Almawave S.p.A.

06/04/2025 | Press release | Distributed by Public on 06/05/2025 08:59

Data dissemination simplified: efficient, accessible, and scalable with DataPortal.AI

Data dissemination simplified: efficient, accessible, and scalable with DataPortal.AI

Artificial Intelligence

4 June 2025

There has never been more data available than there is right now. The great thing about data, though, is that it can be shared and transformed into a common good.

This process is known as data dissemination-the act of distributing or making data accessible to others, whether within an organization, between institutions, or to the wider public.

From internal reports shared among teams to open government data portals available to citizens and businesses, data dissemination plays a crucial role in how we make decisions and solve problems.

However, what are the advantages of disseminating data in today's data-driven world? And with only 48% of high-value datasetsavailable as open data across OECD countries, what are the challenges holding progress back?

This blog explores these questions and highlights how Almawave is working to bridge the gap in data accessibility through its latest product launch, DataPortal.AI, ensuring that valuable information can be shared and utilized to drive better decision-making and boost economic growth to fuel new apps, research, and services.

Why data dissemination matters

Making data accessible comes with real, tangible benefits. It helps:

  • Improve decision-making across sectors: From public health to infrastructure, access to data leads to smarter, evidence-based choices.
  • Increase transparency and accountability: Shared data helps uncover inefficiencies, track progress, and hold institutions to account.
  • Support innovation and research: Open datasets are a resource for startups, researchers, and developers building new solutions.
  • Foster collaboration between institutions: When data flows freely, different departments and organizations can work together more effectively.
  • Empower citizens and communities: Giving people access to information helps them understand, question, and influence decisions that affect their lives.

But perhaps most importantly, data dissemination transforms information into action. When key datasets are shared and effectively applied, they can create tangible value across a wide range of fields.

The benefits of accessible data reach into many critical areas:

  • Public health:Accessible data on diseases, healthcare services, and environmental factors such as air quality can predict outbreaks, improve public health systems, and enhance resource management.
  • Economy and transparency:Open government data, like public budgets and procurement details, helps prevent corruption and promotes transparency. It also allows businesses to make informed investment decisions, encouraging a fairer and more competitive market.
  • Sustainability and the environment:Data on natural resources, pollution, and climate change is vital for shaping policies that drive sustainability. With this data, governments and organizations can take action to mitigate environmental impact and protect future generations.
  • Urban planning and infrastructure:Data on traffic, transportation, and infrastructure performance enables smarter city planning and optimized public services, leading to more efficient and livable urban environments.
  • Democratic participation:Access to data on elections, government policies, and decisions promotes transparency and empowers citizens to engage in the democratic process, holding institutions accountable and making informed choices.

Key challenges in data dissemination

While the benefits of sharing data are clear, putting it into practice is often more complicated. Many organizations and public bodies face similar obstacles when it comes to making their data truly accessible and usable. Some of the main issues include:

  • Data silos- Information is often trapped within individual departments or systems, making it hard to share or combine with other datasets.
  • Outdated or incomplete data- Published datasets are frequently partial, not updated regularly, or lack essential context.
  • Poor discoverability- Even when data is available, it's often hard to find or search for, especially for non-expert users.
  • Limited usability- Many platforms focus only on file downloads, with little to no visualization tools or user-friendly interfaces.
  • Low interoperability- Datasets often use incompatible formats or standards, making integration across tools and platforms difficult.

This results in a huge gap between the potential of public data and its real-world impact. Fixing these issues is key to unlocking the full value of information-and ensuring it can be used to improve services, policies, and outcomes across the board.

Solutions on the market

In the quest to overcome data dissemination challenges, several solutions are available-each with its own set of strengths and weaknesses. These tools and platforms aim to bridge the gap, but choosing the right one depends on specific needs and resources.

  • Custom solutionsTailored to an organization's specific needs, these solutions can offer powerful data visualization and integration features. They provide flexibility and scalability to grow with the data requirements.

    However,custom tools often come with high upfront costs, require ongoing development and maintenance, and can be complex to integrate with other systems. Additionally, they may lack interoperability with certain data formats or standards.

  • Open-source platformsWidely accessible and customizable, open-source platforms can be an excellent option for organizations with limited budgets. They come with many plugins and community-driven features, and often allow for a more hands-on approach.

    While they are cost-effective, these platforms can lack advanced features like intuitive data visualization or real-time updates. They also often require technical expertise for setup and maintenance, and may not be scalable for larger datasets.

  • Commercial off-the-shelf solutionsThese solutions are ready-made and typically come with comprehensive support, advanced features, and integrations with various data sources. They can be quickly deployed, allowing organizations to start using them right away.

    They can however be expensive due to licensing fees, and their features may be too rigid for specific use cases. Additionally, they often come with limited customization, and may not perfectly align with an organization's needs.

Each of these options has a place depending on the organization's goals, resources, and the scale of the data they are working with. The key is to weigh the pros and cons carefully, considering the long-term benefits and potential challenges of each solution.

DataPortal.AI: Built for scalability, transparency, and an exceptional user experience

With over 50 use cases, over onemillion datasets and over onebillion data pointsmanaged all over the world, DataPortal.AI stands out among the solutions developed to tackle these challenges-thanks to its advanced functionalities, high interoperability, and extremely up-to-date and user-friendly UX experience. By treating structured data collected by public entities as a strategic resource, DataPortal.AI significantly increases its value and impact.

