Morganable Data Lab
The Data Lab provides the engineering, governance, standards, schemas, validation, provenance, pipelines and reproducibility infrastructure behind Morganable’s serious data work.
Explore the Data Lab → Facebook
Morganable
Evidence · Provenance · Structure · Reuse
Data becomes valuable when evidence survives its transformation.
Morganable Data is the public gateway to datasets, evidence systems, documentation and reusable data assets developed across Morganable’s journalism, research, observatories and institutional programmes.
01 / Acquire Find the evidence
02 / Structure Make it usable
03 / Validate Test the record
04 / Document Explain the transformations
05 / Release Publish appropriately
06 / Preserve Keep the lineage
01 / Data Gateway
Morganable Data
Data should preserve evidence, not merely rearrange it.
Morganable Data is intended to make governed data assets discoverable and useful across the institution’s public-interest work.
Some datasets may originate in research. Others may emerge from observatories, investigations, historical reconstruction, public records or sustained institutional programmes.
Their value depends not simply on the number of rows they contain, but on whether their provenance, definitions, transformations, validation and limitations remain sufficiently clear for responsible reuse.
A dataset should be more than a table.
It should be an evidence record.
Institutional Architecture
The Data Lab builds the capability. Data makes the assets discoverable.
Morganable Data Lab and the public Data gateway are related, but they perform different institutional roles.
Data
This gateway is where readers should increasingly discover datasets, documentation, data notes, methodologies and other approved public evidence assets.
Explore Data Architecture → Data Architecture
From source evidence to
reusable institutional asset.
Different datasets require different methods, but the underlying discipline should preserve the connection between original evidence and the released data product.
01
Acquire
Identify and obtain evidence from appropriate public, institutional or permitted sources.
02
Structure
Convert fragmented information into coherent, defined and machine-usable structures.
03
Resolve
Harmonise entities, geographies, classifications, dates and other comparable units.
04
Validate
Test completeness, consistency, range, integrity and other relevant quality rules.
05
Document
Preserve definitions, transformations, limitations and appropriate technical metadata.
06
Preserve
Retain versions, provenance and historical states so later evidence remains interpretable.
Data Catalogue Architecture
A public gateway for evidence assets.
As approved datasets mature for publication, the Data gateway should provide a structured catalogue rather than an undifferentiated directory of downloadable files.
D / 01
Public Datasets
Governed datasets approved for public access, accompanied by appropriate documentation.
Catalogue Developing
D / 02
Data Notes
Concise records explaining provenance, coverage, transformations, quality and limitations.
Developing
D / 03
Methodologies
Documentation of measurement systems, classifications, harmonisation and analytical rules.
Developing
D / 04
Historical Vintages
Earlier dataset states retained where historical comparison and reproducibility require them.
Developing
D / 05
Replication Assets
Code, schemas and supporting technical materials released where rights and methodology permit.
Developing
Provenance
Every transformation creates an obligation to preserve the trail.
Data processing can increase usability while simultaneously obscuring origin. Morganable’s data architecture should preserve enough lineage to understand how released data relates to its underlying sources.
Source provenance
Identify where significant source material originated and the conditions under which it was obtained.
Processing lineage
Record material cleaning, coding, harmonisation, derivation and transformation steps.
Definitions
Preserve the meaning of important fields, classifications, measures and units.
Temporal provenance
Record when evidence was observed, published, revised or incorporated where those distinctions matter.
Data Validation
Clean-looking data is not automatically trustworthy data.
Validation should test the structure and evidence, not merely make the dataset appear orderly.
Quality is demonstrated through controls, not implied by formatting.
Schema integrity Structure
Required fields Completeness
Valid ranges Plausibility
Entity consistency Identity
Temporal logic Time
Duplicate controls Integrity
Documented exceptions Transparency
Versioning & Historical Vintages
The newest dataset should not erase the evidence that came before it.
Some datasets require a recoverable version history so changes in source evidence, corrections, methodology or institutional knowledge remain interpretable later.
V / 01
Source State
Preserve the relevant source evidence or reference.
V / 02
Structured State
Record the dataset after initial transformation.
