Ontologies and the humanities: some issues affecting the design of digital infrastructure
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Transcript of Ontologies and the humanities: some issues affecting the design of digital infrastructure
Ontologies and the HumanitiesSome Issues Affecting the Design of Digital Infrastructure
Department of Digital Humanities
Toby Burrows
Of making many ontologies, there is no end…• “A joint project … which aims to develop an ontology of
digital research methods in the arts and humanities…”• “Cette reflexion a necessite la modelisation d’une
ontologie de la transtextualite…”• “The proposed ontology for 3D visualisation for cultural
heritage…” • “Uber die Modellierung einer Ontologie
wissenschaftlicher Prozesse fur den Exzellenzcluster…”• “The model can be aligned with upper level ontologies
like the CIDOC-CRM…”
Digital Humanities 2014, Lausanne, July 2014
What is an ontology?
• “The representation of entities, ideas, and events, along with their properties and relations, according to a system of categories” (Wikipedia)
• “An ontology formally represents knowledge as a set of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts” (Wikipedia)
• “The most typical kind of ontology for the Web has a taxonomy and a set of inference rules” (Tim Berners-Lee)
Gill, Tony (2004) “Building semantic bridges between museums, libraries and archives: The CIDOC Conceptual Reference Model” First Monday vol. 9 no. 5
Why ontologies?
• Computational perspective:– Machine-processable– Support automated reasoning and logic– Enable contextual search and browse– Enable software agents to identify trusted sources and provide
service discovery• Humanities perspective:
– Semantic analysis of the contents of scholarly materials– Categorization of scholarly materials– Relating different categorization schemes to each other– Computational reasoning – faceted searching and browsing
Berners-Lee, Tim, James Hendler and Ora Lassila (2001) "The Semantic Web", Scientific American, May 2001, p. 29-37
Allen, Colin (2013) “Cross-Cutting Categorization Schemes in the Digital Humanities”, Isis, Vol. 104, No. 3, pp. 573-583
Linguistic and semantic difficulties
• Variations in terminology• Ambiguity of terminology• Historical change in language and meaning• Multilingualism – use of different languages• Interdisciplinarity – different perspectives (“cross-
domain”)• Responses within ontologies:
– Definitions of terms– Semantic context (provided by ontological structure)– Ontology mapping across domains– Ontology integration across domains– Ontology learning and modification
Alternative strategies?
• Search – use ontologies to classify search results (facets)• Topic modeling – automatic generation of semantic
categories and relations from text-based NLP• Fluid ontologies and vernacular ontologies• Linked Data with light categorization for reasoning
– Vocabularies & thesauri encoded for the Semantic Web
(SKOS)• “Folksonomies” or social tagging
Tags are applied to entities
There is no formal classification or categorization of concepts
There are no relationships between tags (other than being used to tag
the same entity)
Massive Attack Tags (last.fm)
00s 80s 90s acid jazz alternative alternative dance alternative rock ambient atmospheric beautiful bristol bristol sound british chill chill out chillout dance dark downbeat downtempo dub easy listening electro electronic electronica england english experimental favorite favorites favourite female vocalists hip hop hip-hop house hypnotic idm indie indie rock industrial instrumentaljazz lounge male vocalists massive attack mellow pop psychedelic rap relax rock sexy soul soundtrack technotrance trip hop trip-hop triphopuk
Categorizing contemporary popular music
GrungePun
k Riot grrrl
Indie
Alt-country
Seventies rock
Goth-punk
Slacker punk
“That old weird America”
Stoner rock
Rap metal
Old-school punk
Nu metal
Metal
Hard rock
Hardcore
Post-punkD-beat
Alternative rock
To explain this
_________________________________________________________________
Deeper issues for the humanities
• More than just linguistic or semantic difficulties• Debates about “the nature of things” (ontology!)• Debates about “how to represent the world”• The nature of perception and cognition
• Cognitive themes:– Similarity and dissimilarity– Relationships: metonymic and metaphorical, not just
semantic or logical– Connections and trails– Seeing things holistically
“The problem of modeling representations”“The symbolic approach starts from the assumption that
cognitive systems can be described as Turing machines.
Cognition is seen as essentially being computation, involving
symbol manipulation.” (Gärdenfors 2000:1)
“The Semantic Web is a machine for creating syllogisms”
(Shirky 2003)
“It is an unfortunate dogma of computer science in general,
and the Semantic Web in particular, that all semantic
contents are reducible to first-order logic or to set theory”
(Gärdenfors 2014:258)
Conceptual spaces
In the current Semantic Web, the information mainly concerns
taxonomies and inference rules. If conceptual spaces are used as a
foundational methodology, the focus will be on describing domain
structures. This involves, above all, specifying the geometric and
topological structure of the domains. (Gärdenfors 2014:
261)
The issue is this: Do meaningful thought and reason concern merely the
manipulation of abstract symbols and their correspondence to an
objective reality? Or do meaningful thought and reason essentially
concern the nature of the organism doing the thinking – including the
nature of its body, its interactions in its environment, its social character
and so on? (Lakoff 1987: xv-xvi)
The world as graph
The theory of graph-theoretic structure is sufficient to account for all
structure in thought or world. Minimally, it has the information-theoretic
content to describe the complexity of the apparent world, it mirrors the
“computational” difficulty we have in grasping this world, and it has the
combinatoric texture to give a theoretically satisfying account of the
nature of the world. That is, the world is of daunting size and complexity,
parts of it are difficult precisely to isolate and conceive, but it is
fundamentally made up of parts arranged in simple, graspable
arrangements.
This is an extremely speculative assertion that a graph – large graphs
anyway – have the same compositional “feel” as the world; and that the
“facts” or sentences of first-order predicate logic of logico-metaphysical
analysis do not. (Dipert 1997:351)
HuNI’s approach – socially-linked data
• Aggregate heterogeneous data to a simple data model• Keep the categorization of data entities to a minimum:
six basic categories• No imported relationships between entities• Allow users to express the relationships they see in the
data – by creating links between entities• Allow multiple relationships between the same entities
(even if they are contradictory)• The user-contributed links give meaning and add value• Users can also create and share collections of entities
PERSON A natural person
ORGANISATION A company, club, trust, gallery, political party, etc
WORK A cultural artefact or “man-made” thing created by someone, that has some existence in its own right, either physical or digital
PLACE A real, spatial location
EVENT An activity that occurs in space and time and may involve people, organisations, places, works, etc.
CONCEPT Something whose existence is primarily mental
http://wiki.huni.net.au/display/DS/Data+Model
Events
• Central to humanities perspectives on the world• “Each entity is an event” – Bruno Latour• Attempts at ontological models of events:
– Simple Event Model; LODE; The Event Ontology– Within larger models: CIDOC-CRM, Europeana,
FRBRoo– Treat events as nameable entities
• Knowledge representation of events:– CultureSampo (Finland)
• Events as conceptual spaces – Peter Gärdenfors
T. Ruotsalo, E. Hyvonen, An event-based approach for semantic metadata interoperability (2007)
In 1862, Sir Thomas Phillipps bought Phillipps MS 16402 in London as part of the Sotheby’s sale of the collection of Guglielmo Libri.
The task for DH
• Future lines of DH research: looking beyond ontologies
• Computational modeling of humanities thought: going beyond “reasoning” in the logical sense, as embedded in ontologies
• Examine alternatives from cognitive science and philosophy– Conceptual spaces: the geometry of meaning– Cognitive models– The world as a graph
Dr Toby BurrowsMarie Curie FellowDepartment of Digital HumanitiesKing’s College London26-29 Drury LaneLondon WC2B 5RL