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InterPARES Summer School 2025
Data as artifacts & as records
Day 2 – Tuesday, 24 June
09:15-10:30
Dr Tracey P. Lauriault
Associate Professor
Critical Media & Big Data
School of Journalism &
Communication
Carleton University
Tracey.Lauriault@Carleton.ca
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T.P. Lauriault, InterPARES Summer School 2025
The Program
Part 1: Metrology
Part 2: Data
24/06/2025
Part 3: InterPARES 2
• CS06
Cybercartographic
Atlas of Antarctica
• GS10 Scientific Data
Portals
Part 4: I Trust AI
• CS04 Digital Twin
T.P. Lauriault, InterPARES Summer School 2025
Data? What is the record?
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PART 1:
Metrology
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Metrology
“is the science of
measurement & its
application”
“includes all theoretical &
practical aspects of
measurement, whatever the
measurement uncertainty &
field of application”
Bureau International
des Poids et
Mesures (BIPM)
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T.P. Lauriault, InterPARES Summer School 2025
Measuring
“measuring, is merely
comparing an unknown physical
quantity, w/ a quantity of the
same nature taken as a
reference using an instrument”
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Edme Régnier’s dynamometer +/-1790
measuring tension & pressure exerted
by a person or animal
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Units & Measures are Social
Constructions
A Unit of measurement “is a
particular representation of the
quantity measured, taken as a
reference and chosen by convention
to express the results of
measurement”
Measurement laid the foundation for
science.
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Photo, Lauriault w/OSI 2014
T.P. Lauriault, InterPARES Summer School 2025
Measuring is a social moderator
Before measuring became an act of science, it was about
establishing social justice & peace
“is a response to the necessity of equitable distribution of
resources among inhabitants of the same place”… “is an act of
power” and “an exercise in delimitation, a matter of decision
rather than precision”
Scribe of the Fields of the Lord of the Double Land of
Upper and Lower Egypt” Fresco in the Tomb of Menna, circa
1400 BCE Photo, Lauriault 2022
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Measuring as Social Control
We give authority to measurement, and there are
authorities with the responsibility to ensure good
measures!
Monitoring, enforcing, ensuring..
Providing a continuous chain of standards and
traceability
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Photo, Lauriault 2022
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Proportions: principle of justice
The power of measurement provides control and regulation without
recourse to moral considerations
A means to “equitably regulating relations between citizens in
their relationships to community property, wealth and honours
(responsibilities, posts, political appointments)” Aristotle
Morality and civic responsibility
Communal activity!
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Trafalgar Square
The pertica on the D’Accursio
wall in the Piazza Maggiore
Bologna (circa 1200)
Photo Lauriault 2025
Ascoli, on the wall
of San Francesco
church (1568)
Photo Lauriault
2024
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Fair Measures & Commerce
Main Arch of the Sponza
Palace
FALLERE NOSTRA VETANT
ET FALLI PONDERA
MEQVE PONDERO CVM MERCES
PONDERAT IPSE DEVS
Our Weights Do Dot
Permit Cheating
When I Measure Goods
God Himself Measures
With Me
Sponza Palace (Circa 1513)
Photo Lauriault 2024
Dubrovnik old town,
Column of Orlando
Ragusan cubit, lakat
(1418)
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Measures and Order
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The Allegory of Good and Bad Government is a series of three fresco panels painted,
Ambrogio Lorenzetti, February 1338/1339.
