Building National Evaluation Evidence Clearinghouses Training Course

Course Introduction

Building national evaluation evidence clearinghouses is a strategic priority for governments seeking to improve the accessibility, credibility, organization, and practical use of evaluation findings in public policy and programme decisions. Government institutions commission evaluations, conduct performance reviews, generate administrative data, and produce research that can inform national development strategies, public expenditure decisions, institutional reforms, and service delivery improvements. However, valuable evidence often remains scattered across ministries, evaluation offices, research institutions, development partners, and implementing agencies. The Building National Evaluation Evidence Clearinghouses Training Course provides public sector leaders, evaluation professionals, knowledge management specialists, and digital government teams with practical approaches for designing, establishing, governing, and sustaining centralized or federated systems that make evaluation evidence discoverable, trustworthy, and useful to decision-makers.

A national evaluation evidence clearinghouse is more than a document repository or searchable website. It is an institutional and technical system for collecting, classifying, preserving, assessing, retrieving, and disseminating evaluation evidence according to consistent standards. Effective clearinghouses enable users to discover relevant evaluations, understand the quality and limitations of findings, compare evidence across programmes and sectors, identify research gaps, and retrieve information for policy formulation and implementation improvement. Participants will examine the core components of a national clearinghouse, including institutional ownership, collection policies, metadata standards, evidence classification, document management, search functionality, quality assessment, publication workflows, user access, and long-term preservation. The course emphasizes the need to align technology decisions with national evaluation policies, institutional mandates, user requirements, and the wider public sector evidence ecosystem.

The development of a successful clearinghouse begins with a clear understanding of the evidence landscape and the needs of its intended users. Policymakers may require concise summaries of findings relevant to current decisions, while evaluators need detailed reports, methodological documentation, and information about evaluation designs. Researchers may prioritize advanced search, citation details, datasets, and links to related studies, whereas programme managers may seek actionable recommendations and evidence about implementation effectiveness. Participants will learn how to conduct stakeholder assessments, map existing repositories, identify evidence gaps, define collection priorities, and develop user-centered information architecture. They will explore how controlled vocabularies, taxonomies, standardized metadata, subject classifications, geographic identifiers, and consistent indexing practices can improve discovery and comparison across evaluations produced by different institutions.

Credibility and trust are central to national evaluation evidence infrastructure. A clearinghouse must communicate not only what an evaluation found but also how the evidence was generated, what questions were examined, which methods were used, and what limitations affect interpretation. Participants will examine practical approaches for assessing document completeness, methodological transparency, relevance, independence, and quality without confusing repository inclusion with formal endorsement of every finding. The course addresses procedures for validating submissions, documenting sources, distinguishing completed evaluations from preliminary research, managing conflicting evidence, and communicating limitations. It also considers publication permissions, intellectual property, confidentiality, personal data protection, accessibility requirements, and the appropriate treatment of sensitive reports. Participants will learn how governance arrangements can support transparency while respecting legal obligations and legitimate restrictions on information access.

Digital transformation is creating new opportunities to make national evaluation evidence more searchable, interconnected, and useful. Modern clearinghouses can incorporate full-text search, semantic retrieval, automated metadata extraction, machine-assisted classification, multilingual discovery, evidence maps, geospatial filters, and links to related policies or programmes. Artificial intelligence can help users summarize long reports, identify recurring findings, extract recommendations, and discover related studies, provided that outputs remain traceable to source documents and are subject to appropriate validation. The course explores the design of interoperable platforms, application programming interfaces, digital preservation systems, accessibility features, and analytics for understanding user needs. It also addresses risks involving inaccurate automated summaries, biased classifications, cybersecurity, unreliable metadata, obsolete links, and unequal access to digital services. Participants will consider how to introduce these capabilities responsibly within realistic technical and budgetary constraints.

By completing the programme, participants will be equipped to develop a national evaluation evidence clearinghouse strategy that combines institutional governance, sustainable financing, information architecture, metadata standards, quality assurance, digital infrastructure, and active evidence dissemination. They will learn how to move from fragmented collections toward an organized national evidence resource that supports policy learning, programme improvement, evaluation planning, and evidence-informed public investment. Through practical exercises, system design activities, and a capstone project, participants will develop a phased implementation roadmap covering stakeholder engagement, platform requirements, collection procedures, data governance, quality controls, user adoption, performance measurement, and long-term sustainability. The programme supports governments seeking to strengthen institutional memory, reduce duplication of research, improve evidence accessibility, and increase the practical influence of evaluation findings on public decisions.

