BiographyNet Managing Provenance at multiple levels and from different perspectives
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Transcript of BiographyNet Managing Provenance at multiple levels and from different perspectives
BiographyNetManaging Provenance at multiple levels
and from different perspectives
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
21 October 2013
Niels Ockeloen, Antske Fokkens, Serge ter Braake, Piek Vossen, Victor de Boer, Guus Schreiber, and Susan Legêne
The Network Institute, VU University Amsterdamhttp://wm.cs.vu.nl
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Overview of this presentation• Introduction of the project• Short overview of use cases• Illustrative use case example
• Why provenance is important• Requirements from the perspective of the Historian• Requirements from the perspective of the Computer scientist
• The BiographyNet schema• Foundations• Extending the schema with Provenance• Aggregated provenance information• Detailed provenance information
Overview
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Extracting relations between people, places and historic events•Multidisciplinary E-History Project
What is BiographyNet?
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
E-humanities Investigates what can be done in humanities with moderntechniques which we could not do before, or only with agreat deal of effort
What is E-history?
E-historySub domain of E-humanities which aims at improving existing methodsof historical research rather than introducinga whole new way of doing historical research *
* Zaagsma, G.: Doing history in the digital age: history as a hybrid practice (2013)
http://gerbenzaagsma.org/blog/16-03-2013/doing-history-digital-age-history-hybrid-practice
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Extracting relations between people, places and historic events•Multidisciplinary E-History Project
What is BiographyNet?
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Extracting relations between people, places and historic events•Multidisciplinary E-History Project
What is BiographyNet?
• Funded by the Netherlands eScience Center• Partners are the Netherlands eScience Center, the Huygens/ING
Institute of the Royal Dutch Academy of Sciences and VU University Amsterdam
• Starting Point: The Biographical Portal of the Netherlands http://www.biografischportaal.nl• 125,000 short biographical descriptions with limited meta data
from a variety of Dutch biographical dictionaries• 76,000 individuals
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Short biographical descriptions with limited meta data
Name
Category
Gender
Date of Death
Date of Birth
Place of Birth
Place of Death
Occupation
Religion
Father
Mother
Claim to Fame
Partner
Text
0 20 40 60 80 100 120
percentage
Individuals with available information (%)
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Main project goals • Provide a richer historic knowledge base by creating a semantic layer on
top of the data from the Biographical Portal• Convert the available data to RDF (first conversion available)• Enrichments (NLP) and Aggregations• Link to other sources
• Inspire Historians in setting up new research projects by providing them with interesting leads• Development of a demonstrator• Quantitative analysis, visualisation and browsing techniques
• Re-usable deliverables• Open-source release of the platform for analyzing texts about people• Methodology for extraction of a relation network between people, places and
events
Project Goals
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Currently 12 use cases developed involving quantitative analysis, relation discovery, thematic research, etc. • Simple:• Group analysis of Governors-general
of the Dutch Indies•More complex:• When did Dutch elites get involved
with the ‘New World’?• Highly complex:• What can we say about nationalism in biographical
dictionaries from the nineteenth and twentieth century?
Use Case Overview
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Governors-General of the Dutch Indies• Highest Official in the Dutch Indies (1610-1949)• 129 Biographies describing 71 individuals
•What can we say about these men as a group?•What properties did they need to have to be appointed?• Personal qualities• Relations (already
more difficult)
Illustrative use case
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Focus on the following information• Family connections
• Parents• Partner• Children
• Dates• Birth• Appointment• Death
• Motivation• Education• Religion• Reasons for appointment• Reasons for leaving the office
Governors General: Data Mining
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Manual analysis“More than one full week to manually mine this information
from the Biography Portal.” (Serge ter Braake)
The question“Can a historian do this with (almost) the same results in
less than an hour when using the demonstrator?”