T.P. Lauriault, InterPARES Summer School 2025
Measurement & In-Direct
Knowledge
Measurement is based on “wide-ranging theoretical knowledge, …an
array of extremely sophisticated instruments… and today’s high-
capacity data processing capabilities”
Forging the metre - Le Monde illustré, 6 mars 1875, p. 164. Dessin de M. Miranda,
gravé par Louis Joseph Amédée Daudenarde
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Dematerialization
It is equal to one ten-millionth of the length of the quadrant of the meridian
between Dunkerque and Barcelona through the Paris Observatoire
The metre is adopted as a unit of measure & in June 1799 2 platinum standard
metres were created
The metric system goes international in 1867 & a new metre prototype was created
1875 the Metre Convention is signed
In 2019 the metre becomes:
symbol m, is the SI unit of length. It is defined by taking the fixed numerical value of the speed
of light in vacuum c to be 299792458 when expressed in the unit m s−1, where the second is
⋅
defined in terms of the caesium frequency ΔνCs
Now based “on the rules of nature to create the rules or measurement linking
measurements at the atomic and quantum scales to those of the macroscopic level”
Director of BIPM 2018
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PART 2:
Data
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Datafication
The process of taking information about all
things under the sun… and transforming it
into a data format to make it quantified
“render into data many aspects of the world
that have never been quantified before”
“To datafy a phenomenon is to put it in a
quantified format so it can be tabulated and
analyzed” and “to datafy, we need to know
how to measure and how to record what we
measure”
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Conceptualizing Data
“data are commonly understood to be the raw
material produced by abstracting the world into
categories, measures and other representational
forms – numbers, characters, symbols, images,
sounds, electromagnetic waves, bits – that
constitute the building blocks from which
information and knowledge are created”
“data do not exist independently of the ideas,
instruments, practices, contexts and knowledges
used to generate, process and analyze them”
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The world is abstracted into data
Data are partial, selective and biased – always!
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Framing Data
Technically
Ethically
Politically & economically
Spatial/Temporal
Philosophically
Data & Technological Citizenship
Data activism
Sustainability
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@GlacialMeg
T.P. Lauriault, InterPARES Summer School 2025
Technically
• Data quality
• Validity
• Reliability
• Integrity
• Authenticity
• Useability
• Certainty
• Bias
• Calibration
• Error
• Sample size
• Sampling techniques
• Uncertainty
• Models
• Methods
24/06/2025
• Volume
• Variety
• Veracity
• Interoperability
• Format
• Techniques
• Metadata
• Instruments
• Analytics
• Storage
• Linked
• Structure
• Science
• Samples
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Ethically
• Justice
• Equality
• Fairness
• Sovereignty
• Honesty
• Respect
• Rights
• Entitlement
• Care
• Access
• Sharing
• Laws
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• Codified & enshrined
in rules, principles,
policies, licences and
laws
• How data are shared,
used, generated,
protected
• Data collection can
harm (psychologically)
• Dataveillance – data
analytics – social
sorting
• Cultural bias
• Data protection Laws
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Political Economy
• Open data view
• Business view
• Civil society view
• Citizen view
• Economic resource
• Copyright
• Patents
• Data Governance
• Records Management
View
• Preservation View
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• How people think about
them and how used by the
state
• Notions of how they
should be regulated
• Discursive regimes
• Funding decisions
• How do data leverage
profit
• Traded in the
marketplace
• Data as agents of
capital interests
• Data & surveillance
capitalism
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Spatial / Temporal
Place, Space, Time, Scale,
Relationality
Change:
• Organizational
• Improvements in techniques & tools
• Laws
• Technologies
• Boundaries
• Jurisdictions
• Worldviews
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July 4 2020 March 14 2022
Satellite image Maxar Technologies v/AP
Mariupol Drama Theater, Mariupol Ukraine
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Philosophically
Ontologically benign (what is)
• Neutral technical things
• Pre-analytical
• Pre-factual
• Objective realist view
• Mechanical objectivity
• Science has no politics
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• Epistemological units
(how we know)
• Data produce the world
• Data are more than
representations
• Not independent of
thought systems
• Data are social and
material
• We make the world to
enable data to
flourish
• Component of the real
and producer of the
real
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Dynamic Nominalism
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Philosophy of Science
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Social Shaping Thesis
Kitchin, 2012
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Social & Technological Data Assemblage
Lauriault, T. P. Looking
Back Toward A “Smarter”
Open Data Future,
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Data & Technological Citizenship
We live in a technological society
Decisions about data & technology are political
We should not leave all data & technological
decisions to the technocrats
3 preconditions for technological citizenship
1. Agency
2. Capacity to act – power
3. Knowledge
Those who possess those preconditions have the
responsibility to act and intervene in the
technological society
Andrew Feenberg, 2011
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Data Activism
Walking
With Our
Sisters
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Sustainability
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PART 3: InterPARES
2
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Data
Archives Science
11/06/2025
Datum
• The smallest meaningful units
of information
• A date on a birth
certificate, etc.
