A presentation to the San Andreas chapter of the Special Libraries Association in November 2009. Covers the spectrum of controlled vocabularies, what ontologies and other semantic technologies have to offer, and how it dovetails with the skills of information professionals.
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Future of controlled vocabularies: better content, new career opportunities
1. The Evolution of Controlled
Vocabularies
Better content, new career opportunities
A Presentation To The SLA San Andreas Chapter At San Jose State University, November 18, 2009 By Christine Connors
Among Other Things A Librarian, Information Scientist, Semantic Web Advocate And Founder Of TriviumRLG
2. If you wish to Tweet whilst here...
✤ I am @cjmconnors
✤ Hashtag is #slasa
3. Quick Survey
✤ More interested in controlled vocabularies or career opportunities?
✤ Perform ‘traditional’ library duties? (Research, Reference, Circ, ILL…)
✤ How many of you are building ontologies? Rule bases?
✤ Looking for a job?
✤ Have a position to fill or expect to this year?
✤ Business oriented?
✤ Technology focused?
✤ Content & Information Architecture specialist?
8. The Continuum
We are building more complex and powerful data architectures; all types are
available for use on the semantic web
9. Ontology
Thesaurus
Taxonomy
Power
Synonym Ring
List
Folksonomy
Complexity
The Continuum
We are building more complex and powerful data architectures; all types are
available for use on the semantic web
10.
11.
12. Andorra
Austria
Belgium
Denmark
Finland
France
Germany
Name:
Hungary
Address:
Ireland
City:
Italy Precision
State/Province:
Liechtenstein
Country:
Monaco
Zip/Postal Code:
Netherlands
Norway
Portugal
Spain
Sweden
Switzerland
United Kingdom
13. United Kingdom
Synonym: UK
Synonym: United Kingdom of Great Britain and Northern Ireland
14. United Kingdom
Synonym: UK
Synonym: United Kingdom of Great Britain and Northern Ireland
Behind the scenes in search Recall
15. Europe
NT
...
United Kingdom
NT
England
Scotland
Wales
Northern Ireland
See http://www.nlsearch.com/rssearch.php
16. Europe
NT Better
... Recall
United Kingdom
Advanced Search NT
England
Scotland Better
Wales Precision
Northern Ireland
See http://www.nlsearch.com/rssearch.php
17. Europe
NT
...
United Kingdom
NT
England
Scotland
Wales
Northern Ireland
18. Europe England
NT BT
... Britain
United Kingdom Great Britain
NT United Kingdom
England BT
Scotland European Union
Wales Group of Eight
Northern Ireland United Nations Security Council
NATO
Faceted or Parametric Search; Guided Navigation
See www.endeca.com or www.newssift.com
19. Europe
NT
United Kingdom
Scope Note Situated in north-west Europe,
the island nation was formed January 1, 1801.
Use For UK
Use For United Kingdom of
Great Britain and Northern Ireland
See Also Great Britain
See Also Britain
See Also British Isles
NT
England
Scotland
Wales
Northern Ireland
20. Europe
NT
United Kingdom
Scope Note Situated in north-west Europe,
the island nation was formed January 1, 1801.
Categorization
Use For UK
Classification
Use For United Kingdom of
Search
Great Britain and Northern Ireland
Advanced Search
See Also Great Britain
Rules-based Coding
See Also Britain
See Also British Isles
*Precision ? Recall ?
