containing the semantic explosion

Containing the Semantic Explosion

Jaimie MurdockCameron Buckner

Colin Allen

Indiana Philosophy Ontology (InPhO) ProjectIndiana University – Bloomington, IN, USA

inpho@indiana.edu

17 April 2012

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 1 / 33

Introduction

Table of Contents

1 Introduction

2 Building Ontologies

3 Dynamic Ontology

4 Future Directions

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Introduction

The Information Explosion

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Introduction

The Information Explosion

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Introduction

Guiding Principles

“Augmented intelligence”Let humans and computers each doonly what they do best

“Guided serendipity”Provide useful tools for scholars:

cross-referencing

semantic search

document classification

visualizations

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Introduction

Guiding Principles

“Augmented intelligence”Let humans and computers each doonly what they do best

“Guided serendipity”Provide useful tools for scholars:

cross-referencing

semantic search

document classification

visualizations

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 5 / 33

Introduction

What Philosophers Know

Stanford Encyclopedia ofPhilosophyhttp://plato.stanford.edu

1522 authors

127 subject editors

1315 articles since 14 Sep 1995

1 million weekly articledownloads

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Introduction

What Philosophers DON’T Know

What’s in the SEP!http://plato.stanford.edu

16.3 million words — equivalent to27,250 pages at 600 words/page

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Introduction

The Indiana Philosophy Ontology (InPhO) Project

https://inpho.cogs.indiana.edu/

Pragmatic attempt to organize the discipline of philosophy through a threestep process of:

data mining

expert verification

machine reasoning

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Introduction

The Indiana Philosophy Ontology (InPhO) Project

https://inpho.cogs.indiana.edu/

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Introduction

The Indiana Philosophy Ontology (InPhO) Project

https://inpho.cogs.indiana.edu/

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 10 / 33

Building Ontologies

Table of Contents

1 Introduction

2 Building Ontologies

3 Dynamic Ontology

4 Future Directions

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Building Ontologies

Computational Ontology

“A body of formally represented knowledge is based on aconceptualization: the objects, concepts, and other entities that arepresumed to exist in some area of interest and the relationships that holdamong them . . . A conceptualization is an abstract, simplified view of theworld that we wish to represent for some purpose . . . An ontology is anexplicit specification of a conceptualization.” — Gruber (1993)

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Building Ontologies

Domain Ontologies

GOLD: General Ontology for Linguistic Description

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Building Ontologies

Domain Ontologies

Gene Ontology

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Building Ontologies

Formal Ontology

Goals: interoperability, permanence, precision

ULOs represent the most basic, enduring features of reality — notjust a “conceptualization”

Upper-level ontologies (ULOs) unite domain-level ontologies

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Building Ontologies

Formal Ontology

Concerns

“Double experts” required

Manual design and change

Bias, controversy

Battlefield cluttered with ULOs . . .

BFO, Dolce, DnS, SUMO, Cyc, GFO, IDEAS, GOL, BWW, COSMO,OCHRE, Gist, OBO, PROTON, IFF, MSO, Sowas, . . .In civil war, population suffers most . . .

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Building Ontologies

Formal Ontology

Concerns

“Double experts” required

Manual design and change

Bias, controversy

Battlefield cluttered with ULOs . . .

BFO, Dolce, DnS, SUMO, Cyc, GFO, IDEAS, GOL, BWW, COSMO,OCHRE, Gist, OBO, PROTON, IFF, MSO, Sowas, . . .In civil war, population suffers most . . .

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Building Ontologies

Folksonomy

Can we induce an ontology from tagging behavior?

“Wisdom of the crowds”

Del.ico.us, Flickr, Wikipedia

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Building Ontologies

Folksonomy Concerns

Uncontrolled vocabularyAmbiguity, idiosyncrasy, no definitions

Tagging behavior changes over time

Unstructured or training required

The world is not flat — expertise matters!

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Building Ontologies

Formal vs. Dynamic Ontology

Formal Ontology

Large projects in business,medicine, and natural sciences

Stable consensus

Manual construction

Monolithic perspective

Dynamic Ontology

Smaller, open-access projects influid domains

Emergent consensus

Semi-automated construction

Multiple perspectives

Wish: Top-down quality for a bottom-up price!

