Pratt Sils LIS653 4 Fall 2007

Multimedia Information Organization and Visualization Matt Beeman, Magdalen Kadel and Cedomir Kovacev Standards & Metadata DCMI - Dublin Core Metadata Initiative (DCMI) EXIF - Exchangeable Image File Format XMP - eXtensible Metadata Platform IPTC – Int’l Press Telecommunications Council PLUS - Picture Licensing Universal System DIM2 – Digital Image Management TEI – Text Encoding Initiative / EAD – Encoded Archival Description / METS – Metadata Encoding & Transmission Standard / MARC – Machine Readable Cataloging / MPEG-7 – Motion Pictures Expert Group / NISO IMG (Z39.87) A DAM workflow

Citation Indices

Citation indices are a way to compare:

Authors and scholars

Journals within the same field

Articles within a field

Eigenfactor map example Uses for knowledge visualization The h -index is graphed by most online citation indexes, to compare scholars within a field. Other projects have used the information in citation indexes to visualize relationships between fields, as above. Features Collections / Database / Enterprise capability /Asset versioning / Manage intellectual property rights / Administration of access rights / Metadata flexibility / Controlled vocabularies / Search technology / Automated publishing mpeg-7 TV shopping? Education? Art? References Krogh, Peter. (2005). The Dam Book: Digital Asset Management for Photographers Digital Asset Management: A Closer Look at the Literature (A Research Monograph of the Printing Industry Center at RIT, March 2005) Import

THESAURI ~ THEIR STRUCTURE AND USE Acknowledgments Google Images. Amanda Piekart, Michelle Strassberg and Carla Edwards A Brief History of the Thesaurus  Derived from the Greek “Thesauros,” which means “treasury or storehouse.”  Many thesauri are now available on the Internet. They are important for creating a “controlled vocabulary” when conducting searches.

Why Thesauri are important

 Create a “controlled vocabulary” for searching

 Help locate “preferred terms” used by the particular search engine or database

Aid in producing best results from searching

Address a specialized audience

Figure 2. Getty Thesaurus of Art and Architecture. Figure 1. Finding the right words... Figure 3. ERIC Thesaurus. Figure 4. Thesaurus of Astronomical Terms.

How Thesauri are used

 Most are available in print and online versions

 Inputting keywords will lead searcher to preferred terms

Special Features

Can search in a variety of ways

Figure 5. The Visual Thesaurus. Future of Thesauri  More online thesauri  Thesauri will be embedded in search engines  More user-friendly References Visual Thesaurus http://www.visualthesaurus.com Thesaurus of Art and Architecture http://www.getty.edu/research/conducting_research/vocabularies/aat/index.html Thesaurus of ERIC Descriptors http://www.eric.ed.gov/ Thesaurus of Astronomical Terms http://www.mso.anu.edu.au/library/thesaurus Types of Thesauri For this presentation we will focusing on:  Thesaurus of Art and Architecture  Visual Thesaurus  Thesaurus of ERIC Descriptors  Thesaurus of Astronomical Terms

