This document discusses an approach to exploring large heterogeneous document collections using ontology-based data access. It describes indexing facts from raw data and metadata into Accumulo and using an ontology to allow complex queries. The approach converts documents into enriched documents with structured and unstructured fields, converts them to RDF triples, and stores them in a graph database using Rya and GraphBLAS. It explains how conjunctive queries can be executed over the graph database and how existential rules can infer new facts.

1. ComputableFacts
Cyrille SAVELIEF – csavelief@mncc.fr
Accumulo Summit 2018
MNCC 1

2. The Constraints
Security
Data Engineering
Knowledge
Engineering
2

3. The Problem
How do you explore large and heterogeneous
document collections?
• For example, in the analysis of an NGO dataset one may
be interested in the following two questions:
• In which regions of the world do the reports mention the word
“refugee” more often?
• What kind of events do the reports refer to when they talk about
“refugee”?
3

4. Shortcoming of Keywords Search
4
Keywords
selection
is hard!
False
positives
False
negatives

5. Our Approach :
Ontology Based Data Access
5
Index Facts
Raw DataMetadata
Accumulo
OntologyQUERY

6. Not a simple search engine!
6

7. Tag names, concepts or key phrases and
produce NER training data in record time!
7

8. Complex queries made easy!
8

9. The Collection &
Integration Processes
9

10. Data Collection
10

11. Data Integration
11

12. Data Model
12

13. Enriched
Document
• Structured fields
• Unstructured text fields
• Structured text fields
13

14. Enriched
Document
• Structured fields
• Unstructured text fields
• Structured text fields
14

15. Enriched
Document
• Structured fields
• Unstructured text fields
• Structured text fields
15

16. Convert JSON to RDF triples
16
Predicate ObjectSubject

17. Data Model = Rya + GraphBLAS
17
Table
Stored Triple
D4M Equivalent
RowId CF CQ
PSO person|32490c02-614d-… Ø Frédéric Colin Ø
SOP 32490c02-614d-… Ø Frédéric Colin|person Edge
OPS Frédéric Colin|person Ø 32490c02-614d-… EdgeTranspose
OPD Frédéric Colin|person Ø Ø EdgeTransposeDegree
Text 32490c02-614d-… Ø Ø EdgeText
https://rya.apache.org http://graphblas.org

18. Patterns to Table Scans
Pattern Table to Scan
(S, P, O) Any Table
(S, P, *) PSO
(S, *, O) SOP
(*, P, O) OPS
(S, *, *) SOP
(*, P, *) PSO
(*, *, O) OPS
(*, *, *) Full Table Scan
• Any pattern can be translated
into a scan of one of these 3
tables:
• PSO = (Predicate, Subject, Object)
• SOP = (Subject, Object, Predicate)
• OPS = (Object, Subject, Predicate)
18

19. Anatomy of a
conjunctive query
19
AND
person:
Daniel
rendez-
vous
SeekingFilter
RemoteSourceIterator
• We keep track of the lowest
and highest Subjects for each
entry of the OPD table.
• We compute the intersecting
range of Subjects between the
left and right nodes and use it
as our boundaries.
• We add a SeekingFilter in order
to ensure we won’t exceed the
boundaries.
RemoteWriteIterator
Mutations
TwoTableIterator
SeekingFilter
Hutchison & al., Graphulo Implementation of Server-Side Sparse Matrix Multiply in the Accumulo Database, 2015

20. Back to ontologies…
• Why adding an ontology layer on top of your data?
• It enriches the vocabulary.
• It allows to infer new facts not explicitely stored.
• It provides a unified view of multiples sources.
20

21. An example of Datalog query
21
• Given the fact base below, what is the answer to the
following query ? :- hadMeeting("cyrille", Y)

22. An example of Datalog query
22
• Given the fact base below, what is the answer to the
following query ? :- hadMeeting("pierre", Y)

23. Here comes Existential Rules!
• Graal gives you the ability to assert the existence of
unknown entities : http://graphik-team.github.io/graal
• Graal allows you to rewrite any query as an union of
conjunctive queries:
Matrix multiply!
23M.-L. Mugnier, Reasoning on Data: The Ontology-Mediated Query Answering Problem, 2018

24. An example of Existential query
24
• Given the fact base below, what is the answer to the
following query ? :- hadMeeting("cyrille", Y)

25. An example of Existential query
25
• Given the fact base below, what is the answer to the
following query ? :- hadMeeting("pierre", Y)

26. Any questions?
26
Thank you for
listening!

27. Adresse:
ComputableFacts
178, bd Haussmann
75008 Paris