NT
England
Scotland
Wales
Northern Ireland
21. NT
England
Britain BT
NT
NT BT
BT Wales
Great
Britain NT
NT
BT
Scotland
BT
United NT
Northern
Kingdom BT Ireland
22. NT
England
Britain BT
God and my right
NT
NT BT
BT Wales
motto
Great
Britain NT
NT
BT
Scotland
BT
flag
United NT
Northern
God Save the Queen Kingdom BT Ireland
anthem
official
English language
capital
currency
legislature London
pound sterling
Parliament
37. Circle size indicates the # of triples in the dataset
Circle Size Triple Count
Very large > 1B
Large 1B-10M
Medium 10M-500k
Small 500k-10k
Very small <10k
Arrow direction indicates that a given dataset
contains concepts from the indicated dataset
Arrow thickness indicates the # of shared triples
Arrow Thickness Triple Count
Thick >100k
Medium 100k-1k
Thin <1k As of March 2008
45. Benefits
✤ Interoperable
✤ Increase delivery channels for data and services
✤ Consistent
✤ Dynamic
✤ Greater Return on Investment/Effort
✤ Re-purpose data rather than re-create it
✤ Improved discovery
✤ Improved analytics
✤ Shared meaning
✤ Compliance
47. Benefits of Communicating Clearly
✤ Authority
✤ Trust
✤ Provenance
✤ Joint research / build on existing research
✤ Larger audience
✤ User engagement
49. The Dream Team 2009
✤ Information Scientist
✤ Information Architect/User Experience Designer
✤ Cognitive Scientists
✤ Developers
✤ Business Analyst
✤ Leader/Evangelist/Community Manager
✤ Project Manager
✤ Security Expert
✤ Legal Advisor
50. Where’s the box?
✤ To organise knowledge is to gather together what we know into a
comprehensive organised structure, to show its parts and their
relationships. This is the work of scholars and encyclopaedists.
✤ Our tasks are to make knowledge (whether organised or
unorganised) available to those who seek it, to store it in an accessible
way, and to provide tools and procedures that make it easier for
people to find what they seek in those stores.
✤ Brian Vickery, http://www.lucis.me.uk/knowlorg.htm
51. Embedded Librarians
✤ Collaborated on or contribute to your customer group’s electronic
communications and/or collaborative workspaces, including
email, wikis, blogs and other web-based workspaces.
✤ Shoemaker and Talley, http://www.sla.org/pdfs/
EmbeddedLibrarianshipFinalRptRev.pdf, funded by an SLA
Research Grant, 2007, published June, 2009.
53. Competencies for Info Pros
✤ From the SLA special report
✤ B.1
✤ Manages the full life cycle of information from its creation or acquisition through its
destruction. This includes organizing, categorizing, cataloguing, classifying, disseminating;
creating and managing taxonomies, intranet and extranet content, thesauri etc.
✤ B.2
✤ Builds a dynamic collection of information resources based on a deep understanding of
clients' information needs and their learning, work and/or business processes.
✤ C.3
✤ Researches, analyzes and synthesizes information into accurate answers or actionable
information for clients, and ensures that clients have the tools or capabilities to
immediately apply these.
54. Competencies for Info Pros
✤ D.1
✤ Assesses, selects and applies current and emerging information tools and creates information access
and delivery solutions
✤ D.2
✤ Applies expertise in databases, indexing, metadata, and information analysis and synthesis to
improve information retrieval and use in the organization
✤ D.3
✤ Protects the information privacy of clients and maintains awareness of, and responses to, new
challenges to privacy
✤ D.4
✤ Maintains current awareness of emerging technologies that may not be currently relevant but may
become relevant tools of future information resources, services or applications.
55. Information Architects & User
Experience designers
✤ We need help
✤ Powerful, but UI/UX is not friendly
✤ Organizing elements, pathfinding, labeling, building relationships,
consistent experiences
✤ How to design for n-dimensional space in a 2D or 3D environment?
56. 2001, SuccessFactors has multiple worldwide offices collaborating for strong local support of
customers.
SENIOR FRONT-END ENGINEER, USER INTERFACE
The world of web development is quickly evolving from a thin client model to one with rich
and robust browser-based user interface functionality, using the latest developments in
front-end technology. At SuccessFactors, we strive to constantly improve the way we build
user interfaces and not only employ the latest UI development methodologies, but also
*push the envelope* to discover and establish our own, unique approaches to UI
development.
From that perspective, we are actively seeking candidates who want to flex UI development
muscles and be part of a dynamic, growing team of engineers dedicated to defining and
creating the next generation in front-end, UI technology here at SuccessFactors, Inc..
