Research Document No. 14 Metadata within Intelligent Archival Ecosystems Towards the concept of Intelligent Archival Metadata

 

PDS & Ged/A | Research Notes

Research Document No. 14

Metadata within Intelligent Archival Ecosystems

Towards the concept of Intelligent Archival Metadata

25 July 2026

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🌎 Open Science

The PDS & Ged/A Research Notes are part of an ongoing Open Science initiative devoted to documenting the evolution of our research programme in Digital Archival Science. Rather than presenting definitive conclusions, these documents openly share emerging concepts, evolving hypotheses and future research agendas. This Research Note explores the possibility that archival metadata are evolving from descriptive instruments into active infrastructures supporting knowledge, governance, preservation, interoperability and institutional trust.

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📚 What have we learned so far?

Throughout the previous thirteen Research Notes our research programme has progressively explored how digital transformation is reshaping Archival Science.

We introduced Systemic Digital Preservation.

We proposed the concept of Digital Archival Ecosystems.

We reinterpreted the OAIS Reference Model through an archival perspective.

We expanded the meaning of the Chain of Archival Digital Custody.

We explored the convergence between the European archival tradition, Information Science, the iSchools movement and Computational Archival Science.

More recently we proposed Archival Algorithmic Governance, Intelligent Archival Ecosystems, and Intelligent Archival Records.

Yet one important question remained largely unexplored.

What role will archival metadata play within increasingly intelligent documentary environments?

Initially we expected to discuss metadata as descriptive elements.

Instead, we gradually realised they may become one of the most important infrastructures supporting Intelligent Archival Ecosystems.

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🔄 How our research question evolved

For decades Archival Science asked:

How should archival records be described?

Later we asked:

How should context be represented?

How should authenticity be preserved?

How should interoperability be achieved?

Today our question changes once again.

How can archival metadata organise knowledge, support governance, preserve institutional memory and enable trustworthy Intelligent Archival Ecosystems?

Perhaps this represents one of the most significant conceptual shifts within Digital Archival Science.

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Perhaps metadata have never been merely descriptive

One of the earliest conclusions emerging from our discussions was surprisingly simple.

Archival metadata have traditionally been understood primarily as descriptive mechanisms.

That interpretation remains valid.

Yet it now appears incomplete.

Within contemporary digital environments, metadata increasingly do much more than describe.

They establish relationships.

Activate institutional policies.

Trigger preservation workflows.

Record documentary events.

Communicate with intelligent agents.

Populate Knowledge Graphs.

Support semantic interoperability.

Provide contextual information for Retrieval-Augmented Generation (RAG).

Perhaps metadata are gradually becoming the language through which Intelligent Archival Ecosystems operate.

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📓 Laboratory Notes

During one seminar someone remarked:

"Perhaps metadata constitute the language of Intelligent Archival Ecosystems."

The sentence remained on our whiteboard for several days.

The more we discussed it,

the more convincing it became.

Archival records preserve evidence.

Metadata allow that evidence to be understood.

Connected.

Retrieved.

Preserved.

Governed.

Perhaps metadata represent the true language of archival interoperability.

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🏛️ A Conceptual Proposal

Towards the concept of Intelligent Archival Metadata

We have begun exploring the hypothesis that Intelligent Archival Metadata should not be understood as metadata possessing intelligence.

Instead, we propose understanding them as:

Archival metadata capable of actively participating within Intelligent Archival Ecosystems through semantic structures, preservation events, institutional policies, contextual relationships and interoperable services while preserving authenticity, provenance, documentary context and institutional trust.

Their primary function remains preserving meaning.

However, they increasingly support governance,

transparency,

long-term preservation,

knowledge organisation,

intelligent retrieval

and accountability.

The intelligence belongs to the ecosystem.

Metadata provide the structure through which that intelligence becomes trustworthy.

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Beyond description

Metadata are gradually assuming entirely new responsibilities.

In addition to describing archival records,

they may increasingly:

• activate access policies;

• record PREMIS preservation events;

• preserve provenance;

• represent documentary context;

• populate Knowledge Graphs;

• structure ontologies;

• enrich Retrieval-Augmented Generation systems;

• support intelligent agents;

• strengthen proactive transparency;

• document automated decisions;

• facilitate interoperability across archival platforms.

Perhaps metadata are becoming the cognitive infrastructure of Intelligent Archival Ecosystems.

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💡 One of our research findings

The quality of Artificial Intelligence increasingly depends upon the quality of archival metadata.

Sophisticated AI models cannot compensate for poorly structured metadata.

Without provenance.

Without context.

Without authenticity.

Without documentary relationships.

Trustworthy Artificial Intelligence becomes impossible.

Perhaps archival quality is itself a prerequisite for trustworthy AI.

