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Going from Tables to Graphs http://www.ﬂickr.com/photos/thomasjwoods-com/2264301251
Going from Tables to GraphsNodes and links in a graph
Going from Tables to GraphsAs computing power increases, the ability to buildmore and more complex graphs becomes a reality. msulibraries lookbackmaps msulibraries internetarchive msulibraries librarycongress lookbackmaps internetarchive internetarchive librarycongress
Introducing TriplesNodes and Links follows jonvoss 1n9r1d• Quite simply: Subject, Predicate, Object• gives us the ability to describe entities in a way that is machine readable
What do we know about the person:Ed Summers (aside from the fact that he rocks)? Bio: Hacker for libraries, digital archaeologist, pragmatist. bio knows depiction of knows http://inkdroid.org/ehs.rdf
Triples for machines• Triples can be serialized in many diﬀerent ways, including Resource Description Framework, RDF/XML, RDFa, N3, Turtle, etc, but they all describe things in the <subject><predicate><object> format.• Of course, we need to be consistent and predictable for machines to understand us.• We need to follow simple rules and protocols
Linked Data.• Goal is to enable researchers to explore and interpret the commonalities or divergences in the data.• Multiple signiﬁcant scholarly humanities datasets to pipe in and aggregate with varying levels of standards and technologies.• Information design challenge to build an ontology and use linked data and controlled vocabularies for data to be aligned and related.• Provide a virtual environment to explore this data and process with tools.
HuNI Data. AusStage AUSTLANG Mura & Pathways Media Archives Project Encyclopedia of Australian Science Colonial Australia Popular Fiction Find and Connect Victoria Australian Women’s Register eMelbourne: the Encyclopedia of Melbourne Scholarly Data Providers eGold: Electronic Encyclopedia of Gold in Australia Chinese-Australian Historical Images in Australia Reason in Revolt, Source Documents of Australian Radicalism Guide to Australian Business 104 Records Australian Trade Unions Archive CircusOz Living Archive Video Collection Australian Film Institute Research Collection
Rethinking Resource Discovery.• Goal is to enable researchers to explore and interpret the commonalities or divergences in the data. • Support researcher needs to discern facts (what is?) and locate more information (where is?) drawing on Australian cultural scholarly data. • Major task is to aggregate heterogeneous humanities data that may be related to digital representations e.g. digital text, audio-visual etc ﬁles. • Method is linked data, using ontology and controlled vocabulary development. • Outcomes are the researcher can move easily from: what is? to where is? in their information seeking.
Information Seeking.• Information seeking is supported by intellectual access tools, which include library catalogues, archival ﬁnding aids, reference tools, subject databases, journal repositories and information resources (physical and digital).• Critical step in information seeking is undertaken in preliminary visit to the “reference shelf” and it can often be revisited to satisfy research questions.• What is the researcher question? What information can I ﬁnd out about this person and their life, what they have done, etc. A classic biographical enquiry.• Know the name and other facts associated with a person in the HuNI graph (in the lab) and follow a hyperlink to a range of web resources related to that person.
Metadata Mash Up.• A mash up of reference tools and ﬁnding aids: factbooks, dictionaries, encyclopaedias, bibliographies and catalogues and archival registers.• Link needs to be forged with the ontologies for domain resources e.g. TEI and resource discovery metadata.• Exploring this with the crosswalk between CIDOC-CRM and FRBR-OO (latest draft) and keeping an eye on BibFrame.• Same problem being explored in another NeCTAR virtual lab project: Human and Communication Science.• Role of annotation and metadata in discovery of new knowledge or the means to elucidate new knowledge needs to be unpacked.
Ontology Development.• 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” in library lingo). • Identiﬁed early as: people, organisations, events, relationships, places, dates, resources, and subjects. • Components from ontologies already available are being reused or kept in our sights: CIDOC-CRM, FOAF, SKOS, FRBR, FRBR-OO, BibFrame and PROV-O.
Useful ReferencesNISO. Information Standards Quarterly, Spring/Summer 2012http://www.niso.org/publications/isq/2012Europeana. Linked Open Data – What is it?http://vimeo.com/36752317Linked Open Data – Libraries, Archives, Museums (LODLAM)http://lodlam.net/W3C Library Linked Data Incubator Grouphttp://www.w3.org/2005/Incubator/lld/Twitter hashtag: #lodlamGoogle Group: firstname.lastname@example.org
More Useful References.LinkedData.orghttp://linkeddata.org/LinkedDataTools.com Introducing Linked Data and the Semantic Webhttp://www.linkeddatatools.com/semantic-web-basicsDATA.GOV.UK. What is Linked Data?http://data.gov.uk/linked-data/what-is-linked-dataAusGOALhttp://www.ausgoal.gov.au/Creative Commons Australiahttp://creativecommons.org.au/Wikipedia. Resource Description Framework.http://en.wikipedia.org/wiki/Resource_Description_Framework
Join the LODLAM movementresources and community on http://lodlam.netask for help on Google Group or #lodlam on Twitterhttp://openglam.orghttp://outreach.wikimedia.org/wiki/GLAMContribute!Start small, but START