Duties and Responsibilities:
As a UI Engineer, your responsibilities will include working with a team to develop rich user
interfaces for enterprise-level Software as a Service (SaaS) applications; constantly driving
for consistent user interaction by not only building cutting-edge UI functionality, but also
consolidating common JavaScript and DHTML code to improve our current user interface. In
addition, you will be able to clearly communicate your ideas and both openly and honestly
provide and receive regular input from your peers. While teamwork is of the utmost in
importance, you can also work independently with minimal supervision, and take the
initiative to constantly keep yourself engaged.
Also, you never settle for second best. You possess a strong focus on quality and attention
to detail, and possess the ability to quickly understand and solve unique and even
undocumented programming problems. Naturally curious, you have a penchant for and drive
to quickly learn and master skills in new technologies.
Finally, you have a strong sense of fun and a passion for being part of a movement. As part
57. of the SuccessFactors family, you have a unique opportunity to join an exciting, dynamic and
closely-interactive group of people whose focus is to change the way the world works!
Proven experience in the following areas (not necessarily in order of importance)
* 6+ years hands-on experience in full development life cycle software development,
predominately in User Interface development.
* Hand-coded, W3C-compliant and semantic (X)HTML and CSS with an emphasis on
CSS-driven page layouts.
* High level of proficiency with JavaScript (including object-oriented JS), DHTML,
XMLHttpRequest, XML, JSON.
* Familiarity with best-practices for usability and accessibility standards.
* Writing high-quality, testable, maintainable, and well-documented code.
* Proficiency in a server-side scripting language such as JSP, PHP, or ASP.
* Solid understanding of working within a Model-View-Controller program architecture paradigm.
* Bachelor*s degree in Computer Science, Engineering (any type) or a related field
Desired skills
* Experience with the integration and use of a third-party JavaScript library such as: Yahoo UI
Library, Prototype, jQuery, DOJO, etc.
* Experience in creating standalone, JavaScript-based UI widgets.
* Java/J2EE server-side development
* Experience with Flash, Flex, and SQL are a huge plus, but not required.
Please visit us at www.SuccessFactors.com to learn more about us,
to view all current job postings, and to apply.
58. Job Information
d(s) here-----
Title: Data Architect IV
Location: San Francisco, CA
Job Type: Contract
Compensation: per Hour
Reference Code: 922481-NRC
Description: Our client is seeking a Data Architect to analyze data requirements and
create logical and physical models and specifications of data. The Senior Content
Engineer will work directly with the editors, project managers, system architects and
software developers to develop editorial tools and delivery products that utilize data
markup. Functions:
Analyze complex data and product requirements
Lead the development of data models and specifications in a variety of markup
language syntaxes (W3C schema, RELAX NG Schema, XML DTDs, and RDF)
Perform the change control and update process for maintaining modular data markup
specifications
Lead the development and maintenance of data transformation scripts
Lead the development and maintenance of data conformance validation
Develop ontology/vocabulary to be shared across disparate content types
Work with editors, project managers, system architects, and software developers to
define and develop editorial tools and products that utilize data markup
Deliver presentations and/or train users on use of data markup, as required
Organize and lead data modeling workshops to develop markup specifications
Write documentation for markup specifications and design principles
Research industry standards to contribute to recommendations for architectural
direction
Candidates are preferred to work in either Dayton, OH, Bethesda, MD, Colorado Springs,
CO, Albany, NY, New Providence, NJ, Charlottesville, or San Francisco, CA; however,
strong candidates from anywhere should apply without consideration to relocation.
Occasional travel is required.
59. Information Scientist
✤ Organizing information
✤ Cataloging and classification
✤ Knowledge sharing
✤ Primary & secondary research
✤ Searching & finding
✤ Presentation of results in user’s preferred format
✤ Metrics
60. ONTOLOGIST / SR. VOCABULARY SPECIALIST
Ontologist / Sr. Vocabulary Specialist
Rosslyn, VA
gineer 10%
Job Description:
The Ontologist / Sr. Vocabulary Specialist will work in a team-oriented environment,
directly interface with a Department of Defense (DoD) customer and be a member of an
Enterprise Vocabulary Team. The Vocabulary specialist will be the primary interface to
assigned communities or offices through development of vocabulary artifacts and provide
specific support and guidance consistent with approved methodologies.