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PREMIS as governance metadata

Throughout our discussions we gradually began interpreting PREMIS from a broader perspective.

It no longer appears solely as preservation metadata.

It increasingly documents:

computational decisions;

automated policies;

state transitions;

access releases;

rule execution;

interactions among intelligent agents.

Perhaps PREMIS will eventually function as the permanent governance journal of Intelligent Archival Ecosystems.

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RiC-CM, RiC-O and Knowledge Graphs

The evolution of international conceptual models deserves particular attention.

RiC-CM and its ontological implementation, RiC-O, provide promising mechanisms for representing complex relationships among records, agents, activities, functions, institutions and documentary contexts.

Combined with Knowledge Graphs,

these models enable Intelligent Archival Ecosystems to understand documentary relationships far beyond simple keyword retrieval.

Perhaps Digital Archival Science is gradually becoming a discipline organised around relationships rather than isolated records.

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FAIR Data Principles, Linked Open Data and Semantic Interoperability

Another particularly interesting convergence emerged during our discussions.

Although developed outside Archival Science,

initiatives such as the FAIR Data Principles and Linked Open Data offer valuable opportunities for archival environments.

Archival metadata increasingly allow records to become:

Findable.

Accessible.

Interoperable.

Reusable.

Without compromising authenticity,

provenance,

context

or the Chain of Archival Digital Custody.

This convergence deserves considerably more research.

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MCP, APIs and intelligent agents

Another emerging topic concerns communication among intelligent systems.

Technologies such as the Model Context Protocol (MCP), interoperable APIs and semantic service architectures may eventually enable intelligent agents to consult archival records, metadata and institutional policies while preserving documentary authenticity and institutional accountability.

Interoperability therefore becomes much more than a technical issue.

It becomes an archival responsibility.

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⚖️ An Archival Dilemma

When an intelligent agent interprets metadata in order to execute an institutional decision,

who ultimately remains responsible?

The metadata?

The algorithm?

The software developer?

Or the archival policy represented through those metadata?

Perhaps this question lies at the very heart of Archival Algorithmic Governance.

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Metadata as institutional memory

Perhaps one of the most interesting conclusions emerging from this Research Note is remarkably simple.

Archival records preserve events.

Metadata preserve relationships.

Without relationships,

events lose meaning.

Perhaps this explains why metadata increasingly constitute the invisible infrastructure supporting institutional memory.

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🔬 An unexpected outcome of our seminar

Initially we assumed Artificial Intelligence might reduce the importance of metadata.

Our discussions suggested precisely the opposite.

The more sophisticated intelligent systems become,

the richer,

more contextual,

more trustworthy

and more archival metadata become necessary.

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Towards a relationship-oriented Archival Science

Perhaps the greatest transformation currently taking place within Digital Archival Science is not technological.

It is epistemological.

For centuries archivists organised records.

Today we increasingly organise relationships.

That subtle shift profoundly transforms how we understand archives,

institutional memory

and documentary evidence.

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🤔 A hypothesis we partially revised

Initially we believed metadata primarily described archival records.

Today we increasingly suspect they also organise knowledge,

govern institutional processes,

document computational decisions

and sustain Intelligent Archival Ecosystems.

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🌱 A hypothesis under construction

Perhaps Intelligent Archival Metadata will eventually become one of the foundational conceptual categories of twenty-first century Digital Archival Science.

Not because metadata themselves become intelligent.

But because they allow records,

institutions,

people,

policies

and intelligent agents to share context,

meaning,

governance

and trust.

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🧭 Research Agenda

During the coming months we intend to investigate several interconnected questions.

• How should Intelligent Archival Metadata be modelled?

• How can PREMIS, RiC-O, Knowledge Graphs and Retrieval-Augmented Generation operate together?

• How should archival policies be represented through operational metadata?

• How can the Model Context Protocol (MCP) preserve authenticity, provenance and documentary context?

• How should archival metadata quality be evaluated within intelligent environments?

• How can institutional trust be measured through metadata quality?

• How might semantic interoperability reshape Digital Archival Science over the coming decade?

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🔭 Looking toward 2040

If our hypotheses prove correct,

metadata may gradually cease being perceived merely as descriptive instruments.

Instead,

they may become recognised as the cognitive infrastructure connecting archival records,

institutions,

intelligent agents,

knowledge,

institutional memory

and public trust.

Perhaps this will become one of the defining transformations of Archival Science during the coming decades.

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💬 Let's continue the conversation

How do you imagine archival metadata twenty years from now?

Will they remain descriptive elements?

Or will they become the semantic language connecting archival records,

Artificial Intelligence,

Knowledge Graphs,

institutional governance

and public trust?

We would genuinely welcome your perspective.

Your ideas may contribute to the next stage of this collaborative research programme.