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Building Ontologies

Formal vs. Dynamic Ontology

Formal Ontology

Large projects in business,medicine, and natural sciences

Stable consensus

Manual construction

Monolithic perspective

Dynamic Ontology

Smaller, open-access projects influid domains

Emergent consensus

Semi-automated construction

Multiple perspectives

Wish: Top-down quality for a bottom-up price!

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 19 / 33

Dynamic Ontology

Table of Contents

1 Introduction

2 Building Ontologies

3 Dynamic Ontology

4 Future Directions

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Dynamic Ontology

The Indiana Philosophy Ontology (InPhO) Project

https://inpho.cogs.indiana.edu/

Pragmatic attempt to organize the discipline of philosophy through a threestep process of:

data mining

expert verification

machine reasoning

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Dynamic Ontology

1. Data Mining

Use statistical techniques to make predictions about content

J-measure (n-grams)

Measures similarity usingco-occurrences

Entropy (TF-IDF)

Measures generality based onprevalence

Further details: Niepert et al. 2007, Murdock et al. 2012

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Dynamic Ontology

1. Data Mining

Use statistical techniques to make predictions about content

J-measure (n-grams)

Measures similarity usingco-occurrences

Entropy (TF-IDF)

Measures generality based onprevalence

Further details: Niepert et al. 2007, Murdock et al. 2012

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Dynamic Ontology

2. Expert Verification

Present hypothetical relations to users.

Allows for untrained ontologists.

Amazon Mechanical Turk

Further details: Allen et al. 2008, Niepert et al. 2009, Buckner et al. 2010, Eckart et al. 2010

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Dynamic Ontology

3. Machine Reasoning

Input – Expert feedback combined with statistical dataOutput – Populated ontology with taxonomic projection

Further details: Niepert et al. 2008

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Dynamic Ontology

Applications

Automated cross-referencing

Context-aware search

Citation management

Document classification

Visualizations

Change and controversydiscovery

“Macroscopes” (Borner)

Metaphilosophy

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Dynamic Ontology

Applications

Automated cross-referencing

Context-aware search

Citation management

Document classification

Visualizations

Change and controversydiscovery

“Macroscopes” (Borner)

Metaphilosophy

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Future Directions

Table of Contents

1 Introduction

2 Building Ontologies

3 Dynamic Ontology

4 Future Directions

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Future Directions

CodEx Workbench

Dynamic ontology toolkit for arbitrary corpora

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Future Directions

CodEx Workbench

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Future Directions

CodEx Workbench

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Future Directions

CodEx Workbench

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Future Directions

Guiding Principles

“Augmented intelligence”Let humans and computers each doonly what they do best.

“Guided serendipity”Provide useful tools for scholars:

cross-referencing

semantic search

document classification

visualizations

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 31 / 33

Future Directions

Guiding Principles

“Augmented intelligence”Let humans and computers each doonly what they do best.

“Guided serendipity”Provide useful tools for scholars:

cross-referencing

semantic search

document classification

visualizations

Murdock, Buckner, Allen (IU) Containing the Semantic Explosion 17 April 2012 31 / 33

Future Directions

Acknowledgements

IUB New Frontiers in the Humanities

NEH Digital Humanities Initiative

NEH-DFG Bilateral Digital Humanities Program

Digging into Data Challenge

Alexander von Humboldt Foundation

Views expressed are the authors, and not necessarily the views of any funding angencies

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Future Directions

Acknowledgements

Project Director

Colin Allen

Project Founders

Cameron Buckner, Mathias Niepert

Graduate Students

Jaimie Murdock, Robert Rose

Former Staff

Evan Boggs, Tarun Gangwani, ScottWeingart

Project Staff

Alex Frost, Wesley Pettyjohn, SamWaggoner

CogSci Support

Ruth Eberle, Nubli Kasa

Application Consultants

Ed Zalta & Uri Nodelman (SEP),Tony Beavers (Noesis)

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