabilities of HTML5 as an interchange format, including validation, transformation to other formats, and extracting RDF triple data. It concludes that HTML5 provides a powerful, adaptive, light-weight content format that supports flexible authoring and dynamic delivery while allowing for validation and transformation against formal models.
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The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
NISO Webinar: Return on Investment (ROI) in Linking the Semantic Web
1. Linked
Data
for
Smart
Content
Ellen
Hays,
Elsevier
Labs
e.hays@elsevier.com
Presented
at:
NISO
Webinar
on
Seman?c
Web
Linking
28
September
2011
1
2. Why
Smart
Content?
Elsevier’s
readers
want
more
than
text
and
images,
that
is,
more
than
simply
an
online
rendi?on
of
what
we
print.
They
want:
• Seman?cally
enhanced
content,
such
as
mashups
that
combine
informa?on
from
diverse
sources
and
in
diverse
media
• The
ability
to
do
seman?cally-‐mo?vated
search
• Source
data,
and
the
tools
to
mine
it
effec?vely
for
more
informa?on
• I.e.,
informa?on,
presented
in
ways
that
make
it
straighOorward
to
use
and
understand
2
3. The
challenge
How
to
do
seman?c
enhancement
at
scale
for
STM
publishing?
• In
harmony
with
our
culture
and
legacy
• Across
the
breadth
of
our
content
• Within
an
ecosystem
of
authors,
ins?tu?ons,
publishers,
content
suppliers,
and
funding
agencies
3
4. Smarter
Content
Applied Smart Content
Better discovery
Text
• Faceted search & browse
• Ontology-driven navigation
Elsevier
• Task-specific results
content • Personalized/localized
Tables results
• Question answering
Images
Better understanding
• Tag clouds
• Heatmaps
Related
Concepts: • Streamgraphs
Elsevier
content Metadata, • Scatterplots
and data Entities, • Time series
Relationships • Animations
Actionable, persuasive knowledge
• Topic pages
• Social network maps
Linked data • Geolocation maps
from partners • Data mashups
and the Web • Text mining reports
4
6. Guiding
principles
• Leverage
our
exis?ng
content
produc?on
workflow
and
infrastructure
• Acknowledge
a
deep
dependence
on
subject
maZer
exper?se,
third
par?es
and
the
Web
for
content
enhancement
and
knowledge
organiza?on
systems
• Deliver
benefits
across
the
complementary
use
cases
of
researcher
and
prac??oner
6
7. Current
approach
• Embrace
linked
data
principles
• Reuse
Web-‐standard
vocabularies,
taxonomies,
ontologies
and
en?ty
resources
where
possible
• Start
with
a
focus
on
standards
and
infrastructure
• Leverage
partners
and
acquisi?ons
for
content
enhancement
algorithms/capabili?es
• Build
out
linked
data
design
paZerns
for
applica?on
development
• Explore
new
product
opportuni?es
around
linked
data
7
8. Linked
data
principles
1. Use
URIs
to
name
things
2. Use
HTTP
URIs
so
they
can
be
looked
up
3. Return
useful
data
when
things
are
looked
up
4. Include
links
to
other
things
in
the
returned
data
“Linked
data
is
just
a
term
for
how
to
publish
data
on
the
web
while
working
with
the
web.
And
the
web
is
the
best
architecture
we
know
for
publishing
informa?on
in
a
hugely
diverse
and
distributed
environment,
in
a
gradual
and
sustainable
way.”
Tennison
J,
2010.
Why
Linked
Data
for
data.gov.uk?
hZp://
www.jenitennison.com/blog/node/140
ShoZon
D,
Portwin
K,
Klyne
G,
Miles
A,
2009.
Adventures
in
Seman?c
Publishing:
Exemplar
Seman?c
Enhancements
of
a
Research
Ar?cle.
