Implementation & IntegrationFrom planning to production: how IST becomes operational.

This section walks through the practical process of implementing IST within a national statistical office (NSO). Beginning with a structured implementation roadmap, NSOs are guided through each phase - awareness, training, pilot deployment, integration, and full-scale production.

You’ll find detailed information on system requirements, installation, and integration options with existing administrative registers, databases, and platforms such as Power BI, QGIS, and REST APIs.

IST is designed with deployment flexibility in mind. It can be hosted on-premises, run entirely in the cloud, or operate in a hybrid setup, adapting to any institutional IT strategy and infrastructure.

Whether you're launching your first pilot survey or migrating dozens of surveys into IST, this section shows how easily IST fits into your existing environment. It also highlights real-life examples of successful implementations across the region, providing practical insights and best practices from Population and Agriculture Censuses, LFS, HBS, CPI and more.

Implementation Roadmap

Implementing IST in a national statistical office is a well-defined, phased process that has been refined through multiple country experiences. The roadmap below outlines how an NSO can move from initial awareness and training to full-scale production across multiple surveys.

The implementation journey typically spans four quarters (Q1–Q4), with each phase focused on building capacity, testing core functionalities, and ensuring integration with existing systems. The process begins with institutional awareness, training, and deployment, then progresses through a limited-scope pilot, followed by full integration, migration, and finally production rollout.

Phased Implementation Overview:

Q1: Preparation & Training

  • Study visit and needs assessment
  • IST installation at NSO premises
  • Introductory training on IST design and functionalities

Q2: Pilot Phase

  • Start of a limited pilot survey
  • Training on SQL Server and SQL for outputs
  • Early-stage integration with national systems
  • Feedback gathering and system refinement

Q3: Expansion

  • Finalization of pilot
  • Definition of testing and deployment processes
  • Rollout of the first official survey in IST

Q4: Consolidation

  • Full migration of existing surveys to IST
  • Advanced training and deeper integration (e.g. with registers, portals, APIs)
  • IST enters production with 20–40 active surveys
This roadmap ensures that NSOs can gradually adopt IST with minimal disruption, supported by training, hands-on testing, and ongoing technical assistance.
IST Implementation Roadmap

System Requirements

IST is designed to be lightweight, modular, and highly adaptable - making it suitable for a wide range of IT environments. Whether an NSO plans to host IST on-premise, in the cloud, or in a hybrid setup, the system is built to ensure consistent performance and security with relatively modest technical requirements.

Deployment Scenarios

IST can be deployed in three common configurations:
  • On-premise: Installed within the NSO’s internal network, often using Windows Server and SQL Server environments.
  • Cloud-based: Hosted on public cloud infrastructure (e.g., Microsoft Azure), enabling remote access, scalability, and centralized backups.
  • Hybrid: Combines local database storage and services with cloud-based access (e.g., CAWI/CAPI with a centralized SQL back-end).
Each deployment type is fully supported by the IST Team and can be tailored to the NSO’s security policies, internet connectivity, and operational capacity.
IST Deployment Options Deployment Options for IST

Minimum Technical Requirements

Component Requirements
Operating System Windows 10/11 (for Desktop) or Windows Server 2016+ (for central servers)
Database Engine Microsoft SQL Server 2016 or later
NET Framework. .NET Framework 4.8 (for IST Desktop and IST WEB apps)
Memory (RAM) Minimum 8 GB (recommended 16+ GB for production servers)
Storage SSD storage recommended; minimum 100 GB for database and backups
Processor Intel i5 or equivalent (recommended: Intel Xeon for servers)
Browser Support Chrome, Edge, Firefox (for IST Web and CAWI components)
Android Devices Android 9.0 or higher (for IST Android CAPI apps)

Recommended Server Configuration (Centralized Installation)

For national-level production environments, the following architecture is recommended:
  • Application Server: Hosting shared folders, application files, and services
  • Database Server: Dedicated MS SQL Server instance with regular backups
  • Data Entry Clients: IST Desktop or web browsers (via IST Web) for data entry and validation
  • Web Server (optional): IIS server for CAWI and administrative portals
Component Requirements
Operating System Windows Server 2016+
Database Engine Microsoft SQL Server 2016 or later
Memory (RAM) Minimum 8 GB (recommended 16+ GB for production servers)
Storage SSD storage recommended; minimum 100 GB for database and backups
Number of Servers 2 virtual servers with minimum 16GB RAM each

