Lesson 3.3: Interoperability Standards and Protocols

Description: Explain the concept of interoperability and its different dimensions (technical, structural, semantic, organisational) in the context of the QCP.

By the end of this Lesson, you will be able to:

• Explain the concept of interoperability and its different dimensions (technical, structural, semantic, organisational) in the context of the QCP.
• Describe the importance of structured data and data standards as prerequisites for interoperability.
• Identify key interoperability standards and protocols used in the QCP, such as JSON-LD, controlled vocabularies, and APIs.
• Recognise how these standards facilitate seamless data integration and understanding across diverse national systems and the continental platform.
• Appreciate the lessons from international frameworks like the EQF in achieving qualification data interoperability.

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Introduction to interoperability in the QCP context

Defining Interoperability

Interoperability refers to the fundamental ability of different information technology systems, software applications, and networks to communicate, exchange data, and use the information that has been exchanged in a meaningful way. In the context of the ACQF Qualifications and Credentials Platform (QCP), interoperability is not merely a technical feature; it is the cornerstone that enables the platform to achieve its core objectives. It ensures accurate data handling, seamless integration of qualification data from diverse national systems, and reliable verification of credentials across the continent. Without robust interoperability, the vision of a unified African qualifications landscape would remain unattainable on the long-term.

For a continental platform like the QCP, which aims to connect numerous national qualification systems, several dimensions of interoperability are critical:

Technical interoperability: this is the foundational layer, focusing on the ability of systems to connect and exchange data packets. It involves common communication protocols and transport mechanisms (e.g., HTTP, TCP/IP) ensuring that public users, curators and virtual spaces can technically “talk” to the QCP and transmit data.

Example: The Universal Charger (USB-C)

For years, every device had a different charging cable. An old Nokia phone charger couldn’t connect to a Samsung phone, which in turn couldn’t connect to an iPhone. You needed a different cable for everything. This is a lack of technical interoperability.

Nowadays, there is a widespread move towards USB-C as a standard for phones, laptops, and tablets is a perfect example of achieving technical interoperability. Now, one type of cable and plug can physically connect to and transmit power and data with a wide range of devices from different manufacturers.

Structural (syntactic) interoperability: moving beyond basic connectivity, structural interoperability ensures that the structure of the data exchanged is recognisable and usable by the receiving system. For example, in case of an automatic important of a large number of qualifications date to QCP, it focuses on consistent data formats (e.g., JSON, XML) and the syntax of the data, ensuring that the data is organised in a way that can be correctly parsed and interpreted by the QCP. If the QCP receives a data file from a national system but cannot make sense of the field arrangement because it doesn’t follow the expected structure (like the African Learning Model – ALM), this is a breakdown would mean a breakdown in structural interoperability.

Semantic interoperability: this is the highest and most crucial level for the QCP. Semantic interoperability ensures that the meaning of the exchanged data is preserved and understood consistently by all participating systems and users. It involves shared vocabularies, ontologies (formal descriptions of concepts and relationships), data models, and contextual awareness.

For the QCP, this means that when a qualification is described as “Level 5” on the African Continental Qualifications Framework (ACQF) this term has a comparable meaning regardless of which country it originates from. If “Level 5” ACQF qualifications from two different countries represent vastly different complexities or learning outcomes, the QCP would not provide comparable and meaningful data.

Example: Temperature

Suppose you are planning a video call with a colleague in the United States. They say, “It’s a beautiful day, it’s 70 degrees here!”

If you’re in a country that uses Celsius, you would be shocked, as 70°C is as hot as an oven. But they mean Fahrenheit, which is a pleasant 21°C.

You both used the number “70” (the data), and you both understood it was a temperature (the structure), but you had a complete misunderstanding because you weren’t using a shared system of meaning, which is vital for making information truly meaningful and comparable.

