DoRES — A Three-tier Ontology for Modelling Crises in the Digital Age

GRÉGOIRE BUREL1, LARA S. G. PICCOLO1, KENNY MEESTERS2, HARITH
ALANI1
1Knowledge Media Institute, The Open University, Milton Keynes, UK.
2Center for Integrated Emergency Management, University of Agder, Kristiansand, Norway.
ISCRAM’17, Albi, France.
21-24 May 2017.
DoRES — A Three-tier Ontology
for Modelling Crises in the
Digital Age
www.comrades-project.eu

Data Management and Processing
DoRES — A Three-tier Ontology for Modelling Crises in the Digital Age
Publications
2
When dealing with information collected from various online sources* (e.g., SM,
mapping software, etc.), it is necessary to be able to collect, represent and
process such information in order to better understand a situation.
Collect Analyse Understand Act
Gather data
from various
information
sources
Extract key
information,
verify
trustworthiness
, classify, etc.
Connect
information to
resources and
events.
Decide what to
do and
organise actors
and resources.
* We are focusing on online information sources rather than traditional information
sources.

Processes, Platforms and Models
3

4

5

Data and Processes Representation
Publications
6
Multiple models exist for representing
individual parts of the previous
collection/analysis process. However:
1. Models tend to focus on only a few
parts of the previous workflow.
2. Modelling approach tend to not take
into account the usage of existing
tools and data in their modelling
approach.
3. Not all models are open and use open
representation languages (e.g.,
RDF/OWL vs. custom data structures).
!

Data and Processes Representation
Publications
7
How can we support the collection,
process, understanding and the formal
representation of online information in
crisis situations? How can we create a
model that integrate with existing data
structures and software usage?
1. Create an open model that enable the
high level representation of the
transformation of raw information
into actionable knowledge by
representing information sources, their
analyses and high-level situations.
2. Use qualitative and structural design
for identifying requirements from
current data usage and needs and
follow an ontology design approach to
ensure that design requirements are
met.
?
!
Document
Report
Situation Event

DOcument Report Event Situation Ontology
Publications
8
DoRES: DOcument Report Event Situation Ontology
- A multilingual high-level ontology model that represents information
sources, analyses (reports), events and situations.
Modelling Approach:
1. Use qualitative and structural design (Burel, 2016) for identifying
model requirement:
- Interviews and data structures analysis.
2. Use the NeOn Methodology (Suárez-Figueroa et al, 2012) for
specifying and creating the DoRES model:
– Provides a scenario-based approach for creating ontologies.
– Definition of an Ontology Requirement Specification Document
(ORSD) .
3. Validation using Competency Questions (CQs):
– Classes/Properties mappings.

ORSD & DoRES
Publications
9
ORSD and DoRES:
- Analyse the model requirements by
creating a specification document.
- Integrate the structural and qualitative
analysis in the NeOn methodology.
Ontology Requirement Specification
Document (ORSD):
1. Purpose
2. Scope
3. Level of Formality
4. Intended Users
5. Intended Uses
6. Competency Questions
7. Glossary Terms

The Qualitative and Structural Method
Publications
Qualitative Design
Identify stakeholder needs
from interviews.
Structural Design
Analyse crisis–related
platform data structures for
identifying current data
usages.
The qualitative and structural method can be
used for identifying model needs and
requirements.
Structural Analysis: Identify needs by
analysing data structures and platforms.
– We analyse the Ushahidi platform data
structures.
– We analyse 11 different crisis-related
datasets (e.g., CrisisLex, GDELT, ACLED).
Stakeholder Interviews: Extract
requirements by performing interviews with
existing emergency communities:
– We interviewed an ICT specialist for
disaster management and 7 community
leaders.

ORSD & DoRES (2)
Publications
11
1. Purpose/ 2. Scope:
– Representation of information sources, reports, events and
situations.
3. Level of Formality:
– Flexible with loose semantics.
4. Intended Users / 5. Uses:
– Different user groups such as governmental organizations and non-
governmental groups, as well as individuals.
– Be useful in situations where users are looking for/or are willing to
provide information about crises and where responders are
organising resources in order to solve a particular situation.
6. Competency Questions / 7. Glossary Terms:
– Based on structural and qualitative analysis, we create 102 CQs.
– Extract key terms from CQs and data structures.

Competency Questions (CQs)
12

Glossary Terms
13

Publications
14
Document
– Social media posts.
– Outside data information.
– Non analysed content.
– Unknown reliability.
– Loosely formatted.
Report
– Structured analysis of documents
and information sources.
– Can be assigned to tasks
– Can be classified into categories.
– Has information source (e.g.
Document)
Event/Situation
– Formalised representation of events
and crisis situation.
– Cite reports as information sources.
– Can be used for automatic
inferencing and querying (e.g.
asking what are the building
collapsed in a given area.).
– Model relations between events (i.e.
results, involvement, induces…)
(http://socsem.open.ac.uk/ontologies/dores)
Information Knowledge

15

Ontology Integration
16
WGS841

DoRES Validation
17
Since DoRES is not integrated yet to any platform, the model is evaluated by
checking if a path exists between the properties and classes that are
present in the 102 CQs.
E.g., "What is the location of an event?”: dores:Event → dores:geolocation →
dores:Geolocation.

Summary and Conclusion
Publications
18
+ - A high-level ontology for representing
information sources, analyses (reports), events
and situations.
- A model that was validated with an exhaustive
theoretical evaluation based on 102
competency questions.
- An open ontology based on widely used
vocabularies (e.g., SIOC, FOAF, Veracity, etc.)
- No domain specific knowledge:
- Allow the representation of domain knowledge by
extending classes and properties.
- Not yet integrated in existing platforms
- Future integration with the COMRADES project tools and
platform (Ushahidi).
- Not designed primarily for non Social Media
information sources.
-
Document
Report
Situation Event

Questions
@
Email: g.burel@open.ac.uk
Twitter: @evhart
COMRADES: http://comrades-
project.eu
19

DoRES — A Three-tier Ontology for Modelling Crises in the Digital Age

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