Duration

10 days

Who Should Attend

• Directors and senior officials of national evaluation offices responsible for coordinating evaluation systems, disseminating findings, and strengthening evidence use across government.

• Officials in ministries of planning, finance, public administration, and national development responsible for evidence infrastructure and policy learning.

• Government monitoring, evaluation, and learning professionals who manage evaluation reports, evidence registers, research outputs, and institutional knowledge resources.

• Cabinet secretariat and executive policy support professionals seeking reliable access to evaluation findings for decision briefs, policy submissions, and government-wide reviews.

• Knowledge management directors and information management specialists responsible for organizing institutional research, technical reports, and evidence repositories.

• Digital government leaders and IT professionals designing public sector information platforms, searchable databases, digital libraries, and interoperable government systems.

• Research and evaluation institute professionals responsible for publishing, indexing, preserving, and disseminating programme evaluations and policy research.

• Government statisticians, economists, and policy analysts who need to discover, compare, and synthesize evaluation evidence across sectors and jurisdictions.

• University research managers and academic library professionals supporting collaboration between government evaluation systems and national research infrastructure.

• Development partner and international organization professionals supporting national evaluation capacity, knowledge sharing, evidence use, and public sector reform.

• Public sector librarians, archivists, documentation officers, and records management professionals responsible for digital preservation and institutional information governance.

• Data governance, cybersecurity, and privacy specialists responsible for information access policies, data protection, metadata integrity, and secure evidence sharing.

• Sector ministry officials working in health, education, agriculture, infrastructure, climate, social protection, governance, and other fields that generate substantial evaluation evidence.

• Procurement and contract management professionals responsible for commissioning evaluation studies and ensuring that deliverables meet repository submission and documentation requirements.

• Consultants and institutional development advisers supporting the design, implementation, modernization, and sustainability of national evidence clearinghouses.

Course Objectives

• Develop an advanced understanding of national evaluation evidence clearinghouses, including their strategic purpose, institutional role, technical components, and contribution to evidence-informed government.

• Design a national clearinghouse strategy that aligns collection priorities, governance arrangements, technology choices, user needs, and dissemination practices with national evaluation and development objectives.

• Conduct evidence landscape assessments to identify existing repositories, institutional data sources, evaluation collections, information gaps, duplication risks, and opportunities for integration.

• Develop metadata standards, controlled vocabularies, classification systems, and document indexing procedures that improve the consistency, discoverability, and comparability of evaluation evidence.

• Establish submission, validation, cataloguing, quality review, publication, updating, and preservation workflows for evaluation reports and related documentation.

• Apply practical approaches for documenting evaluation methods, findings, recommendations, limitations, source provenance, and quality assessments without misrepresenting the strength of available evidence.

• Design user-centered information architecture, search interfaces, filtering mechanisms, multilingual discovery features, and accessibility provisions that support different categories of evidence users.

• Evaluate suitable digital platform architectures, repository software, interoperability standards, application programming interfaces, and hosting arrangements for national-scale evidence infrastructure.

• Assess responsible applications of artificial intelligence, semantic search, automated metadata extraction, machine-assisted classification, and evidence summarization while maintaining source traceability and human validation.

• Establish data governance, intellectual property, privacy, cybersecurity, publication rights, records retention, and access control arrangements appropriate to public sector evaluation evidence.

• Develop sustainable financing, institutional ownership, operating procedures, partnership arrangements, and capacity-building plans to support long-term clearinghouse performance.

• Create a practical implementation roadmap with measurable indicators for evidence coverage, metadata quality, search effectiveness, user engagement, accessibility, system reliability, and contribution to evidence use.

Comprehensive Course Outline

Module 1: Foundations of National Evaluation Evidence Clearinghouses

• Examine the purpose and strategic value of national clearinghouses in organizing evaluation findings, preserving institutional knowledge, supporting public accountability, and improving policy decisions.

• Distinguish evidence clearinghouses from general document repositories, academic databases, government statistical portals, research libraries, evaluation registers, and systematic review databases.

• Analyze common barriers to evidence accessibility, including fragmented collections, inconsistent documentation, weak metadata, inaccessible reports, duplicated studies, and limited dissemination.

• Define the essential functions of a national clearinghouse, including evidence collection, cataloguing, quality information, discovery, access management, preservation, and user support.

Module 2: National Evidence Landscape Assessment and Stakeholder Mapping

• Map evaluation evidence sources across ministries, independent evaluation offices, local governments, public agencies, research institutions, universities, development partners, and implementing organizations.

• Identify existing digital repositories, document management systems, evaluation registers, research databases, and knowledge platforms that could be integrated or linked.