Relationship with DoD community points of contact in support of their data strategy
implementation.
Development of a Standard Information Structure that includes a glossary,
ong- semantic model, and an object model.
any Provide glossary development support.
Provide thesaurus development support.
on by Provide ontology development support.
Elicit knowledge from Subject Matter Experts.
Support handoff of vocabulary products to XML developers.
Support optimization of search engine tuning parameters based on content of
vocabulary content.
Conduct vocabulary analysis and harmonization activities.
Develop documentation and presentations for delivery to clients.
Help resolve problems and ensure customer satisfaction.
Foster positive client relationships
DoD customers on adopted approach to development of vocabularies that are
based on business process definition and identifying authoritative data sources.
61. Jack-Of-All-Trades
✤ Employees who are early adopters frequently have to be able to do a
little of this, a little of that
✤ Academia
62. ver Spring, MD
1
Title: Knowledge Manager
LLTIME Skills: self-starter, business systems analysis, databases, Microsoft Office SharePoint
lary Server 2007, web part development, site definitions and workflow, information
taxonomy and other features, Office 2007
l Time
pos705775
Date: 6-2-2009
X143098
ne
Description:
Job Summary
The Knowledge Manager gathers, reviews, analyzes, and evaluates business systems and
user needs and writes detailed description of user needs, program functions, and general
requirements. This person should have good understanding of relational database concepts
and client-server concepts. May lead and direct the work of others, including managing
vendors and vendor contracts. Working with limited managerial oversight, the Knowledge
Manager is responsible for fielding requests from users, analyzing those requests, producing
business and functional requirements, creation of metrics and test plans to prove that
functional requirements have been met, documenting, and training both the end-user and
the User Support Department on the end product. This individual will determine and
demonstrate whether SharePoint can be effectively used "out-of-the-box" to meet
requirements or whether custom coding will be required. Mentoring IPM and IT on
SharePoint policies and best practices as part of project planning and scoping as needed,
including site structure, security and other areas. The Knowledge Manager will apply
advanced problem-solving skills including hypothesis generation, testing, successful
resolution and communication. Assist project manager with issue and risk identification. The
Knowledge Manager will also serve on the IPM SharePoint Governance Board.
Job Responsibilities
63. Position ID: 679636 Date: 5-21-2009
Dice ID: RTL84898
avel Required: none
Description:
Telecommute: no We're looking for a Senior Manager/Front-End Engineer to serve as Team Lead for our
client-side development efforts.
Are you the person we're looking for? Maybe, if:
You understand how to gracefully degrade styles and JavaScript behaviors, how to
structure information and keep it and presentation style separate.
You read sites like A List Apart and Ajaxian.
You know what our yslow score is and have many suggestions for how to make it better.
You have an opinion on the Semantic Web, Microformats, HTML5, jquery vs mootools vs
ext, and what doctypes we should be using.
You know your way around conditional CSS selectors and the DOM. You used Blueprint
when it came out, but now find Fluid 960 a bit more to your taste.
You know what "template inheritance" means and how extension differs from composition.
Having done this before, you'll find it even more fun to lead a team of other front-end
folks, and keep a whole bunch of back-end engineers intrigued with new things to figure
out.
You are going to look on our sites and despair. And then make them more efficient,
functional, and beautiful, and show us how you did it. And you think that sounds like fun.
::About Us::
We're looking for someone with at least 5 years of front-end engineering experience, with
a super-strong preference for team lead experience. We want someone who enjoys
teaching others how to manage the front-end work, and has built a set of tools for doing
so in the past.
Our technology stack includes Linux, Postgres, Ruby+Rails, Python+Django,
Javascript+Ext, with several ongoing experiments using Pylons, Jinja, jQuery, Dojo and
other tools and frameworks. We use Subversion to manage our code, and Mercurial to
manage our content.
