RDA offers semantic meanings and powerful new linking associations

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2 RDA offers semantic meanings and powerful new linking associations Special Libraries Association Engineering Division Linked Data: What s New with Knowledge Organization on the Web June 20, 2017 David Stern Saint Xavier University

3 Meaningful metadata We will describe possibilities for deeper semantic linking using object-based attributes and associated values. One can employ enhanced navigation using the intelligent processing of semantic and relational values. We will demonstrate a few examples of enhanced metadata and novel navigation options utilizing this additional nuanced and layered information.

4 Metadata Today Metadata limitations within our current records: Content only general information Structure at the whole record level Granularity at the whole record level Functionality little functional information Semantics little semantic assistance Simple description not semantic and relational descriptions between and among the various record/item objects.

5 Limited metadata Content only general information. The description of the book/movie/play. Few details about the nuances of the individual characters (objects). Little comparison to similar materials.

6 Limited metadata Structure/Granularity at the whole record level. May include anthology information. May include music performer information for each piece not often actors or characters. Few details about the nuances of the individual elements or characters.

7 Limited metadata Functionality little functional information. May have simple descriptions of elements. May include detailed information for some elements musical forms carry implicit information-- but aspects are not listed. No details about the potential behaviors or properties of the individual elements or characters. (i.e. Liberal Senator, Bad Guy)

8 Limited metadata Semantics provides little semantic depth. May include subject headings. Does not include nuanced and/or multiple meanings or representations of elements. Little detail about the nuances or changing roles of individual elements or characters. Simple description not semantic and relational descriptions between and among various elements.

9 Limits within the current Knowledge Structure Navigation tools allow facets and visualization of content. Organizational elements: controlled hierarchy keywords within set vocabularies Folksonomies (dynamic free text) The nature of the information Ontologies inherent structured relationships (linkages) Taxonomies according to hierarchy outline (broader/narrower) Free text relational linking (with homegrown taxonomy?) Raw data keywords, frequency, and near/within fields

10 The RDA triplet: a relational tool The RDA structure provides an infrastructure that allows for powerful new linking associations based upon structured semantic meanings. We will look at the possibilities of using enhanced values - properties associated with each object - in order to create deeper semantic linking. Imagine searching for: any character in a novel who was like Holden Caulfield, in that he represented youth and teenage rebellion and angst. Such semantic attributes could be used to search for common deeper meanings -- if the metadata for such values and associations were present in the RDA records.

11 Metadata Elements in an RDA Knowledge Database RDA allows for new layers of descriptive semantic elements: RDA triples provide association links using the following: Object Predicate: Semantic meaning Value One can mine relationships using these concept spaces

12 RDA semantic associations Example association links. Object : Action : Value Atticus Finch : racism : non-carrier/carrier Sun : symbol : hope

13 Enhanced sematic meanings RDA triples can provide contextual meaning links. Object : semantic meaning : Value The rabbit is ready to eat. Option 1: The rabbit is the eater. Rabbit : food : eater Option 2: The rabbit is the eaten. Rabbit : food : portion

14 Building a Knowledge Database Considerations and Actions: Know your content (and associated properties) Know your user behaviors/needs Select the appropriate tools Develop facets, taxonomies, crowdsourcing options Build an intuitive interface Review and Revise in reaction to user feedback Required: apply RDA metadata and actions across multiple tools/databases

15 Next: Integrating Disparate Materials Into One Knowledge Database Wine snob example Capture of links, images, text, memories (Evernote, Zotero, other apps) Capture of purchasing and preference info (Vino Wine Scanner/apps) Capture of subscription info (apps: Corkz, Drync, Wine Spectator) Capture social contacts (Paper for FB, Flipboard or Feedly, Yahoo feeds) Capture favorite books (GoodReads or Library Thing) Scraping of ratings data from web pages (Outwit) Into Excel spreadsheets for later manipulation Run updates to locate new material

16 Next: Integrating Disparate Materials Into One Knowledge Database Hate speech example Capture of links, images, text, social comments (Evernote, Zotero, etc.) Capture of radio and video clips (scalability -> enterprise server) Capture of subscription info (behind firewall) Capture social contacts (Paper for FB, Flipboard or Feedly, Yahoo feeds; then diigo for sharing snapshots of these communications) Pointers to published examples (GoodReads or Library Thing) Scraping of polling data from web pages (Outwit) Into Excel spreadsheets for later manipulation Run updates to locate new material

17 Next: Integrating Disparate Materials Into One Knowledge Database The present option: Linking between platforms not entities. Discoverability across tools IFTTT If This Then That seamlessly link/load across platforms/services Triggers launch Recipes that perform linking tasks

18 Leadership Action Encourage the creation of deeper semantic descriptors Develop community ontologies for powerful linking Develop interfaces to maximize relational options Dedicate resources to metadata creation

19 More information about RDA possibilities My open access article: Stern, David. "Making Search More Meaningful: Action Values, Linked Data, and Semantic Relationships" Online Searcher 39 (5) : (September/October 2015).

20 Questions David Stern Saint Xavier University