Ontologies and Digital Libraries Nicholas C. Jackson & Erin Elliot What is an Ontology “ What exists is that which can be represented! ontology is the study of what is real, what is reality, and or what existence” (Gruber,1). “An ontology is an explicit description of a domain; concepts, properties and attributes of concepts, constraints on properties and attributes, individuals” (Noy, 2). Ontology Engineering “ Defining terms in the domain and relation among them. Defining concepts in the domain (classes), arranging the concepts in a hierarchy (subclasses-superclasses hierarchy), defining which attributes and properties classes can have and constraints on their values, defining individuals and filling in values.” (Noy, 3). PRATT Uses in digital libraries “ The ontology enables concept-based searching that can improve precision of results far beyond common keyword matching” “The ontologies has the potential to offer navigation support that would facilitate the seeking process…” It “provide a conceptual structure that” organization and arrangement information (2006, Patuelli, 4). Ontology vs. Vocabulary, Taxonomy, and Thesauri “ A controlled vocabulary is a list of terms. A taxonomy is a collection of controlled vocabulary terms organized into a hierarchical structure. A thesaurus is a networked collection of controlled vocabulary terms. A formal ontology is a controlled vocabulary expressed in an ontology representation language” (Jernst, 1). PRATT Jernst. (2003). What are the difference between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model? McGuinness, D. L. (2003). Ontologies Come of Age. Spinning the Semantic Web: Bringing the World wide Web to Its Full Potential. MIT Press. Marcum, . 2002. Noy, N. F. McGuinness, D. L. (2000) Ontology Development 101: A Guide to Creating Your First Ontology. Stanford University. James W. (2002) Beyond Visual Culture: The Challenge of Visual Ecology . Portal: Libraries and the Academy, Vol. 2, No. 2, pp. 189-206. Noy, N. F., Ontology Engineering for the semantic web and beyond. Pattuelli, M.C. (2006). Context for content: Shaping learning objects and modeling a domain ontology from the teachers' perspective. In Blandford A. & Gow, J. (Eds.). Proceedings of the Workshop on Digital Libraries in the Context of Users' Broader Activities (DL-CUBA), pp. 23-27. JCDL 2006, Chapel Hill, NC, USA. http://www.isi.edu/isd/LOOM/LOOM-HOME.html “ The rise of the digital library is an important step in the development of the library as a cultural resource” (Marcum, 2002, 201). Digital Library? “ the use of computers to store library materials appearing in electronic (digital) format.” Digital records of collections “encoded in order to be stored, retrieved, and read by computer to collect, organize, preserve, and access information and knowledge records in digital form.” UMDL Ontology- http://www-personal.umich.edu/~peterw/Ontology/Beethoven/demo.html UMDL Ontology- http://www-personal.umich.edu/~peterw/Ontology/Beethoven/demo.html McGuinness, D. L. (2003). Ontologies Come of Age. Spinning the Semantic Web: Bringing the World wide Web to Its Full Potential. MIT Press. dog mammal animal rabid dog sick animal disease rabies rabid animal has has has

Tags: terms used to identify resources for retrieval; created and defined by users who are both the providers of content and the end-users

Folksonomies: composed of user-generated metadata, created by tagging pieces of digital information with their own searchable keywords

broad: third-party users assign tags to the same content, creating metadata for their bookmarks; sites aggregate this metadata, make it searchable

narrow: users tag their own content so that they can easily retrieve it and help others find it; useful for assigning metadata to unique content

Museum/Archival Applications

Value

Tagging: dialog between viewer and work as well as viewer and museum

Encourages personal interpretations of work

Fosters/maintains museum relationships

Serves altruistic purpose of museums

steve.museum (www.steve.museum)

Collaborative research project (launched in 2005) that explores the potential for tagging within the context of museums.

Goals:

Motivate users to tag, guide them through the process, and reward them when done (create prolonged and repeat use by giving users control)

Integrate contributed data into local documentation systems to improve access to collections

Encourage engagement with cultural content

Traditional Library Applications

Venues

Social Networking Sites

GoodReads

Information Management Sites

LibraryThing

PennTags

Directions

Towards a shelfless library

Items in multiple “locations”

Towards a personal experience

Evocation of personal feelings

Movement away from Library-centeredness

PennTags

Emergence of Folksonomies

Traditional subjects reaffirmed

Traditional facets reaffirmed

New descriptors emerge

Personal descriptions

New representations of the traditional emerge

Innovative combinations

Tagging & Folksonomies Social Applications

Value

User-generated vocabulary based on personal understanding of object

“ Placing Hooks”

