This presentation sheds light on the critical challenges of establishing a sustainable digital infrastructure in the United Kingdom. The work conducted by TaNC plays a crucial role in addressing key factors within the realm of digital infrastructure, including:
[1] Tools and Pipelines: This encompasses software and related components.
[2] User Knowledge Needs: We draw insights from Ackoff's 'Data to Wisdom' model and Taylor's 'Needs of Information' theory to understand user requirements.
[3] Platform Support: This pertains to the necessary infrastructure to sustain the digital ecosystem.
Currently, our focus lies in finding solutions to several pressing issues, such as:
Capacity and Digital Readiness: We are actively exploring strategies to address capacity-related challenges and enhance digital readiness.
Open Access and Equivalently Licensed Content: We are committed to promoting open access and content with equivalent licensing to foster a more accessible digital landscape.
Collaboration Pathways: We are working towards optimizing collaboration pathways to facilitate seamless cooperation within the digital community.
2024: The FAR, Federal Acquisition Regulations - Part 29
Where Do I Stand? Deconstructing Digital Collections [Research] Infrastructures: A Perspective from Towards a National Collection
1. Where Do I Stand?
Deconstructing Digital Collections
[Research] Infrastructures:
A Perspective from Towards a National Collection
Open and Engaged 2023: Community over Commercialization
British Library
Javier Pereda
Senior Researcher
2. Overview
• Towards a National Collection is supporting
research that breaks down the barriers that
exist between the UK’s outstanding cultural
heritage collections, with the aim of opening
them up to new research opportunities and
encouraging the public to explore them in
new ways
• The term ‘national collection’ represents the
breadth and range of culture and heritage
collections across the UK
3. Scoping future infrastructure
• How should we respond to the issues around capacity and digital
readiness?
• Should it include only Open Access and equivalently licensed
content?
• How should it maximise collaboration?
• How should we integrate processes of decoloniality at design
level?
• How do we ensure resilience and sustainability?
Needs of Information
(Information Objects)
Tools
(Pipelines)
Platforms
(Infrastructures)
5. Future Infrastructure
Needs of Information (Objects)
Lavoie, B., 2000. Meeting the challenges of digital preservation: The OAIS reference model. OCLC Newsletter, 243, pp.26-30.
OAIS Reference
Model
What, how, where is
*information needed
by/from users?
What is:
• Data
• Metadata
• Information
• Knowledge
6. Future Infrastructure
Needs of Information (Objects)
Visceral
Conscious
Formalised
Compromised
ACKOFF, R. L. 1989. From data to wisdom. Journal of Applied Systems Analysis, 16, 3-9.
TAYLOR, R. S. 1967. Question-Negotiation and information seeking in libraries. DTIC Document.
Stressful
Leisure
Ackoff (1989). From data to wisdom.
Taylor (1967). Levels of need of information
Knowledge Graphs &
Semantic Web, AI
Behaviours
Information(Objects)
7. Future Infrastructure
Tools (and pipelines)
Findable-Accessible-Interoperable-Reusable
…the principles apply not only to ‘data’ in the
conventional sense, but also to the algorithms,
tools, and workflows that led to that data. All
scholarly digital research objects —from data to
analytical pipelines—
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3,
160018 (2016). https://doi.org/10.1038/sdata.2016.18
Wilkinson, et.al., (2016)
PRINCIPLES
InfoObjs/Platforms/Tools
8. Future Infrastructure
Tools (and pipelines)
Open Data
Sets
Open
Standards
Technology
Open
Standards
Data
Open
Source
Technology
Used
Used
Created
Created
User Adopter Implementer Developer Creator
Technical Capability
Open Standards/Technology Audit, Towards a National Collection (2023)
PRINCIPLES
10. Future Infrastructure
Platforms (Infrastructures)
Content Information
Content Data
Object
Representation
Information
Content Data Object
Description
Environment Description
Software
Environment
Hardware
Environment
Lavoie, B., 2002. Preservation Metadata and the OAIS Information Model: A Metadata Framework to Support the Preservation of Digital Objects. Available
at: https://www.oclc.org/content/dam/research/activities/pmwg/pm_framework.pdf (Accessed: 11 September 2023)
OAIS Reference
Model
11. Future Infrastructure[s]
The Wider TaNC Research Ecosystem… so far
Knowledge
Infrastructures
Cultural
Infrastructures
Creative
Infrastructures
Technical
Infrastructures
Socio-Economic
Infrastructures
DCMS. 2022. DCMS Sector Economic Estimates Methodology [Online]. Available: https://www.gov.uk/government/publications/dcms-
sectors-economic-estimates-methodology/dcms-sector-economic-estimates-methodology [Accessed 1 June 2023].