Security & Maintenance Considerations

  • Role-based access control is configured via Microsoft SQL Server security roles and groups, ensuring that users only access the parts of the system relevant to their responsibilities.
  • Integration with Active Directory (AD) is supported, allowing user authentication and group management to be centralized within the NSO’s domain environment. This improves access security, simplifies administration, and enables single sign-on for IST Desktop.
  • Windows Scheduled Tasks and SQL Server Jobs are used for automatic database backups, system monitoring, and cleanup of log tables.
• IST Platform can be optionally linked to external services such as:
  • Mail servers – for automatic notifications via MS SQL Servers (e.g. to respondents or administrators)
  • Domain controllers – for unified login credentials

Installation and Deployment

IST is designed for straightforward deployment in national statistical offices (NSOs) with varying IT capacities. Its modular structure allows for flexible installation in single-user, local network, or centralized multi-user environments. Whether hosted on-premise, in the cloud, or in a hybrid setup, the IST Team provides support for each stage of the deployment process.

Deployment Steps

Typical deployment of IST follows a structured process: 1. Initial Configuration
  • Installation of IST Desktop, IST Web, or Android components
  • Creation of shared folders for metadata, data, logs, and system files
  • Configuration of Microsoft SQL Server (users, databases, security roles)
2. Metadata and Database Setup
  • Setup of IST’s metadata database (IST) using default templates
  • Configuration of subject-matter databases for each statistical domain (e.g. LFS2025, HBS2024)
  • Establishment of backup policies and automated SQL Jobs
3. Application (Form) Creation
  • First applications in IST metadata created using sample or imported metadata
  • IST interpreter and therefore all applications defined in the IST metadatabase (Desktop/Web/Android) launched via ProcessStarter launcher app or direct execution
  • Testing of forms, validation rules, reporting procedures
4. User Access and Security
  • Integration with Active Directory for centralized user authentication (optional)
  • Assignment of user roles (admin, data editor, validator, CAWI respondent, etc.)
  • Setup of Windows Scheduled Tasks for nightly jobs (e.g. backups, clean-ups)

Installation Tools

IST interpreter installation is managed through utilities provided by the IST Team:
  • ProcessStarter - a launcher used to initialize specific version (usually the one in production) of IST interpreter for all users across NSO.
  • Metadata Templates – predefined metadata packages that speed up the initial setup of new surveys.
  • SQL Scripts – to initialize databases, configure indexes, and load versioned system procedures.

Time Continuity Support

IST (both, interpreter and metadata database) supports time-based continuity, enabling the system to display data, applications, and functions dynamically according to the selected time reference. This ensures precise historical tracking and context-sensitive data processing.

Application and Time Point Selection in IST

In IST interpreter, the selection of the time point is a fundamental prerequisite for working with metadata. All operations executed within IST interpreter, including metadata management, application launch, and data processing - are tied to the currently selected time point.

IST supports structured versioning logic to manage parallel application versions for different surveys or time periods:
  • Applications, defined by metadata and read by IST interpreter, are time-stamped using VALIDFROM and VALIDTO in metadata
  • New versions of apps developed in IST do not affect older versions or archived data
  • IST versions can be upgraded modularly (Desktop, Web, Android) without interrupting operations
Regular updates and patches are delivered by the IST Team.

Integration with External Systems

IST is designed as an open, interoperable platform that easily connects with a wide range of external systems used in statistical offices. Its modular architecture, metadata standardization, and export-ready outputs allow for secure and efficient interaction with both internal institutional platforms and public-facing services.

Unified Architecture with External Interoperability

As shown in the system architecture diagram (see below), IST provides a centralized processing core, including metadata interpretation, data entry, validation, editing, and output generation - accessible across all collection modes (CAPI, CATI, CAWI, Desktop, Android, and Web). The system also includes utility modules for reporting, backup, logging, and authentication, enabling full operational support.

IST is designed to integrate smoothly with external systems through flexible data exchange mechanisms such as SQL views, shared folders, structured exports, and optional REST-based connections. This allows statistical offices to enable automated reporting, preloading of data from administrative sources, synchronization with registers, and streamlined dissemination - all tailored to their existing infrastructure and security standards.