Example 2: The ACQF as a “Qualifications Translation Device”

The diagram shows how two different national systems, one with ten levels and another with eight, can be difficult to compare directly. An employer cannot easily know if a ‘Level 7 Diploma’ from the first country is higher or lower than a ‘Level 6 Certificate’ from the second. The ACQF provides the solution by acting as a neutral reference point, much like the central red column in the diagram. Each country maps its national qualifications against the common ACQF standards. Through this process, they might find that both the ‘Level 7 Diploma’ and the ‘Level 6 Certificate’ are equivalent in their learning outcomes to ACQF Level 6. The result is true semantic interoperability; on the QCP, an employer can see that both qualifications represent a comparable level of learning, removing ambiguity and creating trust.

Organisational interoperability: This dimension addresses the alignment of processes, policies, responsibilities, and goals among the various organisations involved to enable effective data sharing and collaboration. For the QCP, this could involve clear agreements of relevant national authorities and agencies (e.g. national qualifications authorities) to mutually trust uploaded qualifications, or, the agreements on the processes and maintenance of ACQF QCP.    

Example: International driving licenses

Suppose you have a valid driver’s license from your home country. However, you can’t just fly to any other country and expect to rent a car with it. The technology is there—you know how to drive a car. The meaning is there—a “driver’s license” means you’re certified to drive.

However, for it to work, countries must have formal agreements to recognise each other’s licensing systems. The International Driving Permit is a result of these agreements. It’s a document that proves your local license is valid, based on the mutual trust and established processes between national authorities.

Importance for ACQF QCP and African Qualifications

Interoperability is paramount for the ACQF QCP to fulfil its mandate of fostering transparency, comparability, and recognition of qualifications across Africa. By enabling seamless data exchange and shared understanding:

• The QCP can effectively process, classify, compare, and visualise information on qualifications originating from diverse national systems, each with its own unique characteristics.
• It supports educational and professional mobility by allowing learners, employers, and institutions to understand and trust qualifications from other African countries.
• It provides a reliable foundation for evidence-based educational planning and policy-making at both national and continental levels.
• It underpins the credibility and usability of the QCP, making it a truly valuable tool for all stakeholders in the African education and training landscape

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The Foundation: Structured data and data standards

Effective interoperability, particularly at the semantic level, is not an isolated achievement. It is built upon a critical foundation of structured data and commonly agreed-upon data standards. Without these foundational elements, attempts to make diverse systems “talk” to each other in a meaningful way are destined to fail.

• Structured data: This refers to data that is organised in a predefined, consistent format, typically in tables with rows and columns, or in formats like XML or JSON with clear tags and hierarchies. This structure allows for efficient processing, querying, and analysis by computer systems. In the context of qualifications, structured data means that information like qualification titles, levels, credits, and learning outcomes are stored in predictable fields rather than as free-form text. Aside from each field being in a machine-readable field, it also means that the machine can understand the relationship between various fields (e.g. a part-qualification belonging to a larger qualification).

• Data standards: These are documented agreements on the representation, format, definition, structuring, tagging, transmission, manipulation, use, and management of data. Data standards ensure consistency, accuracy, and quality in data. For the QCP, adhering to data standards is crucial for ensuring that qualification data from different national sources can be integrated, compared, and verified without ambiguity or errors. The African Learning Model (ALM) serves as a core data standard for the QCP.

You may check Training Unit 5 on Structured Data and Data Standards for more detailed information.

The relationship between these elements forms a causal chain leading to interoperability. Structured data provides the necessary order and predictability for machines to process information. Data standards then overlay this structure with a common language—shared definitions, formats, and rules for interpretation. Only when data is both well-structured and adheres to common standards can different systems begin to exchange it reliably (achieving technical interoperability), parse it correctly (structural interoperability), and, most importantly, understand its intended meaning (semantic interoperability).

Consider a situation without appropriate standardisation and interoperability: if national qualification data were submitted to the QCP in unstructured text documents, or if each country used entirely different field names and definitions for “accreditation” or “achieved learning” with no agreed-upon standard, the QCP would be unable to automatically process, compare, or aggregate this information meaningfully. Comparisons would be manual, error-prone, and incredibly time-consuming, defeating the platform’s purpose. Thus, the commitment to structured data and data standards, such as the ALM, is a non-negotiable prerequisite for the QCP to achieve its continental interoperability goals.