DataPortal.AI is the first platform of its kind to leverage generative AI for improving data accessibility and publication efficiency. The integrated conversational assistant is powered by Velvet, Almawave'sproprietary large language model, designed to enhance user interaction.

Born from Sister's 25+ years of experience in the industry, as the fourth generation of a product line (StatPortal, SPOD, StatKit), DataPortal.AI turns raw datasets into accessible and meaningful content with the goal of:

  • Improving transparency and public engagement
  • Making it easier to search for and access relevant information
  • Turning raw data into a meaningful,high qualityand interactive resource
  • Supporting both internal and external collaborationthanks to the adoption of international interoperability standards
  • Breaking down data silosby implementing a single, reliable source of information
  • Reducing the complexity, time, and costsof data dissemination

Potential applications

Thanks to its modular design, the platform can be used in a variety of contexts, such as:

  • Open data portals: To publish and share datasets with the public, enhancing transparency and enabling data reuse.
  • Decision Support Systems (DSS): To provide key stakeholders with data-driven insights that support planning and operational choices.
  • Data hubs: To federate structured data coming from various sources and organizations in one accessible location.
  • Environmental data monitoring: To track environmental indicators in near real time, enabling better management of natural resources and compliance with sustainability goals.
  • Economic data sharing: To support public and private stakeholders with up-to-date information for economic analysis, planning, and policy making.
  • Healthcare observatories: To monitor public health trends, service performance, and demographic needs using reliable, regularly updated data.
  • Statistical dissemination: To present raw statistical data into standardized, accessible, understandable, and interactive formats for broader audiences.
  • Internal and external data sharing: To streamline collaboration between departments or institutions, eliminating silos and enabling consistent access to critical information.
  • Interactive reports and dashboards: To visualize data dynamically, making it easier for users to explore, interpret, and act on key findings.

What sets DataPortal.AI apart

In a landscape where data is abundant but often underutilized, this platform offers a practical, flexible, and future-ready approach to dissemination.

Modular, pick-and-choose structure

Thanks to a modular, pick-and-choose structure, organizations can tailor the platform to their specific needs-whether they're building an open data portal, internal observatory, or interactive dashboard. Each module is designed to integrate seamlessly, reducing the need for multiple tools and simplifying workflows.

The base module enables seamless data integration, an intuitive portal for searching and cataloging, data visualization, and interoperability with other platforms through APIs.

However, additional modules are available to further enhance the platform's capabilities. These include:

  • Open Data: Facilitates the sharing of datasets with the public, ensuring transparency and accessibility.
  • SDMXBI: Supportsadvanced Business Intelligence features andthe implementation of datawarehouse that enablethe exchange of high-quality statistical data and metadata across different platforms, thanks to a standardized ISO Statistical Data and Metadata Exchange protocol used by major statistical organizations worldwide.
  • AI: Integrates LLMs to deliver a conversational assistant that makes user interaction significantly more effective, intuitive, and accessible, along with an automatic multilingual metadata generator that accelerates data documentation and streamlines technical workflows.
  • GeoData: Manages geographical data, enabling location-based insights and mapping functionalities.
  • Data Pipeline: Automates the process of collecting, transforming, and delivering data across systems.
  • Semantic Data Governance: Ensures data quality, compliance, and proper management through semantic technologies.
  • Ontology Based Data Management: managementof access to data definedthrough ontological models.
  • Linked Open Data: Enables the publication of data at the highest quality level for open data-achieving the '5-star' standard.

Easy-to-Use UX

User experience is at the core of the platform's design. The intuitive interface caters to both technical and non-technical users, simplifying the search, management, and sharing of information. The platform supports Progressive Web Apps (PWA) for seamless mobile access and is fully compliant with the latest accessibility standards.

Data visualization

The platform supports advanced data visualization, transforming raw numbers into clear, interactive insights. Whether you're monitoring environmental trends or publishing public reports, the platform helps make data not just available-but understandable.

Built on experience

With over 25 years of experience behind it, the solution is robust, scalable, and ready to evolve alongside the needs of public institutions, businesses, and anyone working to make data accessible and actionable.

New opportunities for economic development

By streamlining publication processes and ensuring data quality, DataPortal.AI not only improves service delivery but also enables new opportunities for economic development and public value creation.

Technological features
The platform is built as a modern, lightweight web application with a secure, scalable, and high-performing architecture designed for long-term reliability.

  • Cutting-edge technologies
    Based on a microservices architecture, up-to-date technologies, using caching and in-memory operations for better performances, multitenancy to host multiple portals in a single installation. The platform is also cloud ready, it supports Docker and is highly scalable to manage huge databases and big data.
  • Multilingual support
    Offers a user-friendly experience in multiple languages, enhancing usability for diverse audiences.
  • High security standards
    Developed in line with the OWASP Web Security Testing Guide to ensure data protection and system integrity.
  • No CMS required
    The platform is ready for cloud deployment and does not rely on any content management systems, making it lighter and easier to manage.
  • Seamless interoperability
    Supports automated data integration via REST APIs based on ISO standard like ODATA and SDMX, manual uploads with a user-friendly web wizard, and harvesting from CSV/XLS file repositories.

Interested in learning more about DataPortal.AI?

Contact us to explore how DataPortal.AI can support your goals

Almawave S.p.A. published this content on June 04, 2025, and is solely responsible for the information contained herein. Distributed via Public Technologies (PUBT), unedited and unaltered, on June 05, 2025 at 14:59 UTC. If you believe the information included in the content is inaccurate or outdated and requires editing or removal, please contact us at support@pubt.io