Serendipitous browsing capabilities

Inexpensive way to create order and community

Examples

www.Flickr.com

Photo sharing and management site

Narrow

www.Del.icio.us

Social bookmarks manager

Broad

Limitations

No synonym control

No hierarchal structure

Do not consider the future

Pros:

supplements traditional cataloging by increasing access points, findability

encourages discovery/rediscovery and sharing of information

Cons:

no controlled vocabulary, synonym/homonym control; lack of hierarchy

tags may be imprecise, ambiguous, inconsistent, or overly personal

Goals: introduce controlled vocabulary to tagging systems; tools should be simple, efficient and not require large investments of capital; they should make it easier to locate new and older materials and allow reuse/remix of content and data to produce new collections and online tools

Cataloging Cultural Objects (CCO) Introduction to CCO Historical Overview Recommended Elements Managing Content & the Future of CCO

Cultural Heritage

Created by members of a culture

Found in texts, objects, images, etc.

Universal access benefits the community

Need for CCO

Attempted to use MARC & AACR, which fell short

Community created a shared element set (VRA Core) in 1990’s

Recognized need for data content and data format standards

Museums needed a more compact element set for exchanging data

Working Together

Forums organized by the National Initiative for a Networked Cultural Heritage

VISION & REACH project

VRA & CCO project

Purpose

Provide guidelines for cataloging cultural objects

Promotes good descriptive cataloging, shared documentation, and superior end-user access

Assists in the development of in-house cataloging rules or manuals.

Serves as a guide to building consistent cultural heritage documentation in a shared environment.

Audience/Users

Museum catalogers, curators, archivists, librarians

System designers

Scope

Descriptive metadata & authority control data

Points out term choices, defines order, syntax & form

Work Record

Object Naming, Creator info, Physical characteristics, Stylistic, Cultural & Chronological, Location & Geography, Subject, Class , and Description

Image Record

View Info

Authorities

Personal & Corporate Name

Geographic Place

Concept

Subject

The Getty Vocabularies

Metadata & Standards

CDWA

CDWA Lite

VRA Core 4.0

VRA Core 4.0 XML

Crosswalks & Mapping

CCO maps to CDWA & VRA 4.0 core elements

CCO works with the standard element sets of CDWA & VRA Core 4.0

Content Management Systems (CMS)

Manage visual information

digital Visual Information Management (dVIM) provides discovery, distribution & display of digital images

Examples of dVIM

Mdid - Madison Digital Image Database

Insight - Luna Imaging

CONTENTdm - DiMeMa/OCLC

Innovative interfaces

Digitool - Ex Libris

Digital Asset Mgmt

Telescope

Artesia

Mediabin

Canto

Piction

Moving Forward

Educational outreach

Future webpage allocated to training, tools, & presentations

Jamee Ard, Adrid Santos, Fumi Kelleher & Erica McDonald

Personal Information Management Matt Flaherty, Jessica Brooks, Maggie Balistreri

Since the Beginning

An issue ever since information has been available

It is the practice and study of acquiring, organizing, maintaining, and retrieving of personal information items

Personal Information Management Tools (reflects individual needs, preferences, and styles) E-mail: file organization, filters, chatting Calendar: reminders, calendar sharing Computer desktop: file finder tools, widgets Internet: search engines, RSS feeds Websites, Wikis, & Blogs: circulating information versus absorbing information Figure 2. Structure of Information System (Barreau, 1995). Figure 1. Ten Commandments. Key Image 1 Key Image 2 Figure 3. Before utilizing computer PIM tools. Figure 4. After utilizing computer PIM tools. Meta PIM: The PIM of a PIM Project Three individuals collaborate on a Personal Information Management project. Each uses, and all coordinate using, the following tools: E-mail, calendar, phone/text messaging, personal computer/desktop, Internet search tools, and a Wiki . Figure 5. PIM Wiki for PIM Group Project. Implications of PIM Save what? More digital space means we can save everything. Save where? Data saved across multiple tools benefits from an integration method. Retrieve how? Saving more and more personal information results in increased reliance on robust search tools, tagging, and metadata. References Barreau, D.K. (1995). Context as factor in personal information management systems. JASIS, 46 (5), 327-39. Jones, William and J. Teevan, editors. Personal Information Management . University of Washington Press: 2007.