Our applications are designed for, built and run in high-availability environments. So this
is not front-end for the sake of front-end, but front-end for the sake of results. Directly. You
64. Semantic Technology: Knowledge Engineering Associates
===========================================
Applications are invited for Research Associate, Graduate Student and PDF positions in the Knowledge
Navigation Infrastructure Team (KNIT) lead by the Innovatia Research Chair at the University of New
Brunswick, Saint John http://www.unb.ca/news/view.cgi?id=1680
Researchers will collaboratively develop reusable infrastructures to support custom vertical search across
multiple application domains in biomedical, health care, energy and telecom. Researchers will develop
solutions for enterprise search using semantic web technologies, service oriented architecture, ontologies
and text mining. Successful candidates will have demonstrated software development expertise and
familiarity with knowledge engineering lifecycles. Candidates with demonstrated experience with two or
more of the following technologies are encouraged to apply:
1) Web based Content Acquisition Strategies
2) Knowledge Representation with OWL / RDF
3) Text Mining / Natural Language Processing
4) Ontology based reasoning over instance / triple stores
5) Terminology Management and Curation
6) Literature and (Meta) Data Integration
7) Provenance Tracking / Tracability
8) Algorithm Design / Graph Matching
9) Human Computer Interaction
10) Semantically Enabled Software Architecture
11) Semantic Desktops and Publishing
Enquiries and applications and can be made by sending a full CV and cover letter to: bakerc@unbsj.ca
70. ✤ Since we need to represent a physical object in the subject, we
will use the book’s ISBN
✤ Prefix / QName
✤ Shorthand method of referencing a namespace
✤ dc:title = http://purl.org/dc/elements/1.1/title
uri:isbn:1843342286 dc:title
‘Organising Knowledge’
Predicate
Object
Subject
55
72. Ontology
People Places Events Time
Authority Geographic Events ISO
File Thesaurus Taxonomy 8601
57
73. HTML XML XHTML
XTM SKOS
RDFa Microformats
OWL RDF/RDFS
FOAF eRDF
Dublin Core
58
Notes de l'éditeur
We have schema into which we plug the the terms from our various controlled vocabularies.
We have accession numbers, shelf numbers, international standard numbers and still...
&#x2026; we&#x2019;re limited in what we can find, and how we find it. Be it in print, or online finding aids.
This is the card catalog room at the Sterling Memorial Library, Yale.
Metadata goes back quite far, actually. In the British Museum are girginakku, Mesopotamian library boxes that have clay tablet labels on them - metadata. Go see David&#x2019;s picture at http://www.flickr.com/photos/70494923@N00/2650269503/in/photostream/
SO what are taxonomies, ontologies etc? Let&#x2019;s talk about it.
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Folksonomies provide personalized labels - they have meaning for the person that creates them, that is if they are memorable&#x2026;
Lists provide ambiguity control.
Synonym rings provide equivalency control.
Taxonomies provide ambiguity control, synonym control and hierarchical relationships (BT, NT).
Thesauri provide ambiguity control, synonym control, hierarchical relationships (BT, NT), associative relationships (RT, See Also, USE/UF) and Scope Notes.
Ontologies do all of the above but allow for custom relationship types (properties/predicates), inferencing, reasoning and &#x201C;NOT.&#x201D;
Here&#x2019;s an example of folksonomy. How many of you make a list when you go grocery shopping? This is like going to the store with no list. There are some staples that everyone needs, but everything is kind of random.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
This is a list; typically used in forms. It reduces typos and the use of alternate terms and once an appropriately designed list is learned it improves efficiency.
Here we have a taxonomy - hierarchical relationships. We see these used in file systems and in search tools, where if subsumption is turned on we get higher recall at the higher classes and better precision in the lower classes.
Here we have a taxonomy - hierarchical relationships. We see these used in file systems and in search tools, where if subsumption is turned on we get higher recall at the higher classes and better precision in the lower classes.
Here we have a taxonomy - hierarchical relationships. We see these used in file systems and in search tools, where if subsumption is turned on we get higher recall at the higher classes and better precision in the lower classes.
