dh101 2013/2014 course 6 - semantic coding, rdf, cidoc-crm

Digital Humanities 101 - 2013/2014 - Course 6

Digital Humanities Laboratory

Frederic Kaplan

[email protected]

Semester 1 : Content of each course

• (1) 19.09 Introduction to the course / Live Tweeting and Collective note

taking

• (2) 25.09 Introduction to Digital Humanities / Wordpress / First assignment

• (3) 2.10 Introduction to the Venice Time Machine project / Zotero

•9.10 No course

• (4) 16.10 Digitization techniques / Deadline first assignment

• (5) 23.10 Datafication / Presentation of projects

• (6) 30.10 Semantic modelling / RDF / Deadline peer-reviewing of first

assignment

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Digital Humanities 101 - 2013/2014 - Course 6 | 2013 2o

Semester 1 : Content of each course

• (7) 6.11 Pattern recognition / OCR / Semantic disambiguation

• (8) 13.11 Historical Geographical Information Systems, Procedural modelling

/ City Engine / Deadline Project selection

• (9) 20.11 Crowdsourcing / Wikipedia / OpenStreetMap

• (10) 27.11 Cultural heritage interfaces and visualisation / Museographic

experiences

•4.12 Group work on the projects

•11.12 Oral exam / Presentation of projects / Deadline Project blog

•18.12 Oral exam / Presentation of projects

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Objective of today’s course

•Showing you the beauty and making you feel the power of semantic coding

•Give you a quick idea about what is behind the following strange acronyms :

RDF, URI, OWL, SPARQL, SWRL, CIDOC-CRM

•Motivate you to look deeper.

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A short introduction to semantic coding

•Many good books exist. I recommend

this one.

• I will reuse some of their example in the

following slides.

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Doris Stockly

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incanti.dhlab.ch

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The simplest kind of dataset, that everyone is familiarwith, is tabular data (any data kept in a table such as anExcel spreadsheet).

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Data kept in table is easy to display, sort, print, edit.

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You might not even think of data in an Excel spreadsheetas modeled. But there are semantics in data table.Where ?

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There are also obvious limitations with this kind ofstorage.

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You cannot search for the routes that stay more than 2days at Corfu. Sorting the columns does not capture thedeeper meaning of the text we entered.

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Relational databases are a solution. Many very matureproducts exist like Oracle DB, MySQL and PostgreSQL. Arelational database allows multiple tables to be joined in astandardized way.

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But, as our project goes we may need to reformate ourtables.This is called schema migration. A painful process.

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For big databases, schema can get incredibly complex.

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Trying to normalize these databases in a single schema isa labor-intensive process.

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How tomake future-proof schemata

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How tomake future-proof schemata

•With this mode of coding we can add easily new properties (price of

Route, captain, etc.). The schema is future-proof.

• In addition, the data about the data (i.e. the medadata, the name of

columns) is now part of the data itself.

•This is ideal for projects in Perpetual Beta.

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and most important it makes a direct and simpleconnection with a well-developed research field : logic.

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Indeed, this can bewritten in a different way

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Indeed, this can bewritten in a different way

• (Subject Predicate Object)• (R1 departure Venice)

•This is called a RDF statement, an atomic relation in a database

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RDF statements

• (Subject Predicate Object)• (R1 departure Venice)

•This is called a RDF statement, an atomic relation in a database

• (R1 departure-date 2.7.1422)

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This is a graph

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As RDF statements can be understood both a logicstatements and as parts of a graph, one can use manytools and idea from logic and graph theory to manipulatethem.

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URIs

•The nodes of the Graph are called Resources.

•When you want to coordinate multiple datasets it can become

increasingly difficult to guarantee unique and consistent identifiers fore

ach node.

•R1 that we use in our database may mean something else in an other

database.

•For naming resources, RDF uses URIs (Unique Resource Identifiers) and

an optional Fragment identifier.

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URIs

•You are probably familiar with URL (Universal Resource Locators), the

string used to specify how web pages are retrieved.

•URIs generalize this concept further by saying that anything, whether you

can retrieve it electronically or not, can be uniquely identified in a similar

way.