3.3.2 Key standards and protocols for QCP interoperability

To achieve the necessary levels of interoperability, the ACQF QCP leverages several key standards and protocols. These choices are strategic, aiming to balance semantic richness, developer accessibility, and scalability for a continental platform.

Controlled vocabularies

As mentioned previously, controlled vocabularies are essential tools for achieving semantic interoperability within the QCP.

QCP utilises the following controlled lists:

• Accreditation.type (Controlled List of Accreditation Types).

Example: http://data.europa.eu/snb/accreditation/003293d2ce (Institutional License)

• Credit Point.framework (Credit point frameworks)

Example: https://data.acqf-qcp.africa/model/creditpoint-framework/resource/acts (African Credit Transfer System)

• Learning Entitlement Specification.limit national occupation (ESCO Occupations)

Example: http://data.europa.eu/esco/occupation/25206eaa-04da-4fd6-bac7-173d7eb142dc (casting machine operator)

• Learning Opportunity. default language  (Language Named Authority List):

Example: http://publications.europa.eu/resource/authority/language/POR (Portuguese)

• Learning Outcome. related skill (ESCO Skills)

Example: http://data.europa.eu/esco/skill/c7bb240e-4e08-47d2-a4ed-b85185773d3a (polish silverware)

• Location.spatial code (Countries and Territories Authority List):

Example: http://publications.europa.eu/resource/authority/country/MUS (Mauritius)

• Qualification.educational level (ACQF levels, as well as NQFs)

Example: https://data.acqf-qcp.africa/model/acqf-levels/resource/level-1 (Level 1)

• Qualification.thematic area (ISCED-F 2013)    

Example: http://data.europa.eu/snb/isced-f/0110 (Education not further defined)

As you can see, these lists take use of various classification systems. Below, we present the main ones shortly:

ESCO: The European Skills, Competences, Qualifications and Occupations (ESCO) classification is a large-scale, multilingual example of a system to categorize occupations, skills, qualifications, and competences. Originally, it was developed for the European context but it is applicable globally. Its latest version (1.2) has around 14.000 skills linked to 3.000 occupations.

ISCED-F 2013: is a classification system developed by UNESCO to organise education and training programmes and qualifications by their subject matter. It provides a hierarchical structure, moving from broad fields of education and training down to more detailed and specific areas.

APIs (Application Programming Interfaces)

APIs are sets of rules and protocols that allow different software applications to communicate and exchange data with each other automatically. For the QCP, APIs are a crucial mechanism for enabling efficient and scalable data integration from national qualification databases. The platform is designed to support both manual data entry via a Curator Portal and automated data import features, specifically for countries that already have existing, structured digital qualification databases and wish to make them publicly accessible through the QCP.

In this context, an API acts as a secure bridge, allowing a country’s national database to programmatically connect and send its qualification data directly to the QCP. This process enables automated and periodic data uploads, avoiding the reliance on manual data entry, which is more suitable for countries without established digital databases. By using an API, national systems can ensure their data on the continental platform remains synchronised and up-to-date, supporting the QCP’s goal of creating a unified and reliable source of qualifications information that fosters transparency, comparability, and mobility for learners and workers across the continent.

File formatting and extension standards

For systems to exchange data effectively, they must agree on the format in which that data is structured and presented. The choice of file format significantly impacts how easily data can be created, parsed, validated, and understood by different systems.

JSON-LD (JavaScript Object Notation for Linked Data): is a lightweight, modern data format that builds upon the widely used JSON format to support Linked Data principles. Its adoption by the QCP is significant for enabling data to interoperate at a web scale.