IST System Architecture IST System Architecture

Integration Use Cases

IST has been successfully integrated with a variety of national systems and tools, including:
  • Active Directory (AD) for centralized authentication of enumerators, supervisors, and administrators
  • VoIP / IPT platforms to support and monitor CATI operations
  • QGIS to enable spatial analysis and visualization of fieldwork coverage and data distribution
  • Intranet Portals for internal publishing of documentation, dashboards, and monitoring tools
  • Mail Servers for sending CAWI login credentials, password resets, and system notifications
  • Custom Export Scripts for generating ready-to-use datasets for post-processing in tools such as SPSS and R
These integrations enable automated workflows, improved user and access management, and timely dissemination of results within a unified statistical infrastructure
IST Integration with QGIS, Arc GIS and Power BI use cases IST Integration with QGIS, Arc GIS and Power BI use cases
IST Integration with QGIS, Arc GIS and Power BI use cases

Supported Systems and Tools

The IST platform can interoperate with the following commonly used tools and services:
  • Authentication: Microsoft Active Directory, LDAPs
  • GIS: QGIS or other WMS-compatible applications
  • Statistical Software: SPSS, R, τ-Argus (via structured export)
  • Communication: Mail servers, VoIP/Softphone systems
  • Dissemination: National open data portals, .Stat Suite
  • BI Tools: Power BI, web dashboards (using IST export formats)
All exports can be automatically generated in standardized formats (Excel, XML, JSON, CSV), with optional header templates and macros.

Data Exchange with Administrative Registers

IST can connect to data from administrative sources (e.g. business registers, civil registries, educational and health databases) through SQL views, linked servers, or API connectors. This allows:
  • Preloading of frames and respondent lists for surveys
  • Use of reference tables to validate IDs or classifications
  • Synchronization of metadata (e.g. economic activity codes, regional structures)
Such integrations support statistical operations while reducing the need for repeated manual input and improve data quality through direct verification.

Interoperability by Design

IST’s open approach ensures that statistical offices are not locked into proprietary ecosystems. Its integrations rely on widely adopted technologies (SQL Server, shared folders, and REST compatibility) making it compatible with national eGovernment and data-sharing frameworks or other interoperability platforms (e.g. such as X-Road / MS BizTalk / IBM ESB based systems).

This ensures that IST can function both as a standalone production environment and as part of a larger institutional IT ecosystem.

Cloud-based Use (Azure)

IST is fully compatible with cloud infrastructure and can be deployed securely and efficiently in environments such as Microsoft Azure. Whether implemented as a fully cloud-hosted platform or as part of a hybrid setup, IST offers national statistical offices (NSOs) a scalable, cost-efficient, and reliable alternative to on-premises infrastructure.

Why Deploy IST in the Cloud?

Deploying IST in the cloud provides several strategic benefits:
  • Scalability: Resources (CPU, memory, storage) can be dynamically allocated based on the size of statistical operations, allowing NSOs to handle large-scale surveys (e.g. censuses) without local hardware bottlenecks.
  • Cost-efficiency: Reduced hardware maintenance and energy consumption; cloud costs align with actual usage.
  • Accessibility: Secure remote access to applications for decentralized teams, CAWI respondents, or regional offices.
  • Disaster Recovery: Built-in backup, replication, and geo-redundancy features available in platforms like Azure.
  • Speed of deployment: Faster setup of test, training, and production environments using virtual machines or containers.

Typical Azure-based IST Deployment Model

An IST deployment in Microsoft Azure typically includes the following components:
IST Component Azure Service Example
IST Application Server Azure Virtual Machines (Windows)
SQL Database Azure SQL Managed Instance or VM-hosted SQL Server
File Storage Azure File Shares or Blob Storage
CAWI Hosting Azure App Services or IIS on Azure VM
Backup & Logs Azure Backup, Azure Monitor
External Access Secured via VPN Gateway or Bastion
IST on Azure – Architecture Layout of Hybrid Setup IST on Azure – Architecture Layout of Hybrid Setup

Security & Access Control

IST on Azure can be integrated with:
  • Azure Active Directory for single sign-on and identity management
  • Role-based access controls (RBAC) to restrict system components
  • Encrypted storage and secure connectivity (VPN/IPSec/SSL)
These features support compliance with data protection frameworks while maintaining operational flexibility.