Here we have a taxonomy - hierarchical relationships. We see these used in file systems and in search tools, where if subsumption is turned on we get higher recall at the higher classes and better precision in the lower classes.
Here we have a taxonomy - hierarchical relationships. We see these used in file systems and in search tools, where if subsumption is turned on we get higher recall at the higher classes and better precision in the lower classes.
In a polyhierarchical system we can find a term from many different starting points. Faceted search systems frequently make use of the rules of thumb regarding using isA, kindOf, and partOf relationships. But notice that we&#x2019;re still not allowed to encode the relationships directly as &#x201C;isA&#x201D;, &#x201C;kindOf&#x201D; or &#x201C;partOf&#x201D; and instead still have to use NT/BT.
In a polyhierarchical system we can find a term from many different starting points. Faceted search systems frequently make use of the rules of thumb regarding using isA, kindOf, and partOf relationships. But notice that we&#x2019;re still not allowed to encode the relationships directly as &#x201C;isA&#x201D;, &#x201C;kindOf&#x201D; or &#x201C;partOf&#x201D; and instead still have to use NT/BT.
In a polyhierarchical system we can find a term from many different starting points. Faceted search systems frequently make use of the rules of thumb regarding using isA, kindOf, and partOf relationships. But notice that we&#x2019;re still not allowed to encode the relationships directly as &#x201C;isA&#x201D;, &#x201C;kindOf&#x201D; or &#x201C;partOf&#x201D; and instead still have to use NT/BT.
Our thesaurus. Filling requirements for many systems -see right list. Enterprise Search, content portals, business analytics packages.
I can do my BT/NT stuff, but I can also create classes and properties that i need for my own application
I can do lots more in an ontology - using transitive, symmetric and functional properties, declaring data types and cardinality and I can also say NO - this object is NOT part of a certain class or have a certain property. In this diagram, I could easily add a branch for the British Isles, define it as having England, Wales, Scotland, Northern Ireland, Ireland, the Isle of Man, the Channel Islands etc, but be able to state specifically that Ireland is not part of the United Kingdom, so as not to create confusion for a machine processing the concept base. The power of no.
I an also now take this graph (presuming I&#x2019;d encoded it properly) and link it to other graphs that define the UK if I choose. I do this to take advantage of the work others have done -- to share, discover and have a more complete data set which, if I&#x2019;ve chosen carefully, should provide better data and analysis.
one URI can be embedded everywhere vs. a web page which is maintained by one creator (entity)
why do this
findability
reuse
share
but most importantly to NEXT (analyze)
why do this
findability
reuse
share
but most importantly to NEXT (analyze)
ANALYZE
what do i want them to do:
manage your own data
branding and for data reuse
We have to think more now about what we do, and how that impacts our digital environment. The ripples that our actions create. Make statements. Give them URIs. Revise those statements. Maintain history. Maintain your integrity.
spammers and false data will out because other people can link to it
need to work on trust and security
someone asked yesterday &#x201C;How does it decide what is the most accurate info?&#x201D;
1st - &#x201C;it&#x201D; shouldn&#x2019;t decide - you should
2nd - trust layer needs work - ontologies, algorithms etc
first steps - True Knowledge
can be one way
myths -
security - open
Key advances needed in the semantic web are user interface/interaction design patterns and security. The semweb community knows this! They need your help - send in your use cases!!!
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
So where does one get some of this data? As there are many data sets available, and I&#x2019;d like to show you the growth as visualized in these graphs from Richard Cyganiak and Chris Bizer.
Not all of these are completely FREE. I promise you that IEEE and ACM are NOT giving away their research papers.
SO what are some examples of applications using this data?
Data from MusicBrainz and Wikipedia are combined - with a bit of editorial oversight - with playlists and story data from BBC properties
OK, but why do we do all of this?
explore, discover, magic, enjoy, learn
false starts, circular paths - much like enterprise data and paths through the web of unstructured data
What&#x2019;s in these silos? How do we get in safely and get back out cleanly?
