INLS 520 – Erik Mitchell INLS 520 Information Organization.

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Presentation transcript:

INLS 520 – Erik Mitchell INLS 520 Information Organization

INLS 520 – Erik Mitchell Review Controlled vocabularies –Term Lists, Hierarchies, Trees, Paradigms, Facets, Folksonomies Knowledge organization systems –Term Lists, Thesauri, Taxonomies, Ontologies

INLS 520 – Erik Mitchell Today Poster topic review Poster creation concepts Automation in metadata & organization –RDF –OWL Guest Speaker – Barrie Hayes

Creating poster presentations Content –Methodological approach Title, question, overview, methods, findings, observations –Conceptual approach Title, question, model or framework Structure Balancing words & images Document flow Examples - 1, 2, 3, INLS 520 – Erik Mitchell

Creating poster presentations Technology –Creation tools PowerPoint Templates in blackboardblackboard An image editor HTML Display –Flickr, PrintedFlickrPrinted Some guidelines 1, 2, 3, INLS 520 – Erik Mitchell

Automation Group discussion –Based on the articles by Hlava, Hearst, and Stearns what are some of the primary uses of automation in information organization? –Is automation primarily a tool to create representations of resources or to enable retrieval of resources? INLS 520 – Erik Mitchell

Automatic Indexing Automatic Extraction/representation –Lancaster calls this: “Words or phrases appearing in a text are extracted and used to represent the content of the text as a whole” (Lancaster 284) Automatic Classification/Categorization –The computer compares terms in the document against thesauri or controlled vocabularies to map a word in the resource to an accepted index term (Lancaster 287) Automatic Abstract/Surrogate Generation –The extraction of sentences from documents to create an abstract (Lancaster 298) Automatic index/tool Generation –Creating spelling dictionaries, word lists, indexes, etc to be used for other automation techniques Latent Semantic Indexing - Concepts are extracted and analyzed to detect relationships. These relationships are then used to help identify & rank documents (overview)overview INLS 520 – Erik Mitchell

Automatic metadata use Metadata Harvesting –Using automated techniques to discover and extract metadata from documents OAI/PMH Knowledge representation & discovery –Using structured ontologies to make statements and inferences about resources –OWL OntologiesOWL Ontologies Metadata interoperability –Using structured metadata to automatically connect with other metadata systems –OpenURL, XML SchemaOpenURL Transformation –Creating new documents through the automatic extraction, analysis, and processing of resources –XML/XSL INLS 520 – Erik Mitchell

Metadata standards XML –Structure & syntax but no ‘semantic constraints’ XML Schema –Restrict structure of XML, extend XML with datatypes RDF –Data-model showing relationships among resources RDF Schema –‘Vocabulary for describing properties and classes of RDF resources’ OWL –Added vocabulary for describing properties & classes Relationships, cardinality, equality, charicteristics INLS 520 – Erik Mitchell

INLS 520 – Erik Mitchell RDF Subject, property, object triples Transmitted in xml RDFS extends RDF with an ontology language –Properties, specialization OWL –More powerful extension of RDFS –Uses same syntax of RDF

INLS 520 – Erik Mitchell RDF Model Webpage: “Saki Knafo” Author (Value) Object (Property type) Predicate (Resource) Subject “The author of the stuff webpage is Saki Knafo” - A literal, a triple, a statement

INLS 520 – Erik Mitchell How is RDF different? RDF is a descriptive model that –Allows variable contextualized description –Deconstructs the descriptive process –Allows more granular automated processing of data –Uses exact markup to indicate the context of values (namespaces, schemas) –Bags, Sequences, Alternative values, parseType

INLS 520 – Erik Mitchell Encoding RDF in XML <rdf:RDF xmlns:rdf=" xmlns:dcterms=" xmlns:dc=" xmlns:rdfs=" The Hang: The Island of Black Jeans SAKI KNAFO Sun, 16 Sep :04:40 GMT descriptive content