PLoS
Comput
Biol
5(4):
e1000361.
doi:10.1371/journal.pcbi.1000361
9. Standards:
Content
satellites
Content
satellites
are
XML
documents
containing
RDF
statements;
for
example:
• Tags
from
a
taxonomy
for
a
given
document
• Document
sec?ons
relevant
to
a
given
concept
• Document
sec?ons
providing
answers
to
a
given
ques?on
• Learning
objects
compliant
with
a
given
state
educa?onal
standard
• Genes
men?oned
in
a
given
document
• Documents
suppor?ng
or
dispu?ng
conclusions
of
a
given
document
• Concepts
that
are
in
the
areas
of
exper?se
for
a
given
author
Goal
is
to
balance
expressivity
and
manageability
for
seman?c
enhancement
• Constrain
the
RDF
serializa?on
to
allow
exis?ng
XML-‐centric
staff,
tools,
and
workflows
to
accommodate
RDF
modeling
for
specific
applica?on
use
cases
9
10. Infrastructure:
Linked
Data
Repository
• Allows
Elsevier
plaOorms
and
applica?ons
to
retrieve
and
store
content
enhancements
• About
Elsevier
content
• About
third
party
content
• Allows
third
par?es
to
store
content
enhancements
• About
primary
and
secondary
content
• Provides
a
REST
API
for
• CRUD
opera?ons
on
satellites
as
RDF
named
graphs
• Simple,
low-‐expressivity
queries
across
stored
named
graphs
• For
<subject>,
give
me
all
objects
for
<property>
• Give
me
all
subjects
that
have
<object>
for
<property>
• These
can
be
for
sets
of
subjects
and
objects
• Supports
content
nego?a?on
• Op?mized
for
high-‐volume
read-‐write
of
RDF
named
graphs
10
11. Benefits
of
the
LDR
• Unprecedented
access
to
Elsevier
content
• Key
enabler
for
providing
advanced
seman?c
search
across
products
• Provides
links
to
other
data
sources
to
provide
further
contextual
enrichment
• Allow
others
to
discover
and
integrate
with
Elsevier
content
• Link
content
across
domains
• Data
can
be
pulled
out
of
large
amounts
of
text
and
organized
for
review
and
ac?on
• Informa?on
mining
for
compliance
and
research
• Create
mashups
from
mul?ple
data
sources
• Present
informa?on
with
enhanced
visualiza?on
11
12. Mining
text
for
semanHc
data
Building
the
databases
that
support
content
enrichment
includes
extrac?ng
from
unstructured
text:
―
men?ons
of
concepts
―
men?ons
of
rela,ons
between
concepts
―
other
seman,c
informa,on,
such
as
document
metadata
and
context
indicators
http://www.ifs.tuwien.ac.at/dm/
12
13. Mining
text
for
semanHc
data
• We’re
exploring
a
range
of
tools
and
techniques
to
do
text
mining,
including:
Rule-‐based
informa?on
extrac?on
Sta?s?cal
informa?on
extrac?on
Mapping
terms
in
text
to
thesauri
(Ei
Thesaurus,
EMTREE)
or
other
sources
of
lexical/seman?c
informa?on
• Working
with
GATE
and
UIMA
components
to
design
and
implement
language
processing
pipelines,
and
with
a
number
of
text
mining
vendors
• Because
Elsevier
publishes
in
a
broad
range
of
subject
areas,
content
types,
and
languages,
no
one
approach
is
appropriate
for
all
uses
13
14. SemanHc
and
lexical
models
Suppor?ng
our
text
mining
efforts
is
an
increased
focus
on
acquiring,
building,
and
maintaining
vocabularies
and
seman?c
models,
including:
Dic?onaries/thesauri
Taxonomies
Ontologies
We
reuse
Web-‐standard
seman?c
and
lexical
resources
wherever
possible,
but
also
create
applica?on-‐specific
domain
models,
some?mes
by
hand,
for
narrow
domains
These
seman?c
resources
are
also
stored
in
the
LDR,
which
links
seman?c
data
to
documents,
to
non-‐text
content,
and
to
other
resources,
to
create
a
web
of
meaningful
and
re-‐usable
informa?on
14
15. Smart
Content
design
paIerns
Linked
data
• Link-‐following
naviga?on
over
linked
graph
of
browser
RDF
resources
• Integrated
presenta?on
of
content
and
data
Mashup
across
mul?ple
sources
• Free
text/faceted
search
over
document/data
Seman?c
search
sets
• Rela?onal
query
over
aggregated/federated
sets
Seman?c
query
of
RDF
statements
15