Governors General: Time and effort
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Basic System for data enrichment using text:• Identifying meta data in text• Linguistically naïve supervised machine learning
• Linguistic processing• Detection of (co-referenced) named-entities
(persons, places and dates) and events• Concept identification
Text mining using Natural Language Processing (NLP)
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Challenges for NLP within BiographyNet:• Deal with alternative spelling• Texts vary from 19th century Dutch to contemporary Dutch• Variations in the naming of people and places
• OCR-ed texts contain errors• Used methods may introduce bias:• Example: Location identification with GeoNames
Heuristic: On multiple possibilities, take the one in, or closest to The Netherlands
• Problem: ‘America’ is a place in The Netherlands, but what about trade with the new world?
NLP: Challenges
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
NLP: Preliminary results – Governors
mariage
multiple mari
age
partners
Children
(number)
Children
(nam
es)
Age (st
art fu
nction)
Place o
f Birt
h
Place o
f Deat
h
Studies
Previous c
arree
r
Reason jo
b end
Last jo
b
Family
connecti
ons
Religio
n0
10
20
30
40
50
60
70
80
90
100
metadatatext
Presence of information in text vs. meta data (% on 71 individuals)
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Before development of the actual demonstrator can commence, we first need to:• Convert the data of the Biography Portal to RDF• Prevent loss of information
• Devise a schema • Structure the data• Provide compatibility with other interesting sources• Facilitate the recording of provenance information on the
manipulation of the data
Towards the demonstrator
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Two main requirements for the demonstrator:• A trace back to all original sources (texts and meta data)
involved in producing a certain result• Which sources were used for the overall outcome and how often?• What potentially relevant data was excluded from the end result?• Which piece of data led to a specific result (e.g. the age of a
specific governor at his appointment)?• Insight in the processes manipulating and selecting the data• Indication of overall performance: Focus on recall or precision?• Global description of the used heuristics should be provided• Indication of responsibility: Who to contact when results are
pulled into question?
Requirements from the perspective of the Historian
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Reproducing results:• Reproducing results in NLP is non-trivial• Details in implementations or experimental setup can influence
results up to a point where they tell a different story• Clear registration of all steps involved and storage of
intermediate system output can improve reproducibility• Systematic testing can help to gain insight into the variation of
the outcome of our systems and hence lead to more insight in their performance
Antske Fokkens, Marieke van Erp, Marten Postma, Ted Pedersen, Piek Vossen and Nuno Freire (2013) Offspring from Reproduction Problems: What Replication Failure Teaches Us. In: Proceedings of ACL 2013, Sofia, Bulgaria, August 2013.
Requirements from the perspective of the Computer Scientist / Computational Linguist
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Translation into requirements for the demonstrator:• Facilitate Replication and Reproduction• Recording of information on used tools such as Creator, version
number, etc.• Recording of any kind of pre- / post-processing done on
input/output data.• Recording of the intention behind the various steps in the NLP
pipeline, including made assumptions and possible biases.• Intermediate results need to be preserved for debugging purposes
• The schema needs to be both generic and flexible• NLP pipeline design can change• Tools and their formats unclear towards the future
Requirements from the perspective of the Computer Scientist / Computational Linguist
Foundations of the schema: • Based on the structure of the original XML files• Needs to facilitate the coupling of different biographies of the same
person, without compromising the original data• Needs to facilitate the incorporation of several enrichments, following
from NLP, as well as aggregations• Compatible with existing
schemas such as the Europeana Data Model,PROV, P-PLAN, DC terms, etc.
The BiographyNet Schema
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Purely syntactic conversion• Preserve the original
structure of the data• Prevent los of information• Allow for reinterpretation of
the original data in the future
The conversion process
Data Preservation
<XML> Very simplified BP XML Example <BioDes>
<FileDes> Source Meta Data <Author></Author> </FileDes>
<PersonDes> Person Meta Data <Name></Name> </PersonDes>
<BioPart> Biographical Text <Snippet></Snippet> <BioPart>
</BioDes></XML>
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Conversion steps: • Retrieval of XML dump of the Biography Portal• Initial conversion to ‘crude’ RDF• Using ClioPatria and the XMLRDF
tool for ClioPatria• RDF restructuring• Correction of purely syntactic
inefficiencies in the data• TODO: Linking to other sources• Essential step in the
‘Linked Data’ philosophy
The conversion process
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Provenance information is information on how Entities come into existence
• What are entities?• Documents, Articles, Pictures, etc.• Basically anything that can be
‘produced’ by something or someone• What kind of information?• Who did what?• Using which entities?• In which processes?