Data
• Facts or instructions
represented in a formalized
manner, suitable for
transmission, interpretation
or processing manually or
automatically. [Archives]
Datum
• Singular for data
• One item of information
• A fact, a statistic, a
temperature reading etc.
Data
• Plural of datum
• Dataset, database, etc.
• See the Metrology & Data
sections of this presentation
• See the Data Revolution for
kinds of data (Kitchin 2022)
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InterPARES (IP2)
Interactive, Experiential, Dynamic Records
(2002-2007)
Funding
• SSHRC Major Collaborative Research Initiatives (MCRI) programme,
• US National Historical Publications and Records Commission (NHPRC)
• US National Science Foundation (NSF)
PI
• Luciana Duranti, iSchool, UBC
Carleton University Partnership
• D.R. Fraser Taylor, Geomatics and Cartographic Research Centre, Department of
Geography and Environmental Studies, Carleton University, Canada
• GRA Tracey P. Lauriault
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The InterPARES 2 (IP2):
Interactive, Dynamic Records (2002-
2007)
• Multinational funded multicultural, multisectoral, international, inter-
and trans-disciplinary research project
• Produced a new body of knowledge consistent with each separate field and
provided solutions to the problems presented by digital preservation.
• IP2 extended the work of IP1
• Developed and articulated concepts, principles, guidelines, criteria and
methods to ensure the:
“creation and maintenance of accurate and reliable records and the long-
term preservation of authentic records in the context of artistic,
scientific and government activities that are conducted using
experiential, interactive and dynamic computer technology”
• It was far reaching, exciting and groundbreaking.
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IP2 Objectives
Objectives
• Creation and maintenance of accurate and reliable records
• the long-term preservation of authentic records in the context of
artistic, scientific and government activities
• are conducted using experiential, interactive and dynamic computer
technology
Object of Research
• CS06 Cybercartographic Atlas of Antarctica
• GS10 Scientific Data Portals
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IP2 Intellectual Framework Research
Activities
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FOCUS 1
Artistic Activities
FOCUS 2
Scientific Activities
FOCUS 3
Governmental
Activities
DOMAIN 1
Records Creation &
Maintenance
Working Group 1.1 Working Group 1.2 Working Group 1.3
DOMAIN 2
Authenticity,
Accuracy & Reliability
Working Group 2.1 Working Group 2.2 Working Group 2.3
DOMAIN 3
Methods of Appraisal
& Preservation
Working Group 3.1 Working Group 3.2 Working Group 3.3
Terminology
Policy
Description
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IP2 Focus 2 – Sciences Case & General
Studies
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IP2 Focus 2 Science Case Studies
CyberCartographic Atlas of Antarctica
Mars Global Surveyor Data Records in
the Planetary Data System
MOST Satellite Mission: Preservation
of Space Telescope
Archaeological Records in a
Geographical Information System:
Research in the American Southwest
Data Preservation and Authentication
of Electronic Engineering and
Manufacturing Records
IP2 Focus 2 Science General Studies
Preservation Practices of Scientific
Data Portals
Building Preservation Environments
with Data Grid Technology
Digital Recordkeeping Practices of
GIS Archaeologists Worldwide:
Results of a Web-based Survey
A Bayesian Belief Network:
Supporting the Assessment of the
Degree of Belief that a
Recordkeeping System Maintains
Authentic Digital Records
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IP2 Case Study 06 (CS06)
Cybercartographic Atlas of Antarctica
(2005)
CS06 Researchers
• Tracey P. Lauriault, Geomatics and Cartographic Research Centre, Department
of Geography and Environmental Studies, Carleton University
• Yvette Hackett, Library and Archives Canada
• Data Collection Support from:
• Geomatics and Cartographic Research Centre, Carleton University
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IP2 CS06 - Objectives
Cybercartographic Atlas of Antarctica
To study the creation and use of:
• Born digital experiential, interactive & dynamic online atlas
• Scientific, multidimensional, multisensory & multimedia
mapping
• Federated, distributed data
• Interoperable, Open source, specification & standards
• Early example of the Spatial Web
• Portrayed, explored and communicated the complexities of the
Antarctic continent for educational, research and policy
purposes and support some of the requirements of the Protocol
on Environmental Protection to the Antarctic Treaty
• Early examples of complex assemblages of data and technical
systems (digital entity) that presented preservers with
significant preservation challenges
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IP2 CS06 Methodology