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URIs

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Since URIs can identified anything as a resource, thesubject of an RDF statement can be a resource, the objectcan be a resource and most importantly predicates arealways resources.

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An example of URI Ref for a common RDF predicate

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It is common in RDF to shorten URIs by assigning anamespace to the base URI and writing only thedistinctive part of the identifier. The last URIs can bewritten in a shorter manner : rdf:type

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rdf:type

Serialization

•While the data model that RFD uses is very simple, the serialized

representation tends to get complicated when a RDF graph is saved in a

file or sent over a network.

•Different serialization formats exist :, N3, RDF/XML(the most freq.

used), RDFa (RDF in attributes)

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Vocabularies

•A set of URIRefs is known as a vocabulary.

•We can design a specific vocabulary for our maritime route examples.

•There are also famous vocabularies like the RDF vocabulary (the set of

URIRefs describing the RDF concepts, ex. rdf :resource, rdf :type)

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SPARQL

•Just as SQL provides a standard query language across relational

databases, SPARQL provides a query language for RDF graphs.

(pronounce sparkle)

•SPARQL queries attempt to match patterns in the graph and bind

wildcard variables as its finds solutions.

•Departure( ?x1,Venice)

•Captain( ?x1, ?x2), Gender( ?x2,Women)

•Semantic coding is all about asking bigger questions.

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SWRL

•With RDF coding, we can also write rules to infer new triples

• If hasParent( ?x1, ?x2) and hasBrother( ?x2, ?x3) then hasUncle( ?x1, ?x3)

•This is also a way of detecting possible incoherence in the set of

knowledge coded in the triple store (actors doing things after their death)

•One standard language to do this is SWRL (Semantic Web Rule

Language)

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Ontologies

•An ontology provides a special vocabulary with which knowledge can be

represented.

•This vocabulary allows us to specify which entities will be represented,

how they can be grouped and what relationship connect them together.

• (Venice isa Place), (Corfu isa Place), (Place haslat latitude), (Place

haslong longitude)

•Now, something very beautiful...

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An ontology can be expressed as RDF triples and storedin a graph alongside the data it describes.

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OWL

•OWL (Web Ontology Language) is an ontology language layered on top

of RDF and RDFs

•Terminology statements

• ex:Bridge rdf:type rdfs:class

• ex:Bridge rdfs:subclass ex:Place

•Assertion statements

• ex:Rialto rdf:type ex:Bridge

• ex:ex:RialtoCons ex:broughtIntoExistence ex:Rialto

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ex:Bridge

rdf:type

rdfs:class

ex:Bridge

rdfs:subclass

ex:Place

ex:Rialto

rdf:type

ex:Bridge

ex:ex:RialtoCons

ex:broughtIntoExistence

ex:Rialto

It is relatively easy to create your own ontology using asoftware like Protégé. But some ontologies aim at beinguniversal

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CIDOC-CRM

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CIDOC-CRM

•CIDOC-CRM is an ontology for Cultural heritage.

•About 20 years of work.

•An ISO standard 21127.

•100+ schema. Very stable.

•CIDOC-CRM is a tentative to formalise an underlying semantics common

to many classifications. It includes very interesting ideas.

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CIDOC-CRM : Events

• In CIDOC-CRM, the modelling is event-centric.

•The underlying idea is to model change, not state. Therefore, temporal

entities play a central role.

• Instead of coding the birthdate of a actor, it is better to code the event

of its birth.

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Actors relate to things only via temporal entities and events.

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CIDOC-CRM : Events

•The participation or presence of several non-temporal entities in an event

e1 allows to conclude that they have been in the same time-interval and

space, even without knowledge of the particular time or space.

•They must have existed at that time. They have not been somewhere

else at that time (with electronic communication, the space volume in

which events occur can become very large).

•The events e0i of creation of each participant i have happened before or

at the time of e1. The events e2i of destruction (or vanishing) of each

participant have happened after or at the time of e1.

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CIDOC-CRM : Properties

•The property P11 had participants denotes active or passive involvement

of Actors, whereas P12 occurred in the presence of ranges from objects

just being there (e.g. a desk where a treaty was signed)

•The properties P92 brought into existence, P93 took out of existence are

limiting the existence of things which have a persistent existence.