In case of countries with an existing structured qualifications database, JSON-LD serves as the preferred format for exchanging qualification data with the QCP. It acts as a bridge between the formally structured African Learning Model (ALM) and the practical needs of web-based data exchange, making it easier for diverse national systems to prepare and share their qualification information.

XML (Extensible Markup Language): While JSON-LD is preferred for its modern web compatibility and ease of use with JSON-based tools, XML has historically been a common standard for structured data exchange. Some legacy systems or other international standards might still use XML. The principles of clear structure and agreed-upon schemas are common to both.

CSV (Comma Separated Values): For bulk data import or simpler datasets, CSV files are often used due to their simplicity. However, CSV inherently lacks the structural and semantic richness of JSON-LD or XML. If data is provided in CSV, it would typically need significant transformation and enrichment to meet the ALM’s requirements for structured, linked data before being integrated into the QCP.

XLSX: Microsoft Excel’s widespread use for data handling is often hampered by poorly structured workbooks, stemming from its flexibility. A “well-structured” Excel file features internal data organisation that supports clarity, analysis, and machine processing, extending beyond its file extension. A well-structured excel file requires  that each variable has its own column, each observation (e.g. a qualification) has its own row and that each value has its own cell (atomic data).

International compatibility

The African Learning Model (ALM) is the core data model underpinning the QCP, defining how qualification information is structured and described. It is designed not only to meet the specific needs of the African context but also with international compatibility in mind, drawing inspiration from and aiming for interoperability with established international models.

For example, the European Learning Model (ELM) provides a comprehensive framework for describing and assessing learning outcomes and qualifications in Europe. By ensuring the ALM incorporates robust ways to describe crucial elements like credit systems, detailed learning outcomes, and relationships within qualifications frameworks (similar to the capabilities enabled by models like ELM), the ACQF QCP can significantly enhance student and worker mobility. This alignment facilitates the transfer and recognition of credits and qualifications across African educational institutions and with other regions. Ultimately, a well-defined and internationally-aware data model like the ALM promotes transparency, supports quality assurance mechanisms, and fosters mutual recognition, which are all vital for achieving greater mobility and cooperation in education and employment across the continent.

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Self-assessment Activity

Diagnosing interoperability challenges

Consider the following scenarios that might occur when working with the ACQF QCP. For each scenario, identify which dimension(s) of interoperability (Technical, Structural/Syntactic, Semantic, Organisational) is primarily affected and briefly explain why.

1. National System A attempts to send its qualification data file to the QCP, but the transmission fails with a “connection refused” error.
2. The QCP receives a data file from National System B. The file is in JSON format, but the QCP system cannot process it because the fields are named differently from what the ALM specifies, and some mandatory ALM fields are missing.
3. The QCP displays “Advanced Diplomas” from Country X and Country Y. Both are listed as “ACQF Level 6.” However, upon closer inspection of their learning outcomes and typical duration, it’s clear that the “Advanced Diploma” from Country X represents a significantly higher level of complexity and learning volume than that from Country Y.
4. The national authority in Country Z has successfully mapped its qualifications to the ALM and prepared a well-structured excel file. However, the staff are unsure about the official procedure for submitting this file to the QCP and who within their agency needs to give final approval before transmission.

As we conclude this module, it is clear that interoperability is the essential thread that weaves together the technical infrastructure and the policy ambitions of the ACQF Qualifications and Credentials Platform. From the foundational ‘handshake’ between systems (technical) to the shared grammar of data (structural), the crucial agreement on meaning (semantic), and the vital framework of human trust and processes (organisational), each layer is indispensable. The standards and protocols discussed—such as the African Learning Model (ALM), controlled vocabularies like ESCO, and data formats like JSON-LD—are the practical instruments we use to build these layers. They are the blueprints that ensure data is not just exchanged, but truly understood across diverse national contexts. Ultimately, the rigorous application of these interoperability principles is what transforms the QCP from a simple database into a dynamic engine for continental integration. It ensures that a qualification’s value is transparent and trusted, whether viewed by a learner in Luanda, an employer in Nairobi, or a university in Accra.