The Keyword Aggregator web service A tool and methodology for managing digital objects’ keywords IINFORMATION MANAGEMENT TECHNOLOGY, LAND & WATER David Benn | Software Engineer, IMT Scientific Computing, CSIRO 1 December 2015 scikey.org

Agenda 2 | The Keyword Aggregator | David Benn What problem are we solving? Finding suitable (science) keywords for publications What have we built (to address the problem)? The Keyword Aggregator: –web service, example widget, vocabularies, related tools What remains to be done?

Collaboration 3 | The Keyword Aggregator | David Benn CSIRO Land & Water Nick Car * Simon Cox Jonathon Yu CSIRO Information Management Technology (IMT) David Benn IMT Scientific Computing eResearch projects x 2 –1 day per week for 6 months

What problem are we solving?

Publication Keywords 5 | The Keyword Aggregator | David Benn Data publication, Software publication, Journal paper, Conference paper …

Publication Keywords 6 | The Keyword Aggregator | David Benn

Publication Keywords: Controlled Vocabulary 7 | The Keyword Aggregator | David Benn

Publication Keywords: Free Entry 8 | The Keyword Aggregator | David Benn

What have we built? Keyword Aggregator

Aggregated Keyword Source 10 | The Keyword Aggregator | David Benn ?

Folksonomies 11 | The Keyword Aggregator | David Benn lowest ranking

Design Goals 12 | The Keyword Aggregator | David Benn Fast keyword search, even with many vocabs. Relevant search results Various search strategies may be needed, not just full-text search. Allow for folksonomy-style use. Web service and demo client (widget) For direct use or as a reference implementation (e.g. ZK vs jQuery). Simple management of separate vocabularies.

Keyword Aggregator 13 | The Keyword Aggregator | David Benn Web Service Vocab 1 Vocab 2 Vocab n … Folkso nomy

14 | The Keyword Aggregator | David Benn Keyword Aggregator

REST API: | The Keyword Aggregator | David Benn {"head": {"vars": ["graph_name", "term", "sum", "text_value", "prefLabel"]}, "results": {"bindings": [ [{"term": {"type": "uri", "value": " "graph_name": {"type": "uri", "value": " "vocab_subject": {"xml:lang": "en", "type": "literal", "value": "science"}, "text_value": {"xml:lang": "en", "type": "literal", "value: "EARTH SCIENCE > Agriculture > Animal Science > Animal Physiology and Biochemistry"}, "sum": {"datatype": " "type": "typed-literal", "value": "20"}, "vocab_title": {"xml:lang": "en", "type": "literal", "value": "GCMD Science Keywords V6"}, "vocab_status": {"type": "uri", "value": " "prefLabel": {"xml:lang": "en", "type": "literal", "value": "EARTH SCIENCE > Agriculture > Animal Science > Animal Physiology and Biochemistry"}}] }

Usage Stats: in relational database 16 | The Keyword Aggregator | David Benn KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| KWAG|test| |none| …

What have we built? Vocabularies

SKOS: 18 | The Keyword Aggregator | David Benn

Vocabularies 19 | The Keyword Aggregator | David Benn MODSIM 2011, 2013 keyword analysis.

Vocabularies 20 | The Keyword Aggregator | David Benn GCMD: Global Change Master Directory science keywords

Vocabularies 21 | The Keyword Aggregator | David Benn Wikipedia Computer Science

Discoverable Vocabularies 22 | The Keyword Aggregator | David Benn

Vocabulary Metadata 23 | The Keyword Aggregator | David Benn

24 | The Keyword Aggregator | David Benn Vocab Metadata Generation

25 | The Keyword Aggregator | David Benn

Vocab-of-vocabs concept A SKOS ConceptScheme can point its hasTopConcept property to a Concept outside itself. Useful for broad vocabs where specialisations exist –e.g. science keywords A “vocabulary-of-vocabularies”| Nicholas Car 26 | hasTopConcept

Vocab-of-vocabs concept Allow a single, integrated, vocab set to be used by search tools No change to underlying vocabulary A “vocabulary-of-vocabularies”| Nicholas Car 27 | skos:ConceptScheme GCMD Terms skos:Concept OCEANS skos:Concept MARINE SEDIMENTS skos:Concept TURBIDITY skos:ConceptScheme Turbidity Types skos:Concept Turbidity Type 1 skos:Concept Turbidity Type 2 hasTopConcept Vocab 2 Vocab 1

Search Strategies Explored 28 | The Keyword Aggregator | David Benn Simple matching in vocab text elements Weighted semantic Assign weights to text matches in different SKOS elements –e.g. skos:prefLabel, skos:altLabel, skos:definition, dc:description Hierarchical Exploits explicit broader/narrower relationships present in some vocabs Historical/popularity based

Administration 29 | The Keyword Aggregator | David Benn

What remains to be done?

Future Work: publication, improvements 31 | The Keyword Aggregator | David Benn Software publication in CSIRO Data Access Portal (in draft) Search result “decoration” from JSON to enhance widget keyword selection. Automate ingestion of arbitrary number of known vocabularies. Streamline vocabulary submission process. Mine arbitrary/federated metadata for vocabulary existence. Inter-vocabulary individual term linking search strategy (e.g. skos:related). Use of previously chosen keywords to inform search result prioritisation. Scale search performance with large or many vocabularies. Web-time hierarchical search: pre-compute, more resources, better graph engine.

IMT Scientific Computing, CSIRO David Benn Software Engineer t e w my.csiro.au/B/D/David-Benn.aspx Thank you IMT/SCIENTIFIC COMPUTING