Methodological Principles
1. Interdisciplinarity
2. Transferability
3. Open Inquiry
4. Multi-method Design
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IP2 CS06 - Findings
1. E-publication
• The Atlas is not a record and not a CU Fond
• interactive e-document with variable content & form w/ rules
governing its context and form of presentation at times fixed
or variable w/modules created in a dynamic computing platform
2.Code as a record
• In Subversion & GitHub
3. Enabling document
• incorporating instructions to execute the Atlas - code & data
– w/descriptions of components, context, preconditions or
requirements for the data and the code to be seen in the
future enabling data from several scientific international
sources to be re-mediated in theme-specific modules to be seen
and re-seen
4. Composing relationship
• Between code, modules but w/ non originary data
5. Presumption of authenticity
• Data sources were from reliable and trusted sources
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IP2 Case Studies Findings:
Experiential, Interactive, Dynamic
Records
• The characteristics of the systems w/in which records
were created and maintained revealed that dynamic
objects drew their content from data extracted from
systems which had variable instantiations
• Experiential objects incorporated the behaviour of the
rendering systems along with subjective user
interactions for their content and form
• Interactive objects changed content and form in
response to user intervention or input from another
system
• Records were therefore found in complex social and
technical assemblages of interacting systems and
subsystems
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IP2 Case Studies Findings: Bounded
Variability
Records
• IP1 for digital objects to be records they must
have a stable content and a fixed documentary
form
• Even if the Atlas involved transactions &
actions, it would not be a record according to
IP1
Bounded variability
• In IP2 atlases, GIS, or other like artefacts
could be records according to the new definition
• “referred to changes to the form and/or content
of a digital record that are limited and
controlled by fixed rules, so that the same
query, request or interaction always generates
the same result” (Duranti & Thibodeau 2008)
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IP2 CS06 – Findings:
Recommendations
Because the Atlas was created w/:
• open-source software that was highly interoperable, supported by a robust
repository system that incorporated a classification system and a multimedia
metadata schema that met archival requirements and geospatial standards;
• and the source data for the modules were from presumed authentic sources w/
good lineage and accuracy parameters
IP2 preservers and archival researchers suggested that this was an excellent
strategy for the long-term sustainability and potential preservation of this
and other complex digital entities
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IP2 GS10 - Science Data
Archives/Repositories
GS10 Researchers
• Tracey P. Lauriault, Geomatics and Cartographic Research Centre, Department
of Geography and Environmental Studies, Carleton University
• Barbara L. Craig, Faculty of Information Studies, University of Toronto
• Data Collections Support from:
• IP2 Coordinators: Yau Min Chong, Bonnie Mak, Greg Kozak and Preston
• IP2 Technical Support: Jean-Pascal Morghese
• IP2 GRAs: Sherry Xie, Heather Dean, Cristina Miller, Brian Tremblanth and Stephen Gage
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• Geospatial and scientific data are discovered and
accessed from, and are often stored in data portals,
repositories, catalogues, archives and libraries
• Access and dissemination of data in the sciences and in
the field of geomatics rely heavily on these types of
initiatives, which may or may not include archiving or
preservation as a mandate
• The objective was to collect information about the
actual practices, standards and protocols used by
broadly defined existing data services, portals,
archives, repositories or catalogues in the sciences
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IP2 GS10 - Objectives
Science Data
Archives/Repositories
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IP2 GS10 - Data portals, repositories,
catalogues, archives & libraries
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IP2 Case Studies that examined Data
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IP2 GS10 - Survey Questions
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IP2 GS10 – Findings: Accuracy
• The measure of accuracy, error or distance from the truth is a critical data
quality element for scientific data. It is a measure of certainty, and this is
what attests to the trust of a dataset
• Each scientific community and each specific dataset includes its own accuracy
parameters and particularities.