• Assess user needs through stakeholder interviews, workflow analysis, information-seeking studies, surveys, and consultations with policymakers, evaluators, researchers, and programme managers.

• Develop a national evidence landscape report identifying coverage gaps, duplicate collections, institutional constraints, priority users, integration opportunities, and recommended clearinghouse functions.

Module 3: Institutional Governance, Ownership, and Operating Models

• Compare centralized, federated, distributed, and hybrid clearinghouse models and assess their suitability for different national administrative structures and institutional capacities.

• Define institutional ownership, executive sponsorship, operating responsibilities, submission authority, technical administration, quality assurance, and user support arrangements.

• Establish governance committees, technical working groups, editorial responsibilities, escalation procedures, and coordination mechanisms for participating institutions.

• Develop institutional agreements covering participation, document submission, publication permissions, data exchange, service expectations, accountability, and long-term system stewardship.

Module 4: Evidence Collection Policies and Submission Workflows

• Develop collection policies defining eligible evaluation materials, priority sectors, publication requirements, minimum documentation standards, and criteria for inclusion.

• Design submission workflows covering document receipt, completeness checks, metadata capture, rights verification, quality information, approval, publication, and subsequent updates.

• Establish practical procedures for collecting both published and unpublished evaluations while distinguishing final reports, inception reports, working papers, evaluation summaries, and supporting datasets.

• Develop submission agreements and institutional compliance measures that encourage timely deposit of evaluation outputs generated through public expenditure, government programmes, and externally supported initiatives.

Module 5: Metadata Standards, Taxonomies, and Evidence Classification

• Design metadata schemas covering evaluation title, commissioning institution, implementing organization, publication date, geography, sector, programme, methods, findings, and source identifiers.

• Develop controlled vocabularies and taxonomies for policy domains, intervention types, target populations, evaluation approaches, development objectives, and outcome categories.

• Establish consistent identifiers, date formats, geographic codes, institutional names, versioning practices, and terminology standards that support reliable indexing and comparison.

• Examine relevant metadata and interoperability standards and determine how to adapt them to national requirements without creating unnecessary complexity for contributing institutions.

Module 6: Evaluation Quality Information and Evidence Credibility

• Establish procedures for documenting methodological approaches, evaluation questions, study designs, sampling, data sources, analytical methods, limitations, and disclosed conflicts of interest.

• Distinguish repository completeness checks, methodological appraisal, independent peer review, and formal endorsement to avoid implying that all indexed findings have undergone equivalent scrutiny.

• Develop transparent quality information fields that help users understand the relevance, strengths, limitations, and appropriate interpretation of each evaluation.

• Design procedures for correcting metadata errors, managing disputed records, linking updated reports, documenting retractions where necessary, and preserving a transparent record of changes.

Module 7: Information Architecture, Search, and User Experience

• Design information architecture that allows users to navigate evidence by sector, institution, geography, intervention, target population, evaluation method, date, and policy objective.

• Develop advanced search and filtering functions that support full-text retrieval, structured queries, sorting, saved searches, related documents, and discovery of evidence gaps.

• Apply user-centered design methods to simplify evidence discovery for senior officials, analysts, evaluators, researchers, and members of the public with different levels of technical expertise.

• Establish accessibility, mobile usability, multilingual discovery, plain-language navigation, and inclusive design practices that broaden equitable access to evaluation findings.

Module 8: Digital Platform Architecture and Interoperability

• Evaluate repository software, content management systems, search technologies, hosting options, storage requirements, and deployment models for a national-scale evidence platform.

• Design interoperability arrangements using documented APIs, metadata exchange, persistent identifiers, standardized formats, and links to existing institutional repositories.

• Examine integration with government portals, statistical systems, policy databases, digital libraries, research platforms, and institutional document management systems.

• Develop technical requirements covering performance, scalability, backup, disaster recovery, system monitoring, software maintenance, and long-term migration between platforms.

Module 9: Artificial Intelligence, Semantic Search, and Automated Evidence Processing

• Assess applications of natural language processing and machine-assisted metadata extraction for identifying evaluation characteristics, classifying documents, and reducing manual cataloguing effort.

• Explore semantic search and retrieval approaches that help users find conceptually related evaluations even when terminology, language, or sector classifications differ.

• Evaluate AI-assisted summarization, recommendation systems, and extraction of findings or recommendations while maintaining direct links to source passages and original reports.

• Establish safeguards for hallucination, biased classification, incomplete extraction, multilingual errors, source misrepresentation, and overreliance on automated outputs through human verification and auditability.

