SEA: A Framework for Interactive Querying, Visualisation and Statistical Analysis of Linked...

CAA 2011 Beijing

SEA: A Framework for Interactive Querying,Visualisation and Statistical Analysis of Linked

Archaeological Datasets

Monika [email protected]

Department of Computer ScienceJoint work with

Yi HongDepartment of Computer Science

Katharina Rebay-SalisburySchool of Archaeology and Ancient History

University of Leicester, UK

April 14, 2011Monika Solanki

Talk outline CAA 2011 Beijing

Outline

Context: Tracing Networks

Motivation

Case study

Semantic Explorer forArchaeology

Conclusions and Future work

Demo

Monika Solanki

Context CAA 2011 Beijing

Tracing Networks

Investigates the network of contacts across and beyondthe Mediterranean region, between the late bronze ageand the late classical period (c.1500-c.200 BCE) byinterrogating material objects

Seven archaeological case studies fully integrated withcomputer science projects

http://www.tracingnetworks.org/

Monika Solanki

http://www.tracingnetworks.org/


Tracing Networks

Monika Solanki


Tracing Networks

Archaeologists study a wide range of material objects.

By tracking them at every stage of their production,distribution, use, and consumption across a largegeographical region, over a long time period, they cantrace the links between the people who made, used, andtaught others to make them.

The Chaîne opératoire

Cross-craft interaction

Monika Solanki

Motivation CAA 2011 Beijing

Motivation: Archaeological perspective

Key Barriers to adopting Semantic Web technologiesThe most time-consuming part of an archaeologicalinvestigation is the post-excavation analysis.

There is a lack of tools and platforms that provide anintegrated environment for interactive querying,visualisation and statistical analysis

Traditional search and retrieval mechanisms generallyprovided “Google” style keyword search or “Library” styledrop down search.

They assume knowledge of controlled vocabularies,terminology and structure of the underlying ontologicalschemas.

Monika Solanki


Motivation: Computer Science perspective

To increase the uptake and usage of semantically richarchaeological data, it needs to be openly available andaccessible by humans and applications.

An integrated view of diverse data sources is innovativeand of immense potential value for the archaeologicalcommunity.

There is therefore a mileage in combining the task ofarchiving, querying and analysing the data within a singleframework.

Archaeological data is fragmentary. Inferencing capabilitiesof reasoners can be used to extract implicit knowledge andcontribute to their existing knowledge bases to completethe fragments.

Monika Solanki


Case study: Human representations

Human representations, identities and social relations in theLate Bronze and Iron Age of Central Europe

The scope: examining and analysing humanrepresentations on a range of object types and in a rangeof materials, such as bronze and pottery.

The project utilises details such as gestures and postures,dress and associated objects as keys to understandinghow identity and new understandings of society arecommunicated.

Raw data is collected through examining objects frompublished literature or in museum collections.

Monika Solanki


Human representations

The analysis generates a large volume of data

Along with details of the human representation on objects,the data recorded also includes images of these objects.

We have developed a vocabulary that defines variousconcepts and relationships of interest in the domain ofhuman representation as captured in these images.

Using the ontology we generated linked datasets from theraw data.

We are currently linking to DBpedia and Geonames,however we are also on the lookout for datasets closelyrelated to archaeology with which we can link in the future.

Monika Solanki


Human representations: Informal queries

Example 1:

“Find images of riders who appear on objects found in Austriawhere the altitude of the excavation site is 500 meters abovesea level. I would also like to know the statistical distribution ofthe material and the technologies used for the production ofthese objects. I would like to visualise the results as a pie chartand see the distribution of the sites where these objects werefound on Google Earth”.

Monika Solanki


Human representations: Informal queries

Example 2:

“Find all objects which have images of individuals in the orantgesture who are wearing a triangular dress, earrings and whocarry a vessel on their head, where the vessel is supported bytheir left hand. I would also like to know the statisticaldistribution of the gender of these individuals according to thecountry in which the objects were found. I would like tovisualise the results as a tree map and see the distribution ofthe sites where these objects were found on Google Map”.