• Acquisition is the point where the original observations are collected and
where fundamental assumptions, calibrations are made
• Compilation is the part where a database is created; it occurs when the facts
are assembled into some sort of comprehensive arrangement or into a scientific
dataset, and it is a phase where many errors can be introduced
• Derivation is the stage where data are being manipulated; the output of this
process is a representation, interpolations, averaging, and any number of
manipulative techniques that may change the form, format or structure of the
data
• Error is articulated
• Accuracy is within metadata or is articulated in the paradata
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IP2 GS10 – Findings: Reliability
• Is closely associated with the concepts of reproducibility and accuracy.
• It can be related to the degree to which forecast, model probabilities or
results match the observed frequencies of an occurrence in the environment or
consistently produce the same result.
• More generally, reliability is a quality that can be attributed to a person,
as in a reliable person; to a device, such as a reliable machine; or to a
system that is organized to accomplish certain ends, as in a reliable computer
or records system.
• It is the individual assessor – record/data creator - who determines what
attributes are required before reliability can be reasonably inferred
• Trustworthiness thus has qualitative dimensions - reliability and authenticity
- and quantitative dimensions - accuracy and completeness. If the record’s
integrity appears to be compromised in some way, or if its lineage is not
clear and complete, knowledgeable users would have grounds for withholding
trust
• Data Quality Disclaimers
• Reliability parameters are in the metadata or the paradata
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IP2 GS10 – Findings: Authenticity
• Scientists do not normally use the term authenticity, but instead use the
terms lineage, data provenance or data integrity
• Lineage is the who, what, where, how, and when data were captured and what has
occurred to these data throughout their lifecycle, that includes the methods
and modelling of the data the process of data control begins at the time the
data are ingested into the system, made accessible via Web server sharing
protocols or described into a metadata description form
• Once data are in a particular portal, there are several security measures in
place to ensure they are not tampered with
• Presumption of Authenticity “an inference as to the fact of a record’s
authenticity that is drawn from known facts about the manner in which that
record has been created and maintained.”
1) an explicit description of the sources of the data and of the changes and processes that the
data have undergone over time, so that any user is able to come to a decision about whether the
data fit their proposed use; and
2) the continuing authority that the portal maintains as a viable community of practice & data
• Articulated in the metadata or maybe the paradata
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IP2 GS10 – Findings: Lineage
• Information that describes the source of the observations, data collection and
compilation methodologies, conversions, transformations, analyses and
derivations to which the data have been subjected.
• It also provides the assumptions, and the criteria applied at any stage of its
life, as well as any biases. In fact, lineage is normally the first part of a
quality statement, since most other data quality elements are affected by
lineage.
• Lineage is a kind of audit trail to attest to the fact that the producers have
met those requirements. Lineage provides a dataset with its pedigree and
allows the user to decide on its fitness for use; it can also be found in a
dataset’s associated publications, reports, and technical notes.
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IP2 GS10 – Findings: Overall
• Creators determine data quality and
appraise their data before
depositing them in a portal
• Data users determine fit for
purpose by reading the metadata and
paradata
• The overall recommendation was that
archivists ingest data already
curated by data creators in portals
as these have already been
appraised as worthy of
dissemination
• Accuracy, reliability &
authenticity are contextually
related to the scientific practice
and domain
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“The relevant framework of
appraising scientific
datasets, thus, is not defined
by the business activities or
the need for corporate memory
of the sponsoring agency, but
by the research community.