V / 03
Validated State
Establish a quality-controlled release candidate.
V / 04
Released State
Identify the public or institutional version in use.
V / 05
Historical State
Preserve superseded versions where continuing value exists.
Data Access
Not every dataset belongs in the same access category.
Morganable should distinguish public data from licensed and restricted evidence rather than treating publication as the default for every institutional asset.
Public Data
Data approved for open public access under appropriate publication and reuse terms.
- Public datasets
- Published documentation
- Methodologies
- Data notes
- Approved replication material
Licensed Data
Evidence Morganable may use under conditions that do not permit unrestricted redistribution.
- Third-party licensed datasets
- Restricted redistribution rights
- Commercial data sources
- Institutional-access materials
- Derived outputs where permitted
Restricted Data
Evidence requiring controlled access because of privacy, sensitivity, security, ethics or institutional governance.
- Personal or protected information
- Sensitive source records
- Restricted operational evidence
- Internal validation assets
- Role-controlled institutional data
Connected Evidence Systems
Data becomes more valuable when it can support work beyond itself.
Morganable’s data assets can support journalism, research, longitudinal monitoring, intelligence and institutional retrieval while retaining their own governance and provenance.
Morganable Research
Governed datasets can support systematic inquiry, measurement, testing and reproducible research.
Explore Research →Observatories
Longitudinal datasets can support repeated observation, comparison and historical analysis.
Explore Observatories →ÀṢÀ
Entities, provenance, versions and relationships can become part of a wider institutional knowledge architecture.
Explore ÀṢÀ →Ask Morganable
Approved data assets can eventually support evidence-grounded retrieval and institutional answers.
Explore Ask Morganable → Data Maturity
A dataset must earn its status.
An assembled spreadsheet is not necessarily a governed dataset. Morganable should distinguish stages according to demonstrated structure, validation, documentation, operational use and continuing institutional value.
01
Acquired
Relevant evidence has been obtained but may remain fragmented or close to source form.
02
Structured
Schemas, definitions, transformations and comparable structures have been established.
03
Validated
Appropriate quality controls have been executed and material issues addressed or documented.
04
Operational
The asset is actively supporting intended research, monitoring, publication or analytical work.
05
Enduring
Governance, longitudinal depth, preservation and sustained utility give the dataset continuing institutional value.
Data Governance
Reuse creates obligations.
The more widely a dataset is used, the more important its documentation, rights, corrections and version controls become.
01
Provenance before authority
Important data should retain an intelligible relationship with its underlying evidence.
02
Definitions before comparison
Comparable analysis requires stable and appropriately documented meanings.
03
Validation before promotion
Data should not be described as validated unless relevant controls have actually been completed.
04
Corrections before concealment
Material errors should be corrected transparently with appropriate version history.
05
Rights before release
Possessing data does not automatically create the right to redistribute it.
06
Preservation before overwrite
Historically significant states should remain recoverable where future evidence depends on them.
Data Status
Architecture, validation, publication and maturity are different states.
Morganable’s data portfolio may contain assets at different stages of acquisition, structuring, validation, documentation, operational use and public release. Public descriptions should distinguish those states rather than treating every developing dataset as a completed institutional asset.
Data Institution
Behind the datasets is the infrastructure built to govern them.
Explore Morganable Data Lab for the engineering, governance and reproducibility architecture behind Morganable’s data capability.
Morganable Data Lab Data infrastructure should preserve quality even as
the number of datasets, users and analytical demands increases.
The Data Lab provides the deeper institutional architecture for schemas, validation, provenance, pipelines, documentation, reproducibility and data governance.
Explore the Data Lab → Morganable Data Acquire carefully.
Acquire carefully.
Structure rigorously.
Preserve the evidence.
Morganable Data is designed to turn difficult, fragmented and consequential information into governed evidence assets whose provenance, structure and usefulness can endure beyond the publication or project that first created them.
Morganable
Independent Digital-First Newspaper
Morganable is an independent digital-first newspaper owned by Morganable Media Group, publishing journalism across news, business, entrepreneurship, spotlights, entertainment, sports, lifestyle and opinion for readers in Nigeria, Africa and the wider world.