Module 10: Data Governance, Privacy, Security, and Publication Rights

• Establish data governance policies defining ownership, access permissions, publication status, retention, correction procedures, information sharing, and accountability for repository content.

• Assess copyright, intellectual property, licensing, confidentiality, privacy, consent, and legal restrictions affecting the publication or reuse of evaluation reports and associated datasets.

• Develop cybersecurity controls covering authentication, role-based access, secure hosting, encryption where appropriate, vulnerability management, backups, and incident response.

• Establish differentiated access arrangements for public reports, restricted administrative materials, sensitive evaluations, and confidential datasets while preserving the greatest lawful transparency.

Module 11: Evidence Synthesis, Thematic Collections, and Research Gap Mapping

• Develop thematic evidence collections that organize evaluations around national development priorities, government strategies, cross-sector challenges, and major public expenditure programmes.

• Establish procedures for identifying overlapping studies, comparing evaluation findings, documenting conflicting conclusions, and linking related evaluations across institutions and periods.

• Examine how evidence maps, systematic evidence reviews, research gap analyses, and structured summaries can help policymakers identify what is known and where further evaluation is required.

• Distinguish evidence indexing and discovery from formal evidence synthesis, ensuring that comparative claims are supported by appropriate analytical methods and clearly documented sources.

Module 12: Dissemination, Knowledge Translation, and Evidence Utilization

• Design dissemination strategies for cabinet offices, ministries, evaluation units, programme managers, researchers, local governments, development partners, and public accountability institutions.

• Develop executive summaries, policy briefs, thematic digests, searchable evidence collections, and user guidance that make evaluation findings more accessible to non-specialist audiences.

• Establish mechanisms for connecting clearinghouse resources to policy formulation, budget preparation, programme redesign, evaluation planning, and institutional learning processes.

• Develop user engagement activities, training programmes, newsletters, webinars, communities of practice, and targeted communication approaches that encourage repeated and meaningful use of evidence.

Module 13: Digital Preservation, Records Management, and Long-Term Access

• Establish preservation policies for digital reports, associated appendices, methodological documentation, supporting datasets, and other materials necessary for future interpretation.

• Develop procedures for file format management, version control, persistent identifiers, backup verification, metadata preservation, and migration from obsolete digital formats.

• Examine archival requirements, records retention obligations, authenticity controls, and documentation practices that maintain the integrity and provenance of stored evidence.

• Create continuity plans addressing technology obsolescence, institutional restructuring, funding interruptions, platform replacement, and the long-term stewardship of national evaluation records.

Module 14: Financing, Procurement, and Sustainable Clearinghouse Operations

• Develop lifecycle cost estimates covering platform development, hosting, software support, staffing, metadata preparation, digitization, security, maintenance, training, and user engagement.

• Compare financing approaches including government budget allocations, shared institutional contributions, development partner support, pooled technical services, and phased implementation.

• Establish procurement requirements for platform selection, development services, technical support, hosting, accessibility, interoperability, cybersecurity, and service-level agreements.

• Develop sustainability plans covering staffing, operational ownership, recurrent financing, vendor dependency, system upgrades, performance monitoring, and succession of technical responsibilities.

Module 15: Monitoring Clearinghouse Performance and Continuous Improvement

• Define indicators for collection coverage, document completeness, metadata accuracy, search success, platform availability, response times, accessibility, and user satisfaction.

• Develop analytics for understanding search behavior, frequently accessed topics, unsuccessful queries, user journeys, evidence demand, and patterns of engagement with clearinghouse resources.

• Establish feedback mechanisms and periodic user research to identify information gaps, improve search relevance, simplify workflows, and strengthen the usefulness of published evidence.

• Conduct regular governance, technical, content quality, cybersecurity, and sustainability reviews to ensure that the clearinghouse remains reliable, relevant, secure, and aligned with national needs.

Module 16: National Clearinghouse Design Capstone and Implementation Roadmap

• Develop a prototype national clearinghouse concept specifying user groups, institutional governance, collection scope, metadata standards, search requirements, and integration priorities.

• Prepare a sample evaluation submission workflow covering document validation, metadata capture, quality information, publication permissions, indexing, and ongoing record maintenance.

• Conduct a simulated evidence discovery exercise using a defined policy question to test search functionality, source traceability, relevance, and the clarity of retrieved evidence.

• Present a phased implementation roadmap covering governance approval, technical development, pilot institutions, financing, capacity building, performance indicators, risk management, and national rollout.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue 

The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.

Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment:

Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.