LINKED DATA EXPERIENCE AT MACMILLAN Building discovery services for - - PowerPoint PPT Presentation

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LINKED DATA EXPERIENCE AT MACMILLAN Building discovery services for - - PowerPoint PPT Presentation

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LINKED DATA EXPERIENCE AT MACMILLAN Building discovery services for scientific and Tony Hammond scholarly content on top of a semantic data model Michele Pasin 22 October 2014 Background About Macmillan and what we are doing 1 Linked Data

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LINKED DATA EXPERIENCE AT MACMILLAN

Building discovery services for scientific and scholarly content on top of a semantic data model

22 October 2014

Tony Hammond Michele Pasin

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Linked Data at Macmillan | 22 October 2014

1

Background

About Macmillan and what we are doing

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Macmillan Science and Education

Linked Data at Macmillan | 22 October 2014

Group brands and businesses

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MS&E Current trends

Change Drivers

  • Digital first workflow

– print becomes secondary – support for multiple workflows

  • User-centric design

– things, not data – focus on user experience

  • Deeply integrated datasets

– standard naming convention – common metadata model – flexible schema management – rich dataset descriptions

Linked Data at Macmillan | 22 October 2014

Developing a richer graph of objects

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NPG Linked Data Platform (2012)

Deliverables (2012–2014)

  • Prototype for external use
  • Two RDF dataset releases in 2012

– April 2012 (22m triples) – July 2012 (270m triples)

  • Live updates to query endpoint
  • SPARQL query service (decommissioned)

Current Work (2014–)

  • Focus on internal use-cases
  • Publish ontology pages
  • Periodic data snapshots

Linked Data at Macmillan | 22 October 2014

data.nature.com

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NPG Core Ontology (2014)

Features

  • Classes: ~65
  • Properties: ~200
  • Named graphs (per class)

Namespaces

  • npg: => http://ns.nature.com/terms/
  • npgg: => http://ns.nature.com/graphs/

Approach

  • Incremental formalization (RDF, RDFS, OWL-DL)
  • Shared metamodel vs. automatic inference
  • Minimal commitment to external vocabs

Linked Data at Macmillan | 22 October 2014

Things: assets, documents, events, types

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NPG Subject Pages (2014)

Features

  • Based on SKOS taxonomy

– >2500 scientific terms – content inherited via SKOS tree

  • Dynamically generated

– one webpage per subject term – secondary pages for article types

  • Various formats, e.g. e-alerts, feeds

– allows people to ‘follow’ a subject

  • Customized related content

– ads, jobs, events, etc.

Linked Data at Macmillan | 22 October 2014

Topical access to content

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Linked Data at Macmillan | 22 October 2014

2

Data Storage and Query

Achieving speed by means of a hybrid architecture

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Content Hub

Capabilities

  • Discovery – Graph
  • Storage – Content Repos

Features

  • Hybrid RDF + XML architecture

– MarkLogic for XML, RDF/XML – Triplestore (TDB) for RDF validation

  • Repo’s for binary assets

Datasets

  • Documents (large; >1m)
  • Ontologies (small; <10k)

Linked Data at Macmillan | 22 October 2014

Managed content warehouse for data discovery

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System Architecture

Linked Data at Macmillan | 22 October 2014

Hub content

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Content Discovery – Principles

Generations

  • 1st – Generic linked data API (RDF/*)
  • 2nd – Specific page model API (JSON)

Concerns

  • Speed (20ms single object; 200ms filtered object)
  • Simplicity (data construction)
  • Stability (backup, clustering, security, transactions)

Principles

  • Chunky not chatty, all data in a single response
  • Data as consumed, rather than as stored
  • Support common use cases in simple, obvious ways
  • Ensure a guaranteed, consistent speed of response for more complex queries
  • Build on foundation of standard, pragmatic REST (collections, items)

Linked Data at Macmillan | 22 October 2014

Readying the API for applications

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Content Discovery – Optimization

Approaches

  • TDB + Fuseki – SPARQL
  • MarkLogic Semantics – SPARQL
  • MarkLogic – XQuery
  • MarkLogic (Optimized) – XQuery

Techniques

  • Partitioning – RDF/XML objects
  • Streaming – serialization
  • Hashing – dictionary lookup
  • Cacheing – Varnish

Linked Data at Macmillan | 22 October 2014

Tuning the API for performance

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Content Storage – Layout and Indexing

Challenges

  • Sort orders
  • RDF Lists
  • Facetting, counting

Layout

  • Semantic RDF/XML includes in XML
  • RDF objects serialized in list order
  • Application XML for subject hierarchy

Indexes

  • Indexes over all elements
  • Range indexes for datatypes (e.g. datetimes)

Linked Data at Macmillan | 22 October 2014

Readying the data for page delivery

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In Conclusion

Summary

  • An RDF metamodel allows for scalable enterprise-level data organization
  • It is crucial to adequately distinguish between external and internal use cases
  • A hybrid architecture proved to be an efficient internal solution for content delivery

Future Work

  • Grow the ontology so that it matches product requirements more closely
  • Support automated reasoning and richer query options – both RDF and XML based
  • Maintain and expand the vision of a shared semantic model as a core enterprise asset

Linked Data at Macmillan | 22 October 2014

A few lessons learned

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For more information please contact TONY HAMMOND Data Architect, Content Data Servicestony.hammond@macmillan.com MICHELE PASIN Information Architect, Product Office michele.pasin@macmillan.com

Thank you