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BiographyNet Managing Provenance at multiple levels and from different perspectives

BiographyNet Managing Provenance at multiple levels and from different perspectives. 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 Amsterdam http://wm.cs.vu.nl.

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BiographyNet Managing Provenance at multiple levels and from different perspectives

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  1. BiographyNetManaging Provenance at multiple levels and from different perspectives 21 October 2013 • Niels Ockeloen, AntskeFokkens, Serge terBraake, PiekVossen, Victor de Boer, Guus Schreiber, and Susan Legêne • The Network Institute, VU University Amsterdam • http://wm.cs.vu.nl BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  2. Overview 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  3. What is BiographyNet? BiographyNet: Extracting relations between people, places and historic events • Multidisciplinary E-HistoryProject BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  4. What is E-history? E-humanities Investigates what can be done in humanities with modern techniques which we could not do before, or only with a great deal of effort E-history • Sub domain of E-humanities which aims at improving existing methods • of historical research rather than introducing • a 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

  5. What is BiographyNet? BiographyNet: Extracting relations between people, places and historic events • Multidisciplinary E-HistoryProject BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  6. What is BiographyNet? BiographyNet: Extracting relations between people, places and historic events • Multidisciplinary E-HistoryProject • 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

  7. Short biographical descriptions with limited meta data Individuals with available information (%) BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  8. Project Goals 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  9. Use Case Overview 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? BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  10. Illustrative use case 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) BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  11. Governors General: Data Mining 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  12. Governors General: Time and effort Manual analysis “More than one full week to manually mine this information from the Biography Portal.” (Serge terBraake) The question “Can a historian do this with (almost) the same results in less than an hour when using the demonstrator?” BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  13. Text mining using Natural Language Processing (NLP) 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  14. NLP: Challenges 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 GeoNamesHeuristic: 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? BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  15. NLP: Preliminary results – Governors 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

  16. Towards the demonstrator 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  17. Requirements from the perspective of the Historian 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? BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  18. Requirements from the perspective of the Computer Scientist / Computational Linguist 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 AntskeFokkens, Marieke van Erp, Marten Postma, Ted Pedersen, PiekVossen and NunoFreire (2013) Offspring from Reproduction Problems: What Replication Failure Teaches Us. In: Proceedings of ACL 2013, Sofia, Bulgaria, August 2013. BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  19. Requirements from the perspective of the Computer Scientist / Computational Linguist 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  20. The BiographyNet Schema 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. BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  21. The conversionprocess • <XML> Very simplified BP XML Example • <BioDes> • <FileDes> Source Meta Data • <Author></Author> • </FileDes> • <PersonDes> PersonMeta Data • <Name></Name> • </PersonDes> • <BioPart> Biographical Text • <Snippet></Snippet> • <BioPart> • </BioDes> • </XML> Purely syntactic conversion • Preserve the original structure of the data • Prevent los of information • Allow for reinterpretation of the original data in the future Data Preservation BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  22. The conversionprocess 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  23. Adding Provenance Information 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  24. Provenance in BiographyNet 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 Historiani.e. per enrichment • A detailed level, i.e. all  Targeted at the Computer Scientist and individual processes  computational linguist BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  25. Recap: Why is provenance info important for BiographyNet? 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  26. 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

  27. BiographyNet Enrichment example File Meta Data NNBW “Thorbecke” Biographical Description Person Meta Data Birth Event 1798 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… Johan Rudolph Thorbecke werdin 1798 geboren op 14 januari in Zwolle en komt uit een half-Duitse… Biography Parts prov:plan Thorbecke Enrichment NLP Pipeline Biographical Description Person Meta Data Birth Event 1798-01-14 Zwolle BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  28. More than just Provenance: 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  29. Why model plans besides provenance? 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 withthe 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  30. BiographyNet: Schema illustration BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  31. Variable Variable Plan Plan Agent Person Association Agent NLP Tool Entity Activity Entity Activity

  32. Current Status 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 BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

  33. Thank you for your attentionwww.biographynet.nlFeel free to ask questions BiographyNet: Managing Provenance at multiple levels and from different perspectivesLinked Science (LISC) – ISWC 2013, Sydney, Australia – 21 October 2013

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