Monika Solanki

SEA: Semantic Explorer for Archaeology CAA 2011 Beijing

Semantic Explorer for Archaeology

A web application

RESTful APIs for programmatically accessing the TN-LODcloud

Interactive and global querying of linked datasets

Data visualisations using user defined perspectives

Statistical analysis using bespoke criteria provided byarchaeologists at runtime

Monika Solanki


SEA: Architecture

Monika Solanki


SEA: Query Component

Query builder, a SPARQL/SQWRL endpoint and an inferenceengine

Aggregates the input data as RDFtriples

Generates several sub queries eachof which correspond to a specifictask

Formalises the query in SPARQL,includes any constraints

Provides an interface through whichthe SPARQL query generated byaggregating the triples can be edited

Monika Solanki




Queries can be specified intuitively

Utilises the WordNet dictionary

“Natural Language QuerySummariser”

Records user preferences: statisticalanalysis, visualisation

Monika Solanki


Building the query using SEA

Monika Solanki


Human Representation

“Find images of riders who appear on objects found in Austria wherethe altitude of the excavation site is 500 meters above sea level. Iwould also like to know the statistical distribution of the material andthe technologies used for the production of these objects. I would liketo visualise the results as a pie chart and see the distribution of thesites where these objects were found on Google Earth”.

Part 1Find images of riders who appear on objects found in Austria wherethe altitude of the excavation site is 500 meters above sea level.

Part 2I would also like to know the statistical distribution of the material andthe technologies used for the production of these objects.

Monika Solanki

Sub query Part 1

PREFIX tnh:<http://www.tracingnetworks.ac.uk/ontology/human_representation.owl#>

PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>SELECT ?individual ?object ?site ?country ?abbr ?type

?tech ?image ?altitude ?materialWHERE{

?individual rdf:type tnh:Individual.?individual tnh:appearOn ?object.?object tnh:isFoundAtSite ?site.?site tnh:isLocatedInCountry ?country.?country tnh:hasCountryAbbr ?abbr.?object tnh:has1stObjectType thn:rider.?object tnh:hasImageLink ?image.?site tnh:hasAltitude ?altitude.FILTER (?altitude>=500).FILTER (?abbr="AT").}LIMIT 3000




Includes an option to specify anyreasoning rules.

A rule-based inferencing componentspecified to support deductivereasoning.

SWRL or Jena inferencing rulesused to derive implicit statementsfrom existing archaeologicalknowledge bases

Monika Solanki


SEA: Visualiser Component

Three visualisation modules.Queries generated by the user

Convert the SPARQL triple patterns to GraphMLThe visualiser is interactive and allows a user toexpand/collapse nodes in the graph.Search for a specific node in the graph.

Query Results: linked data, markers on the GoogleEarth/Google maps.

Statistical analysis: commonly used statistical analysismodels.

Monika Solanki


Visualising the query

Monika Solanki


Visualising the query results: Google earth

Monika Solanki


Visualising the query results

Monika Solanki


SEA: RESTful API

The SEA REST API corresponds to a set of servicessimply accessible through HTTP calls.

The SEA API employs content negotiation to decidewhether the result should be encoded in RDF/XML(default), JSON or plain text.

We have been inspired by the linked data APIs publishedby the data.gov.uk.

The APIs do not provide support for PUT/POST request.They are meant to provide a read only access layer to thedata repositories.

The SEA API layer can also act as a proxy over a SPARQLendpoint. This allows a user to specify a sparql query as aquery parameter.

Monika Solanki

Related work CAA 2011 Beijing

Closely related work

D2RQ: Berlin

Virtuoso: Open Link Software

STAR: Glamorgan, English Heritage

STELLAR: Glamorgan, English Heritage

TRANSLATION: Southampton

Monika Solanki

Related work CAA 2011 Beijing

Grand vision: The TN-LOD cloud

Tracing Networks through Linked Open Data

Monika Solanki

Conclusions CAA 2011 Beijing

Conclusions

Little work has been done so far in the Semantic webcommunity that can motivate archaeologists to adopt theirtechnologies to manage and analysis data.

An exploratory attempt to reconstruct the Chaîneopératoire using the principles of linked open data.

A transformation framework for migrating large volumes ofarchaeological data stored in RDBs to ontology based datasets on the Semantic Web.

SEA: A unified framework that allows archaeologists withbasic knowledge of Semantic Web technologies to“explore” their datasets through interactive querying,visualisation and analysis.

Monika Solanki

Future work CAA 2011 Beijing

Future work

Implement a user-friendly graphical modeling environmentfor the language in GMF (Graphical Modeling Framework)to allow easy creation and editing of transformation rules.

Extend the query interface so that it allows archaeologiststo specify ranking heuristics for the search results.

Extend the visualisation interface by providing a facetedbrowser that allows the archaeologist to visualise queryresults along several facets.

Augment the support provided for inference making.

Keeping a close eye on the linked data cloud for anyrelevant archaeological datasets that may eventually bepublished so that we can link to it.

Monika Solanki

Acknowledgements CAA 2011 Beijing

Acknowledgements

Computer ScienceProf Jose Fiadeiro

Yi Hong

ArchaeologyProf Lin Foxhall

Katharina Rebay-Salisbury

Monika Solanki

CAA 2011 Beijing

Many Thanks!!!

Monika Solanki

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