• Why use the PROV-DM, i.e. PROV-O?• PROV-DM now an official W3C recommendation
Adding Provenance Information
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Based on the requirements for the demonstrator, provenance needs to be modeled:
• From several perspectives:• Information involved Sources, but also: NER input data, etc.• Processes involved All steps in enrichment, aggregation, etc • People involved Who was responsible for pipeline, tool, etc.
• At multiple levels:• An aggregated level, Targeted at the Historian
i.e. per enrichment• A detailed level, i.e. all Targeted at the Computer Scientist and
individual processes computational linguist
Provenance in BiographyNet
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Needed to ensure credibility of the demonstrator, to evaluate its performance and to improve the academic status of the tool
• One needs to be able to validate results• Replication: Retrieving the same results later using the demonstrator• Reproducibility: Manually by the historian
• The aggregated level – Targeted at the historian• Which original sources where involved?• Who to contact in case results are pulled into question?
• The detailed level – Targeted at the computer scientist• Detailed information on each individual step• Allows for debugging the internal processing pipeline
Recap: Why is provenance info important for BiographyNet?
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Schema illustration
http://www.biographynet.nl/schema
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Johan Rudolph Thorbecke werdin 1798 geboren op 14 januari in Zwolle en komt uit een half-Duitse…
Johan Rudolph Thorbecke werdin 1798 geboren op 14 januari in Zwolle en komt uit een half-Duitse…
BiographyNetEnrichment example
Thorbecke
Biographical Description
FileMeta Data
NNBW
PersonMeta Data
“Thorbecke”
BiographyParts
Birth1798Event
Biographical Description
Enrichment NLP Pipeline
PersonMeta Data
EventBirth
Johan Rudolph Thorbecke werdin 1798 geboren op 14 januari in Zwolle en komt uit een half-Duitse…
Zwolle1798-01-14
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
prov:plan
Provenance and Plans (P-PLAN):* Represent the plans that guided the execution of scientific processes
• ‘Plans’ describe the original idea behind an activity• Each ‘Plan’ can consist of one or more ‘Steps’• Each ‘Step’ corresponds to an ‘Activity’
• ‘Variables’ describe the input/output of an activity• Structure, format, quantity, etc.• Each ‘Variable’ corresponds with an input/output ‘Entity’ of an
‘Activity’• ‘Plans’ have their own provenance info• E.g. who was responsible for the creation of a plan?
*Daniel Garijo, Yolanda Gil; http://www.opmw.org/model/p-plan
More than just Provenance:
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
P-PLAN is used to not only model what actually happened, but also what was supposed to happen• Forces the recording of what an activity and its
input/output should look like• Provides abstract description of original idea behind activity• As such, can provide info on heuristics and assumptions
• Allows for comparing the actual activity and its input/output with the original plan and its variables• Do they differ from each other and to what extend?• Makes finding errors much easier, as more information is
available about what the input/output should look like
Why model plans besides provenance?
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Schema illustration
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Activity
Plan
EntityEntity
Variable Variable
Agent
Agent
Association
Activity
Plan
Person
NLP Tool
Main components of the demonstrator• Initial schema available• Schema models enrichments and aggregations alongside original
sources • Allows for storing various levels of provenance information• Model will be adapted while progressing with building the demonstrator
• Initial conversion to RDF available• Structure according to devised schema• Next step is linking to external sources
• Initial NLP system setup available• Interface• First ideas and sketches
Current Status
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013
Thank you for your attention
www.biographynet.nl
Feel free to ask questions