Use Scenarios

Cloud-based IST is especially suitable for:
  • Temporary large-scale operations such as population or agricultural censuses
  • Regional offices or NSOs without local infrastructure
  • Pilots or cross-border collaborations where fast deployment and remote access are essential
The cloud option is fully compatible with all IST features including metadata-driven setup, data collection, processing, validation, and output table generation.

AI/ML-Ready Architecture: Unlocking the Power of Automation

One of the most transformative innovations introduced during Serbia’s first Fully Digitalized Population Census was the integration of Artificial Intelligence (AI) and Machine Learning (ML) into the IST platform.

Thanks to IST’s modern, cloud-adaptable architecture, built on Microsoft SQL Server and designed with metadata-driven processing, our statistical infrastructure was ready to support advanced analytics from day one. Key architectural advantages included:

  • Minimal preprocessing, reducing delays and complexity
  • Robust data integrity, which minimized the risk of “Garbage In, Garbage Out” (GIGO)
  • Efficient data handling, enabling faster and more reliable ML model performance
These features positioned IST as an AI/ML-ready system, allowing us to apply trained algorithms with confidence and speed.
The automated classification of activities and occupations (NACE/ISCO). The automated classification of activities and occupations (NACE/ISCO)
While in the 2011 census, this task required 200 employees working for two months, the same classification in our modern census was executed in just 10 minutes using ML.

This leap demonstrates not just efficiency gains, but the future potential of combining metadata-driven systems with scalable AI platforms in official statistics.

Best Practices & Case Studies

Over the past decade, IST has been successfully implemented in a variety of national statistical offices (NSOs), each adapting the platform to their institutional context, infrastructure, and survey requirements. This subsection highlights proven best practices and real-world use cases that illustrate how IST supports diverse statistical operations - from censuses to social, price and business surveys.

Common Best Practices

Based on experiences across multiple countries, the following implementation practices have emerged as particularly effective:
  • Start with a Pilot Survey
    Launching IST with a small-to-medium survey (e.g. LFS, HBS) allows for metadata training, validation rule development, and team familiarization before scaling to larger surveys.
  • Use Standardized Metadata Templates
    Reusing and adapting metadata packages across surveys accelerates deployment and ensures consistency in structure, classification, and validation.
  • Establish a Dedicated IST Team
    Creating a cross-functional team with roles for metadata management, validation logic, and database administration increases efficiency and facilitates internal support.
  • Integrate with Existing Registers and Sources
    Linking IST to administrative sources (e.g. business registers, educational databases) improves data quality and reduces respondents burden.
  • Automate Reporting & Logging
    Use IST’s built-in logging, reporting procedures, and scheduled jobs for transparent, traceable workflows that support quality assurance and audit readiness.
  • Combine IST with Complementary Tools
    Extend IST’s functionality and achieve broader GSBPM coverage by linking to tools such as Power BI (dashboards), QGIS (spatial data), τ-Argus (disclosure control), and .Stat Suite (dissemination).

Examples of IST Use in Practice

IST has been applied successfully across a wide range of survey domains and statistical programs, including:
  • Population and Agriculture Census
    Full-scale use of IST Desktop, CAWI, and Android apps for enumeration, with integration to Active Directory, Power BI, ArcGIS, VoIP, QGIS, and central monitoring systems.
  • Labour Force Survey (LFS)
    Monthly and quarterly data collection using structured metadata, logical validation, and output automation.
  • Household Budget Survey (HBS)
    Structured recording of expenditures and incomes using standardized metadata definitions, prefilled records, and batch validation.
  • Consumer Price Index (CPI)
    Integration with local price collection apps and monthly automated reporting via IST output procedures and macro templates.
  • SILC, Business Surveys, Education & Health
    Domain-specific implementations adapted using reusable metadata structures, shared validation logic, and localized classifications.
These experiences demonstrate IST’s flexibility, scalability, and practical value as a statistical production platform -
whether used in a single survey or as the foundation for a national statistical system.

Next segment:

Documentation ⇒