Silos are ok - as long as they are clearly marked, and can be connected to the preceding and following steps in the workflow.
Open world vs closed world
Organizations need to put their data IN the web instead of simply ON the web.
Just as we use ISBNs, ISSNs, AACR2 and other standards, we need to embrace the methods being considered by diverse working groups to allow the data to be consistent. A common framework will allow us to use the data dynamically - from mashups to annotations. Consistent frameworks allow us to reduce costs in a few ways - shorter time period for learning new models, lower software costs for non-custom, COTS products. Our patrons win as well - they don&#x2019;t have to learn new techniques for each data set. We gain shared meaning for concepts, reducing confusion.
Embed ability to manipulate data rather than expend effort scraping it back out
Re-purpose data rather than re-create it
Improve product development with a global business vocabulary that feeds right into downstream applications such as portals, reporting programs and CRMs
Increase online revenue and improve your customers&#x2019; online experience by cross-referencing industry classification codes and brand names
Compliance
Increase delivery channels for data and services
Communication, after all, is frequently a root cause of many good, and bad, events.
&#x201C;The Shannon&#x2013;Weaver model of communication embodies the concepts of information source, message, transmitter, signal, channel, noise, receiver, information destination, probability of error, coding, decoding, information rate, channel capacity, etc.&#x201D;
On the web, separate protocols and languages handle similar concepts such as transport, encoding, noise reduction, feedback; all in the name of clarifying communication in a virtual space in a manner quite similar to the model defined here by a mathematician and information theorist.
http://en.wikipedia.org/wiki/Shannon-Weaver_model
Exposure, recognition for work
Identify works possibly targets or victims of theft/misappropriation of assets
Sharing ~ embedding, commenting, tagging
&#x201C;Curate the content, not the container&#x201D;
Audience involvement. The stories, the facts, the beauty or repulsiveness of the artefact draws people in, and they are more likely to appreciate the efforts that went in to the collection and display of them. Engaged patrons are more likely to become loyal patrons, and more likely to become financially supporting patrons.
What are some of the roles needed in this space?
There is much of interest in the paper by Mr. Vickery at this URL. I once agreed with the statement &#x201C;This is the work of schoars and encyclopaedists.&#x201D; I do not any longer. It hampered my personal career aspirations. I do agree that our jobs are to make knowledge available using tools that make it easier for people to find and use what they seek. Sometimes it&#x2019;s good to stay inside the box. Sometimes you need to go outside the box.
If you are embedded with a group, or wish to be, building a knowledge base that can be consumed by existing or new systems, added to by team members - or not! - and as easy to query as a datastore will make you imminently more valuable.
if you love your current job AACR2 is going away, RDA and more -- learn this
RDFa
if you love your current job you can still make great use of these capabilities.
AACR2 is going away, RDA and more are coming
RDFa
B.1 insert &#x201C;ontologies&#x201D; before the &#x201C;etc&#x201D; and er, add &#x201C;CRUD&#x201D;
B.2 ontologies allow one to add data as it is found without breaking the existing model, connect to other dynamic datasets and give serendipity a chance
C.3 ontologies are not prose - synthesizing the necessary concepts and relationships is as important in this realm as in an executive summary of research findings;
inherent in ontological data models are the ability to inference and reason across the data -- to ask questions, to analyze and synthesize in ad hoc or scheduled transactions
ontologies serialized in an open standard format also allow your users to integrate the data into their applications -- dashboards, RSS feeds, databases, CMS, DAM etc -- for real-time or near updates
D.1 How many of you have integrated taxonomies and thesauri into systems other than your OPAC? Are you using RSS? Digital Object Identifiers? Dublin Core? These technologies will become just as important.
D.2 Everyone I&#x2019;ve asked thinks that the librarian&#x2019;s skill at developing knowledge organization system is a critical part of this next evolution of the web.
D.3 Privacy, security, provenance, authority, trust are all becoming critical aspects of the system. Work has been done, but much is still needed. Sharing what we&#x2019;ve learned - both our skills and experiences with - determining authoritative sources of information, protecting patron records and interactions is needed. There is still time to get involved, have an impact.
