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Linked Data, Irish Maternity and Maternal Mortality 1864-1913
1. Linked data, Irish maternity and maternal mortality, 1864-1913
Reusing legacy data: Irish historic Vital Registration data, 1864-1913
Dolores Grant and Rebecca Grant, Irish Record Linkage Project
2. Irish Record Linkage project 1864-1913
Irish Record Linkage is an IRC funded project running until September
2015
Collaboration between the University of Limerick, the Digital Repository
of Ireland at the Royal Irish Academy, and Insight@NUI Galway
Constructing a Knowledge Platform – Linked Data based on Vital
Registration Data (digitised registers of Births, Marriages and Deaths) in
order to answer research queries around infant and maternal mortality
3. The Digital Repository of Ireland
DRI is a trusted digital repository for the Humanities and
Social Sciences data
Linking and preserving the rich data held by Irish
institutions, providing a central internet access point and
multimedia tools
Focal point for the development of national guidelines and
policy for digital preservation and access.
4. INSIGHT@NUI Galway
Insight brings together leading Irish academics from 5
of Ireland'€™s leading research centres (DERI, CLARITY,
CLIQUE, 4C, TRIL), in key areas of priority research including:
The Semantic Web,
Sensors and the Sensor Web,
Social network analysis,
Decision Support and Optimization, and
Connected Health.
5. The Linked Data Concept
A method of publishing structured data on the Web,
allowing it to be connected and enriched, and facilitating
linking between related resources.
Linked Data standards such as RDF allows semantic
definitions to be applied to information, using statements
called ‘triples’ in the form subject, predicate, object.
A key principle of Linked Data is that HTTP URIs are used to
name the semantic elements of the dataset
6. The Linked Data Concept
The example above describes the subject (James Joyce) and his
relationship (predicate) to an object (Dublin). By semantically
separating the elements of the information (that James Joyce was
born in Dublin) datasets stored in this way can be easily queried.
7. Vital Registration data: Birth, death, marriage records
1864 -1913
Digitised TIFF images of hardcopy indexes and registers
General Register Office Database which describes the digitised
records and allows them to be searched
General Register Office records
8. Birth Records
Register TIFF Index TIFF System Pre 1900 System Post 1900
Superintendent Registrar’s
District
Registrar’s District Registration district District District
Union
County County County
Province Province
Number in register Entry number
Date & place of birth Year of event Date of birth, year of event
Name (if any) Name Forename, Surname Forename, Surname
Sex Sex
Name, surname &
dwelling place of father
Name & surname &
maiden surname of
mother
Mother’s maiden name
Rank or profession of
father
Signature, qualification,
and residence of
informant
When Registered Returns year Returns year
Returns quarter Returns quarter
Signature of Registrar
Name & surname &
maiden surname of
mother
Rank or profession of
father
Signature, qualification,
9. Death Records
Register TIFF Index TIFF System
Superintendent Registrar’s
District
Registrar’s District Registration District District
District
Union
County County
Province
Number in register
Date and place of death Year of event
Name and surname Name Forename, Surname
Sex
Condition
Age last birthday Age Age at death
Rank, profession or occupation
Certified cause of death and
duration of illness
Signature, qualification and
residence of informant
When registered Returns year
Returns quarter
Signature of Registrar
Signature of Superintendant
Registrar and date
Stamp number Stamp number
Volume number Returns volume number
Page number Page number Returns page number
Stamped number Page ID
2nd
Stamped number
Index entry number
Index page number
10. Marriage Records
Register TIFF Index TIFF System 1845-1901 System 1902-c.1912
Registrar’s District Registration District District District
Marriage solemnised at
Parish
Union
County County County
Province Province
Number in register Entry number
When married Year of event Year of event , Date
of marriage
When registered Returns year Returns year
Returns quarter Returns quarter
Name and surname Name Forename, Surname Forename, Surname
Partner’s surname
Age
Sex
Condition
Rank or profession
Residence at the time
of marriage
Father’s name and
surname
Rank or profession of
father
Celebrant
Witnesses
Signature of Registrar
Signature of
Superintendant
Registrar and date
Stamp Number Stamp number Stamp number
Volume number Returns volume number Returns volume
number
Page number Page number Returns page number Returns Page
number
Stamped number Page ID Page ID
2nd
Stamped number
Index entry number Index entry number
Index page number
11. Data preparation
Identifying the record fields that are necessary to maintain the
archival authenticity of the records and answer the research
questions:
•How many women died within 42 days following childbirth due to
complications related to labour and how does that figure correspond with the
official reports?
•Which women died of causes that can be attributed to maternal death, but for
which no corresponding birth certificate exists?
•How did various socio-economic conditions affect maternal and infant
mortality rates?
Identifying, linking and tracking people across registers
12. GRO Triplestore
Triplestore 2 Data Analysis
Transformation from one model to
another
• SPIN – SPARQL Inference
• SWRL / RuleML
• SPARQL Construct
• …
SEPARATIONOFCONCERNS
GRO Records annotation vs. Data Analysis
13. <#B000-001> a
irl:BirthRecord;
irl:on "1900-08-08";
irl:name "James";
irl:mother "Mary Murphy";
irl:place "Castle Road"; …
<#B010-022> a
irl:BirthRecord;
irl:on "1902-04-19";
irl:name "Patrick";
irl:mother "Mary Murphy";
irl:place "Castle Road"; ...
<#B022-051> a
irl:BirthRecord;
irl:on "1904-09-20";
irl:name "Agnes";
irl:mother "Mary Murphy";
irl:place “Convent Hill"; ...
<#B050-003> a
irl:BirthRecord;
irl:on "1905-02-18";
#1 Mary
Murphy
#2 Mary
Murphy
#3 Mary
Murphy
#4 Mary
Murphy
owl:sameAs
owl:sameAs
owl:sameAs
TRANSFORMATION
ONTOLOGY
MATCHING
All generated are
stored separately
for data analytics ...
14. #1 Mary
Murphy
#1 Mary
Murphy
#1 Mary
Murphy
James Patrick Michael
1900-08-08 1902-04-19 1905-02-18
619 days 1036 days
Average sibship interval = 827.5 days
Data analysis on the generated triples
15. Competency questions to construct the Ontology
ID Competency Question
C01 Women died within 41 days after giving birth
(the date of birth counted as day 1 and day 41 is included)
C02 Women died within 41 days after giving birth AND in their death certificate
‘complication 1’ is mentioned.
C03 Women died within 41 days after giving birth AND in their death certificate
‘complication 2’ is mentioned.
C04 Women having official maternal death reports including “XXXX’
C05 Women having official maternal death reports including “cause 1”
C06 Women having official maternal death reports including “cause 2 and cause 3
together”
C07 For each record in C04 find the ones with corresponding birth record
(the date of death counted as day 1 and day 41 is included)
16. DRI Presentation
• Data security - transfer, storage and use by authorised
parties
• Data protection best practice
• Data formats-ensuring compliance with digital
preservation best practice
• Varying levels of detail eg causes of death
• Variances in record subject names and places
• Place names changes over time
Data challenges
17. DRI Presentation
Irish Record Linkage Knowledge Platform
• Linked Data platform created from subset of
Dublin records
• Prepared to allow formulation of specific
research queries
• Query interface for use by historians
• Potential expansion to include additional
contextualising datasets
@IRL_Project http://dri.ie/irish-record-
linkage-1864-1913