Extending Karkinos for Linked Data Digital Innovation Group - Fall 2015 Tushar Jain

Objectives Introduce Karkinos Introduce Linked Data What would it take to provide data in Karkinos as Linked Data? What data would we provide and how would we have to provide it?

Introduction to Karkinos Its an Hydra Head or in simple terms – a web application developed using Hydra framework Hydra is a repository solution that is being used by institutions worldwide to provide access to their digital content. Hydra provides a versatile and feature rich environment for end-users and repository administrators alike

Linked Data Objective: Linked Data is about using the Web to connect related data that wasn't previously linked, or using the Web to lower the barriers to linking data currently linked using other methods cRud – Modern applications wants to make smart queries over globally connected data sets Linked Data is a publishing paradigm for making data and not just human-readable documents fully accessible and inter-linkable anywhere on the Internet Berners Lee described a 5-star rating system for published data to be considered Linked Data Available on the web Available as structured data readable by a machine Available in a non-proprietary format Expressed using open World Wide Web Consortium (W3C)[9] standards Linked to other data on the web

How Linked Data works? Principles: Use URIs as names for things – anything, not just documents Use HTTP URIs – need for accessibility Provide useful information in RDF – represents basic bricks for the structure Include RDF links to other URIs – glue that would connect different datasets

Different Shades of Data Domain- Sports Center Website response – Web Service (JSON document) Domain – Dinning Website response – HTML Document This pose a challenge to the semantic web application - query two different technological stacks to generate results. Also this reflects the existing lack of link between the datasets across the globe as data in different domains might have different storage structures UD Arizona vs Arizona State10021 November PM MST Sun Devil Stadium, Tempe, Arizona North Entrance – B Block 23123My Big Fat Greek RestaurantGreek(480) :00 AM – 10:00 PM 525 S Mill Ave, Tempe, AZ eathealthyeatgreek.com

Smart queries are possible if different datasets are build using more uniform structure Example: Search café or dinning near Sun Devil Stadium Different Shades of Data Wildcats vs Sun Devils 2015 Arizona vs Arizona State USA 19:00 MST My Big Fat Greek Restrauant 525 S Mill Ave, Tempe, AZ (480) eathealthyeatgreek.com 10$ Greek specialties plus pizzas, pastas & calzones fill the menu at this casual chain eatery

The Idea – Karkinos and Linked Data Thing Karkinos Repo - Humanties Thing Karkinos Repo - Biomedical Thing DisGeNET Dataset Thing Geonames Need to connect the Karkinos/Hydra repositories over the Internet using http, rdf, rdfs, urls

Karkinos and Linked Data Resources as URL over http Karkinos store the resource metadata as ruby objects Need infrastructure to handle the GET request and provide with appropriate response based on the ACCEPT header in request – Content Negotiation Thing RDF HTML

Karkinos and Linked Data Provide useful information using RDF Karkinos uses MODS vocabulary to generate metadata of corresponding Generic File or Data File We need to create a parser that can serialize the metadata model into RDF documents Possible Alternatives: JSON::LD parses and serializes JSON-LD into RDF and implements expansion, compaction and framing API interfaces.JSON-LDRDF

Karkinos and Linked Data Link to other Data Sets Karkinos uses MODS vocabulary to create the metadata of the corresponding Generic or Data files. This generate an inherent link to any other datasets that uses MODS vocabulary in their repository We can add explicit links which can help link MODS vocabulary to datasets using different RDF vocabularies. There exist some popular predicates for this purpose. owl:sameAs foaf:topic foaf:primaryTopic foaf:maker/foaf:made

References

Thank You