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CIDOC-CRM : Place

•CIDOC-CRM has also implemented a very interesting model for places.

What is hard about places ?

•The question where is it can be answered in natural language by relation

to two different kinds of entities : geometric areas or objects.

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In France, in Athens, 39N 124E. Points given by spatialcoordinates are typically understood as the centre of awider, extended area.

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on mount St Helens, at the Rhine river.

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on Queen Elizabeth (the ship), in my suitcase, at home.

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CIDOC-CRM : Place

•Following the CIDOC CRM, geometric areas (E53 Place) can only be

defined relative to larger objects, including the surface of earth.

•Those objects in turn may be located at different times at different places

(relative to a larger object).

•The cultural interest is in the relation to other things and not to an

abstract absolute space. Absolute coordinates seem to make no sense

when the reference objects move.

•As historical information is incomplete and sparse, and many reference

objects move, normalization of place information to absolute coordinates

should not replace the primary information, which is typically relative.

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CIDOC-CRM : Places

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CIDOC-CRM : Influence

•Another problematic issue is the notion of influence. It is difficult to

develop a systematic understanding of the different forms of influence

and their mutual relations

•Some are more physical, like using a mould or a tool. The influence of a

mould on a produced object is strong and can often be verified on the

object afterwards. The influence of a hammer is less specific.

•Similarly, making a copy of a painting has a strong influence on the

product, copying the idea of a painting, a weak one. The latter is more

an intellectual influence than a physical one.

• If a real influence existed, a temporal sequence can be deduced.

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CIDOC-CRM

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Summary : Guidelines for coding historical data

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(1) Prefer events to properties. Actors do not haveproperties, they participate to event. Instead of coding thebirthdate of a actor, it is better to code the event of itsbirth.

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(2) Code date intervals instead of dates. This is muchmore flexible and permits to detect inconsistencies.

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(3) Code places in a relative manner and not an absolutemanner. The cultural interest is in the relation to otherthings and not to an abstract absolute space. Absolutecoordinates seem to make no sense when the referenceobjects move.

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All this is very beautifut, but is it sufficient to do the kindof historical modeling we want to do ? We have an issue,which one ?

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Metaknowledge : Knowledge about how knowledge isproduced.

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How canwe encodemetaknowledge

•Expressed knowledge (RDF triples) is not in the same space as resources

(URI). We can easily attach new information to resource but not to

triples.

• It is not easy to represent metaknowledge like the origin of the

uncertainty linked with an information.

•To overcome this issue we need to introduce two levels of knowledge and

use a trick.

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Reifued RDF vs. Standard RDF

•An expressed RDF (RialtoReconstruction hasTimeSpan 1588-1591) can

be transformed in 3 reified triplets

• (s1 rdf:subject RialtoReconstruction)

• (s1 rdf:predicate hasTimeSpan)

• (s1 rdf:object 1588-1591)

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rdf:subject

rdf:predicate

rdf:object

Reifued RDF vs. Standard RDF

•An expressed RDF (RialtoReconstruction hasTimeSpan 1588-1591) can

be transformed in 3 reified triplets

• (s1 rdf:subject RialtoReconstruction)

• (s1 rdf:predicate hasTimeSpan)

• (s1 rdf:object 1588-1591)

• (s1 metardf:reliability 0.8)

• (s1 metardf:creator FredericKaplan)

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rdf:subject

rdf:predicate

rdf:object

metardf:reliability

metardf:creator

Possible historical spaces

•Now our RDF store includes both historical knowledge and knowledge

about the creation of this historical knowledge.

•These kinds of metainformation can document all the construction

phases (whether realized by humans or machines)

•With this approach, we can extract through queries the historical

knowledge corresponding to some specific sources and thus create a

possible historical reality.

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Summary

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Encodingmetahistorical information

•We must not only model historical information, but model each step of

the construction of historical knowledge.

•There is a need for semantic framework capable of coding historical

information and meta-historical information.

•Coding meta-historical information implies documenting the choice of

sources, transcription phases, interpretation processes realized by humans

or machines.

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No unique global truth but fully documented possiblehistorical reconstructions

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dh101 2013/2014 course 6 - semantic coding, rdf, cidoc-crm

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