Seeking the input of
scientists in the appraisal of
the data recognizes that the
roles and the actions of
academic researchers are at
least as important as the
functions of the agency that
funded the research or
launched the
satellite”(Thibodeau 1995)
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IP2 Outputs
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IP2 Outputs
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Tracey P. Lauriault
Yvette Hackett
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IP2 Outputs
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IP2 Outputs
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2019
2007
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IP2 Outputs
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IP2 Outputs
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PART 4: I Trust AI
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Digital Twin Definition
“a set of virtual information constructs that mimics the structure, context,
and behavior of a natural, engineered, or social system (or system-of-
systems), is dynamically updated with data from its physical twin, has a
predictive capability, and informs decisions that realize value. The
bidirectional interaction between the virtual and the physical is central to
the digital twin”. (NAP 2024)
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Spatial Digital Twin
• Includes a specific spatial context and provide a dimensional and location-
based representation of assets, infrastructure and systems
• Various levels of accuracy, detail and aggregation
• It is multiscalar from buildings to clusters of buildings or other
infrastructure, networks, cities, countries and the globe
• Often used for planning, lifecycle management and monitoring
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Our Case Study Examines
A spatial digital twin for the architecture, engineering, construction and
owner operated (AECOO) sector in Ottawa, Canada that is based at Carleton
University
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1.CU04 Digital Twin Case Study - Archives 4.0: Artificial
Intelligence for Trust in Records and Archives, (UBC, PI Luciana
Duranti & Co-director Muhammad Abdul-Mageed, SSHRC Partnership Grant,
Canada)
• Identify specific AI technologies that can
address critical records and archives challenges;
• Determine benefits/risks of using AI technologies
on records and archives;
• Ensure archival concepts and principles inform the
development of responsible AI;
• Validate outcomes through case studies and demonstrations
2.Object of Study - Imagining Canada’s Digital Twin Project, New
Frontiers in Research Grant, Carleton University Immersive Media
Studio (CIMS), Carleton University, Canada
Joins 2 RESEARCH PROJECTS
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Imagining Canada’s Digital Twin
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CIMS National (spatial) Digital Twin of
Canada
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CS04 – Research Questions
1.If digital twins intermediate and automate
actions and decisions that affect people and
property, how ought records about those actions,
decisions and processes be managed and archived?
2.Can AI/ML enable that preservation?
3.And how would one archive AI/ML processes?
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Data Governance
“the exercise of decision making and authority for data-
related matters.
a system of decision rights and accountabilities for
information-related processes, executed according to
agreed-upon models which describe who can take what
actions with what information, and when, under what
circumstances, using what methods.
about making sure that people are properly organized and
do the right things to make their data understood,
trusted, of high quality, and, ultimately, suitable and
usable for the enterprise’s purposes” (Plotkin 2021)
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We also wanted to know
The epistemic concerns of those involved?
• Architecture, engineering, construction, owner and operated (AECOO)
• Finance, builders, plant management etc.
Are Digital Twins public spaces? Public Goods?
What good governance practices from other fields can be considered? Open
Data? Open Science? Etc.
What data and technological politics are embedded in the system?
• Business models / governance models
• Institutions
• Public access & ability to use and contribute to?
• Governance
• Ownership
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4 Interrelated Theoretical Frameworks &
Concepts
1. Critical Data Studies (Kitchin & Lauriault, 2018)
2. Digital diplomatics (InterPARES 1 & 2 Projects)
3. Social and Technological Data Assemblage (Lauriault 2022)
4. Combination of technological Walkthrough (Light, Burgess
& Duguay 2018) w/ Digital Record Forensics (Duranti 2009)
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Hybrid Methodological Approach
• 13 semi-structured interviews guided by a survey instrument
designed to collect data and information from a digital
diplomatics and social and technical assemblage point of view.