INLS 520 – Erik Mitchell Iterative RDF description <rdf:RDF xmlns:rdf=" xmlns:vcard=" card.xsd" xmlns:dc=" xmlns:rdfs=" The Hang: The Island of Black Jeans Sun, 16 Sep :04:40 GMT descriptive content rdf:about=" Saki Knafo

INLS 520 – Erik Mitchell RDFS RDF Schema –Defines additional rdf elements that help type relationships Special Classes –Based on RDF Classes / Properties / Attributes with additional Allows the creation of vocabularies / ontologies

INLS 520 – Erik Mitchell Ontology Definitions “The study of being or existence” “A conceptualization of a specification” (Gruber)Gruber “An ontology formally defines a common set of terms that are used to describe and represent a domain.” (OWL)

INLS 520 – Erik Mitchell Ontology Concepts Classes –Names of objects in the domain Relationships between classes Connections between classes Properties of classes Background or identifying knowledge of these objects Constraints on these properties & relationships Limits and parameters of the relationships

INLS 520 – Erik Mitchell A good ontology has Features: –Meaningful – all classes have instances –Accurate / correct –Non-redundant – each class/instance is represented in a single way –Rich in description – context, content Enabled functionality: –Able to use queries to connect new pieces of information –Use XML & definitions to integrate knowledge across domains

INLS 520 – Erik Mitchell Ontology Continuum Keyword Lists Basic Thesauri Complex Thesauri Taxonomies Simple Ontologies (wordnet) Complex Ontologies (OWL)

INLS 520 – Erik Mitchell SHOE Ontology project – Possible to build an ontology for anything –Simple HTML Ontology Extensions (SHOE) Project Sample projects –Beer Ontology –Document Ontology

INLS 520 – Erik Mitchell Ontology Concepts Multiple inheritance Vertical and horizontal relationships Decomposed subject/object Predicate based description (isRelatedto, hasVersion)

INLS 520 – Erik Mitchell Creating an Ontology Determine Scope of field, define boundaries Check for existing ontologies, vocabularies Select a top-down/bottom-up approach –Identify concepts, vocabulary, parameters, constraints Identify relationships –Multiple hierarchies, inheritance Build, test, maintain

INLS 520 – Erik Mitchell OWL (Web Ontology Language) An ontolgy that is geared towards representing information on the web –Classes, properties, and relationships that describe URIs and their facets. Based on the Triple concept –Subject, Predicate, Object –3 versions: OWL-Lite, OWL-DL, OWL-Full Formatted in RDF/XML –Uses RDF and RDFS as a foundation –Adds new elements in the owl namespace

INLS 520 – Erik Mitchell OWL Versions OWL-Lite –Simple hierarchies, constraints OWL-DL –Uses description logics Logic-based semantic markup based on first-order predicate logic –Still guarantees finite relationship processing –Adds ‘reasoning’ capacity to infer information/relaitonships OWL-Full –Most complex –Open ended, possible to get into infinite processing

INLS 520 – Erik Mitchell OWL Example <rdf:RDF xmlns:rdf= xmlns:rdfs=" xmlns:owl= xmlns= xml:base=" 1.0 An ontology containing the basic part relations: partOf, hasPart, partOf_directly, and hasPart_directly. These are described in the accompanying note. Author: Chris Welty (Chris Welty)

OWL – Lite features Class A collection of things related to each other by properties rdfs:subClassOf A way of showing hierarchical class relationships rdf:Property A stated relationship between an thing and a value (hasChild, hasRelative, hasSibling, hasAge) Bi-directional, Transitive (hasAncestor), Rdf:subPropertyOf Similar to subClassOf, a way of showing property hierarchies Individual Instances of classes (objects) INLS 520 – Erik Mitchell

OWL relationships INLS 520 – Erik Mitchell Practical guide to OWL ontologies

INLS 520 – Erik Mitchell Some OWL Examples Airport Pizza

INLS 520 – Erik Mitchell Next Week(s) 10/28 – No class 11/4 – Metadata based services, guest speaker 11/11 – no class 11/18 – no class 11/25 – semantic web 12/2 – final projects due