D.4 There are emerging technologies. They aren&#x2019;t young by internet standards, but they are yet to reach their prime. Librarians have always been on the forefront of technologies that will improve their services -- this is an incredible leap forward. Have you ever been frustrated by an anthology of works? Be it poetry, stories or professional papers, you may have just what your patron needs, but not know it&#x2019;s there unless you have had time to look at every book in your collection. And who has time to do that anymore? Catalog records do not contain all of those article titles, but an ontology can.
Now we&#x2019;re going to look at some of the roles I believe are relevant to the industry and the professionals gathered here tonight.
SLA.org, Competencies for Information Professionals
Information professionals have expertise in total management of information
resources, including identifying, selecting, evaluating, securing and providing
access to pertinent information resources.
. These resources may be in any
media or format. Information professionals recognize the importance of people
as a key information resource.
B.1 Manages the full life cycle of information from its creation or acquisition
through its destruction. This includes organizing, categorizing, cataloguing,
classifying, disseminating; creating and managing taxonomies, intranet and
extranet content, thesauri etc.
B.2 Builds a dynamic collection of information resources based on a deep
understanding of clients&#x2019; information needs and their learning, work and/or
business processes.
B.3 Demonstrates expert knowledge of the content and format of information
resources, including the ability to critically evaluate, select and filter them.
B.4 Provides access to the best available externally published and internally
created information resources and deploys content throughout the organization
using a suite of information access tools.
B.5 Negotiates the purchase and licensing of needed information products and
services.
B.6 Develops information policies for the organization regarding externally
published and internally created information resources and advises on the
implementation of these policies.
There is a computationally complex view of the web that involves Boolean logic, Bayesian algorithms, syntax, pattern recognition, neural networks and more. There is another view that is concerned about meaning, categorization, classification and relationships. This view tends to require more human power. Neither is particularly practical &#x2013; one requires heavy-duty processing and lots of monitoring. The other requires a great deal of handcrafting and maintaining. Using the best of each world will get you further in the long run. There are brilliant minds working in the artificial intelligence space, and we make great use of those tools in our own processing platform, but that&#x2019;s not what we&#x2019;re going to focus on today.
Today, we&#x2019;ll be talking about a web of data &#x2013; linked data; the vision promoted by the world wide web consortium. The semantic web is NOT a new web, in fact the specifications are on average a decade old. It is an open framework designed to allow data to be shared by as many people, organizations and applications as is desired.
Right now the majority of the data on the web is locked up in applications and markup languages that jumble the format, the style, delivery mechanism and the content all together. The semantic web is a group of standards that provide the common format for describing data so that data from different sources can easily be combined and integrated rather than siloed.
http://en.wikipedia.org/wiki/File:Artificial_neural_network.svg
http://en.wikipedia.org/wiki/File:Xbarst1.jpg
http://en.wikipedia.org/wiki/Naive_Bayes_classifier
An RDF Graph; a statement
Resource = thing
Literal = string of characters (?lang, ?datatype)
Statement = Triple = (s, p, o) =
Property = (&#x2026;, p, &#x2026;)
Graph = a set of Statements =
RDF Description (of some thing) = a set of Statements (about that thing)
Resource = thing
Literal = string of characters (?lang, ?datatype)
Statement = Triple = (s, p, o) =
Property = (&#x2026;, p, &#x2026;)
Graph = a set of Statements =
RDF Description (of some thing) = a set of Statements (about that thing)
Simply keep adding annotations
Let&#x2019;s say we have a community ontology &#x2013; Friends of the Library, church group, professional group, what have you.
They key concepts in the domain of knowledge that describes this particular community are people, places events, and time.
To continue the notion of a triple to a more familiar realm, you have an element-attribute-value set. &#x201C;Events&#x201D; is an element, but where do we get the values from? We get the values from the Events Taxonomy.
It&#x2019;s enough to make you go crackers&#x2026; cue Shirley Temple