• 4 technological walkthroughs/Records Forensics
• Carleton Immersive Media Studio
• Carleton University Facilities, Plant & Control Rooms
• Carleton Engineering Design Centre Building Labs
• Ottawa City Archives
• Mapped social and technological assemblages & sought records
• Validation of comparative analytical tool w/Archivists
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What we observed at CIMS – Architecture
View
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What we saw at CIMS
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What we Experienced w/Owner operators
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Building
Environment View
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Architectural/City View
Archives
View
Mutually Distinct Systems & Juridical
Contexts
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BLDG
Operations
View
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FM = Facilities Management
What we thought we were studying
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What we saw
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Assets Replicas of Assets
Architecture/City - spatial
T.P. Lauriault, InterPARES Summer School 2025
We also saw
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FM = Facilities Management
Assets
Owner Operated - FM
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What is the record?
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Archives
Data, Logs,
Indicators Reports
Generated by the
Sensors +
Decisions/Actions
seen in Seals &
Approval Signatures
Architectural & engineering renderings
of assets - original data not the copies
of the assets rendered into a map etc.
Contracts, invoices,
receipts, etc.
Assets Replicas of Assets
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CIMS National Digital Twin of
Canada
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Bidirectional?
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Digital Twins are coming though!
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Garisenda Tower in Bologna
T.P. Lauriault, InterPARES Summer School 2025
I Trust AI - RESEARCH QUESTIONS
1. If digital twins intermediate and automate actions and decisions
that affect people and property, how ought records about those
actions, decisions and processes be managed and archived?
• The parts and not the whole
• Code, AI/ML and the data
• Transactions/Actions
2. Can AI/ML enable that preservation?
• Sure, but of records, maybe not the publication
3. And how would one archive AI/ML processes?
• Stay tuned?
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CS04 - Digital Twin CS Team
• ­
Tracey P. Lauriault, I Trust AI Lead, Associate Professor, Critical Media and Big Data, School of Journalism and
Communication, Carleton University
• Anna-Lena Theus, PhD Candidate at Carleton University (Project GAA)
• Carleton Immersive Media Studio (CIMS)
• Stephen Fai, Professor cross appointment in the Department of Civil and Environmental Engineering, the
Institute for Comparative Studies in Literature, Art, and Culture, and the Azrieli School of Architecture
and Urbanism; Director of the Carleton Interactive Media Studio (CIMS)
• Mario Santana Quintero, Professor in Architectural Conservation and Sustainability Engineering
• Nicolas Arellano, PhD Candidate
• Building Science Engineering and Sustainability Engineering
• Liam O’Brien, Professor in Architectural Conservation and Sustainability Engineering, PI the SUSTAIN
Project (Sensor-based Unified Simulation Techniques for Advanced In-Building Networks) project at Carleton
University
• H. Burak Gunay, Assistant Professor in Building Science, Department of Civil and Environmental Engineering
• Carleton University
• Travis Kinnear, MLIS, Digital Archivist, Corporate Records & Archives, University Secretariat, Carleton
University
• Chris Trainor, Archives & Special Collections, MacOdrum Library
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Conclusion
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Conclusion
• A Digital Twin is a system of systems that involves Interactive,
Experiential, Dynamic Digital Records
• Interdisciplinary Hybrid methodological approaches work
• IP2 + I Trust AI + Walkthrough + Archival + Critical Data Studies
• Diplomatic Analysis - for Digital Twin the record depends on the
juridical context of the digital entity
• Validation with archivists is essential
• Mutual shaping of knowledge during interviews
• IP2 concept of Bounded variability remains an important concept
• Data are our cultural artifacts and data can be records and records
can be datafied!
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InterPARES Summer School 2025
Abstract
This class will present the relationship between metrology and data,and
consider data beyond normalized technological understandings.
Examples will be drawn from the InterPARES 2 General Studies about the
concepts of reliability, accuracy and authenticity in the sciences,
and from the InterPARES Trust AI case studies about digital twins and smart
grids.
The class will end with a discussion of the relationship between data and
records.
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