DCMS
Standard Industry Classifications
TaNC Ecosystem… so far.
12. Keep in Touch
Javier Pereda
Javier.Pereda@hes.scot
@TrinkerMedia
www.nationalcollection.org.uk
Explore some of the tools methods issues that would underpin the building of a national collection
IIIF – Use of standards and better ways to use them
National Archives - 'visual search', an AI-based method for matching similar images ** 'generous interfaces’
Locatin Nat collection - Combining geo-spatial metadata across collections can open up new forms of research, engagement and interaction for different audiences
Persistent Identifiers - globally unique identifiers across collections, and how to implement them to support persistence, improve discovery, and enable tracking and citation of heritage collections.
Funded by UKRI – AHRC
Based at Historic Environment Scotland wich is an independent organisation
eight foundation projects
three covid 19 projects
five discovery projects
And commissioned research
Content Information (CI) – What the object is
Preservation Desc – Reference, Provenance, Context, Fixity (authentication),
Package – Archival information package
Descriptive info – facilitates access to the content
Data: This is the most basic form, representing raw facts and figures. At this stage, the data is unprocessed and lacks context or meaning.
Information: When data is processed, organized, or structured in some way, it becomes information. At this stage, questions like "Who?", "What?", "Where?", and "When?" get answered.
Knowledge: This level goes beyond information by adding context, experience, interpretation, and reflection. Knowledge answers the "How?" question and enables one to apply information effectively in different situations. It often comes from human insights, intuition, and skills acquired over time. Knowledge can be tacit (in one's mind) or explicit (codified and documented).
Wisdom: The highest level of the hierarchy, wisdom involves making sound judgments and decisions based on knowledge. It takes into account ethical considerations, long-term consequences, and the "Why?" question. Wisdom allows for a broader understanding and the application of values, ethics, and human experience to make meaningful decisions.
FAIR guiding principles have helped to safeguard transparency, reusability and reproducibility of data objects. However, it is important to highlight that FAIR principles should apply to all kind of information objects including algorithms, tools, workflows and pipelines, and software used to generate new knowledge such as further information objects, scientific publications, and exhibitions, among others (Lamprecht et al. 2020).
Open Data Sets:
“Open data is data that can be freely used, re-used and redistributed by anyone -subject only, at most, to the requirement to attribute and sharealike” (source: OpenDataHandbook.org)
Use and creation of institutional data sets –Creation of website usage data –Creation of survey data –Use and creation of knowledge graphs –Use of social media data
Open Standards Data:
“Open standards for data are documented, reusable agreements that help people and organisations to publish, access, share and use better quality data.” (source: Open Data Institute)
- Use and creation of shared vocabularies –Creation of guidance for use of open standards data
Open Standards Technology:
“An open standard is a standard that is freely available for adoption, implementation and updates. A few famous examples of open standards are XML, SQL and HTML” (Source, IBM)
- Computer Vision - NLP
Open SourceTechnology:
“At its core, open source code is created to be freely available, and most licenses allow for the redistribution as further information objects, scientific publications, and exhibitions, among others (Lamprecht et al. 2020).
- Code libraries –Code repositories –Web applications –Data repositories –Data formats –Desktop applications –Data applications
Content Information:
Content Data Object: information detailing the characteristics and features of the Content Data Object itself that are necessary to render and understand its content.
Representation Information: hardware/software environment capable of rendering or displaying the Content Data Object in the form in which it currently exists in the archival store.
Environment Description
Software Environment: the collection of digital objects – e.g., Internet Explorer and Windows 95 – that, when combined, enable access to the content of the archived object
Hardware Environment: consists of physical objects – primarily computer-related equipment such as monitors, microprocessors, and memory chips – that are necessary to operate the software environment.