HUMANITIES NETWORKED INFRASTRUCTURE (HUNI)

JAILBREAKING AUSTRALIA’S CULTURAL DATA

CRICOS Provider Code: 00113B

NATIONAL E-RESEARCH COLLABORATION TOOLS AND RESOURCES (NECTAR)

NeCTAR is a $47 million dollar, Australian Government project, conducted as part of the Super Science initiative and financed by the Education Investment Fund. The University of Melbourne is the lead agent, chosen by the Commonwealth Government.

VIRTUAL LABORATORY PROGRAM

• Ensure that Australian cultural datasets and the research associated with them become part of the emerging international Linked Open Data environment.

• Enable research enquiries to move easily from: what is? to where is?

• Support the role of annotation and metadata in discovery of new knowledge or the means to elucidate new knowledge

• Position the idea of data as both a subject and object of analysis in humanities

• Contribute to debates around standards for development and implementation

HuNI BROAD BENEFITS

• Enable humanities researchers to work with cultural datasets more efficiently and effectively, and on a larger scale;

• Encourage the systematic sharing of research data between humanities researchers (including the cultural dataset curators themselves), the community and cultural institutions;

• Encourage a greater level of cross-disciplinary and interdisciplinary research, both within the humanities/creative arts and between the humanities/creative arts and other disciplines, and the wider public;

• Support innovative methodologies such as network analysis, game theory and ‘virtual history’ that rely on large-scale datasets

HUNI: SPECIFIC BENEFITS

1. Organisational level: the goals and processes of the institutions involved

2. The semantic level: meaning of the exchanged digital resources3. Technical level: implementing data interoperability requires

both data integration and data exchange processes as well as enabling effective use of the data that becomes available

Pasquale Pagano, ‘Data Interoperability’ (GRDI2020)4. Project level: The advent of more complex ‘big humanities’

projects requires multiple and multi-disciplinary personnel which in turn entails the organization of different workflows and expectations: e.g. challenge of developing a comprehensive or consortial approach, common definition of project method etc.

INTEROPERABILITY

1. A PARTNERSHIP… a Deakin led consortium • Cultural data providers (10) – project co-operators• Humanities software developer (1) – project co-

developers• eResearch organisations (2) – lead development

agencies

HUNI PARTNER DATASETS

AMHD

MAPCAARPBonzaAFIRCCircus OzAusStage

Media: film, cinema, theatre, newspapers, magazines, advertising, music, live performances

DAAOAustLitAWRADBDoS

Biographical: artists, designers, writers, significant people, scientists, Sydney demographics

EOAS

AUSTLANGMura

Indigenous languages

AUSTLIT

ADB

DAAO

AUSTLANG

bonza

AUSSTAGE

EOAS

TUGG

Welcome to the Cinema and Audiences Research Project (CAARP) database: An online encyclopaedia of cinema-going in Australia.

DataThis site contains information on film screenings and venues in Australia. 430,137 screenings10,256 films1,978 cinemas1,649 companiesFrom 1846 to now

• NeCTAR investment of $1.33M

• Partner contributions of $480,000

• Partner in-kind contributions amounting to >$1M

A FISCAL COLLABORATION

COMMUNITY BUILDING• Collated user-stories (20) • Online showcase events – next one is 4th September

2013• Live link to the latest alpha prototype on huni.net.au;

feedback buttons• Wider beta launch at eResearch Australasia in October

2013• Stay up to date through our monthly Newsletter and

blog feed• Follow us on twitter - @HuNIVL

Information design challenge to build an ontology and use linked data and controlled vocabularies for data to be aligned and related.

• Reading the data. Characteristics of the data determine the ontological components selected and the major “entities” (aka “access points”).

• Identified early as: people, organisations, events, relationships, places, dates, resources, and subjects.

• Components from ontologies already available and being reused or kept in our sights: CIDOC-CRM, FOAF, FRBR, FRBR-OO, BibFrame and PROV-O.

2. INTEGRATING MEANING

PHASE ONE

HUNI ONTOLOGY March 2013

HUNI ONTOLOGY (all classes and object properties)

ALIGNING ONTOLOGIES

3. HuNI DATA ARCHITECTURE

A total of 28 Australian datasets are being harvested for integration into HuNI

• Data gateway components, called HuNI Corbicula, deployed on the NeCTAR Cloud to harvest the XML feed data and transforming it into forms suitable for ingestion into two HuNI data aggregates: a Solr search server [HuNI Data], and a Jena RDF Triple Store [HuNI Linked Data]

DATA INTEGRATION

The harvesting process requires:• Live data feeds

deployed at the partner sites to publish updated partner data as XML

TWO HUNI DATA AGGREGATES?Solr aggregate RDF aggregate

28

0

7

1

4

2

1

24

0

7

1

4

2

1

6

part

ner

data

set

part

ner

data

set

TECHNOLOGY STACK

• front-end frameworks - AngularJS and Twitter Bootstrap single page web app

• tools hosting framework - Open Social via Apache Shindig

• back-end framework - SpringMVC via Roo.• layer integration - RESTful web services

• Search the HuNI Data• Save their search results as a

private collection• Refine their collection through

additional searches• Analyse and annotate their

collection with their own assertions and commentary

• Export their collection for further analysis

• Publish and share their collection and research

RESEARCH ACTIVITIESA researcher with a HuNI account will be able to:

Scholarly researchers will also be able to perform a “deep search” of the graphs in RDF Triple Store.The large-scale aggregation of Linked Data makes explicit the relationships and connections between related records across all the partner datasets, enabling the researcher to construct more complex semantic queries.

RESEARCH ACTIVITIES 2

EARLY VLAB PROTOTYPE

VIRTUAL LABORATORY RESEARCHER WORKFLOW: Discovery (part 1)

VIRTUAL LABORATORY RESEARCHER WORKFLOW: Discovery (part 2)

VIRTUAL LABORATORY RESEARCHER WORKFLOW: Discovery (part 3)

VIRTUAL LABORATORY RESEARCHER WORKFLOW: Analysis (part 1)

VIRTUAL LABORATORY RESEARCHER WORKFLOW – Analysis (part 2)

VIRTUAL LABORATORY RESEARCHER WORKFLOW: Sharing

4. THE PROJECT• project director/community liaison (20%)• project manager (100%)• technical coordinator (100%)• information services coordinator (90%)• community engagement (30%)• communication coordinator (20%)• administrative support (20%)• software developer(s)

NeCTAR Directorate

HuNI Steering

Committee

Team HuNI

Technical Working

Group

Expert Advisory

GroupExpert Data

Group

PROJECT WEBSITE: huni.net.au

PROJECT WIKI: apidictor.huni.net.au

HuNI: a virtual laboratory for the humanities

http://huni.net.au/@HuNIVL