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How to start a Data Space: framework and guides for implementation.

Redacción — Wed, 24 Jul 2024 14:12:14 +0000

When starting a Data Space, we recommend a couple of resources that will help analyze its feasibility. Moreover, these resources allow us to conduct this analysis in a guided and simple way. Let’s take a look at them.

First and foremost, it’s important to note that a data space only makes sense if there are at least two entities with a use case that requires data sharing. With this premise in mind, we share below two resources we frequently use for the preliminary analysis of data space projects.

The Data Cooperation Canvas

The Data Cooperation Canvas was developed by the consulting firm Braxwell and the city of Amsterdam and is an Open Data resource. At ITELLIGENT, we have translated it into Spanish (download it here). This Data Cooperation Canvas allows you to analyze all the fundamental elements for data cooperation, which are the same elements needed for a Data Space. The creation of the Canvas only requires a high-level analysis, which is suitable for evaluating the feasibility of a Data Space project with a reasonable effort. Additionally, the format of this Canvas (just one page) is particularly useful for presenting the project to potential stakeholders, providing a double benefit.

Data Office Guides

Another fantastic resource is the two guides published by the Data Office (download here). These guides are two Excel files that allow you to answer the different aspects needed to assess the feasibility of a data-sharing use case in a simple and guided way. Once feasibility is confirmed, the second guide helps design the use case.

Use Case Design Guide

Use Case Feasibility Assessment Guide

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ITELLIGENT becomes a new member of the SEGITTUR Smart Destinations Network

Redacción — Wed, 26 Jun 2024 11:15:24 +0000

On June 6th, the Secretary of State for Tourism, Rosario Sánchez, chaired the Plenary Commission of the Smart Tourist Destinations (STD) Network -in spanish, Red de Destinos Turísticos Inteligentes (Red DTI)- in Benidorm, where the incorporation of 45 new members was approved. ITELLIGENT Information Technologies SL was one of the ten companies admitted as members of the STD Network. With these new additions, the STD Network now totals 619 members, of which 440 are destinations, 86 are institutions, 86 are companies, and 7 are international observers.

At ITELLIGENT, we are deeply grateful to the Plenary Commission of the STD Network for approving our company as a member of the STD Network. We are delighted to be part of this great family in the tourism sector. This family now totals 619 members in the STD Network, with 440 destinations, 86 institutions, 86 companies, and 7 international observers.

The Secretary of State for Tourism emphasized in her statement “the growing interest of destinations in joining the STD Network and adopting the Smart Tourist Destinations model, which is helping to improve management by focusing on innovation, sustainability, technology, accessibility, and governance.”

#SolucionesTecnológicasDTI|@ITelligent_IT es empresa de transformación digital y desarrollo de plataforma netITELLIGENT, que permite generación de inteligencia turística a partir de explotación de fuentes de datos y del uso de analítica avanzada (IA y PLN):https://t.co/V1Phr20YUF pic.twitter.com/VOqhqnduZM

— RedDTIturismo (@Red_DTI) June 21, 2024

ITELLIGENT was accepted into the STD Network thanks to its technological solution netITELLIGENT, a platform that enables the generation of tourism intelligence by analyzing diverse data sources and using advanced analytics (Artificial Intelligence and Natural Language Processing). From the obtained data, comparative information about tourism destinations can be developed to analyze the tourist’s journey cycle. This tourist journey is divided into three distinct areas: trip planning, the trip itself, and the tourist’s feedback after the trip.

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Interoperability in Data Spaces: key aspects of Chapter VIII of the Data Act (EU)

Redacción — Mon, 13 May 2024 07:49:40 +0000

Imagine you have multiple technological devices at home: a phone, a computer, and a smart TV. For you to use these devices seamlessly, they need to “speak the same language.” This is what we seek with interoperability: ensuring that data from different sources can be used smoothly and efficiently. This is especially crucial for improving research and developing new products or services.

Chapter VIII of the Data Act (EU) focuses on Interoperability and Data Spaces, and here are the key aspects to understand:

Who is affected?

This chapter is primarily directed at two groups:

Participants in Data Spaces: If you are part of a data space that shares or offers data to others, this part of the law impacts you.
Service Providers: This includes providers of smart contracts and data processing services.

What needs to be done in practice?

Accessible Description: If you participate in a data space, you need to have a clear and public description of the structures and formats of the data you handle.
Interoperability: You must ensure that data-sharing agreements (like smart contracts) are interoperable, meaning they can work well with different systems and technologies.
Requirements for Providers: Providers of smart contracts must ensure that these contracts are executed properly and are resistant to external manipulation.

How does the European Commission help with interoperability?

The Commission has several responsibilities to facilitate interoperability:

Assessment of Barriers: It identifies obstacles that hinder good interoperability and prioritizes which areas need standardization.
Request for Standards: It can ask European standardization organizations to develop harmonized standards.
Common Specifications: If an adequate standard is not achieved, the Commission can introduce common specifications, based on feedback from data innovation experts.

This Chapter VIII of the Data Act is essential to ensure that data can flow and be used without barriers between different systems, fostering a more efficient and productive environment for innovation and the development of new services.

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Data sharing in IoT: what businesses and consumers need to know about the Data Act (EU)

Redacción — Tue, 12 Mar 2024 13:47:19 +0000

The Data Act aims to promote fairness in the digital economy, allowing users to leverage the data generated by connected products they own, rent, or lease. This includes devices such as connected cars, health devices, industrial machinery, and more. The law allows users of these products and related services (like an app to control a washing machine or regulate a refrigerator’s temperature) to access the data they generate. This data can be used to improve services, create new products, and benefit both businesses and consumers.

Chapter II of the Data Act applies to all data generated by the use of connected products or related services that are easily accessible. In this post, we explain six key points that businesses and consumers should know about this European Union law known as the Data Act

What types of data are included?

Included:

Personal and non-personal data
Raw and pre-processed data (information directly from sensors such as temperature, pressure, etc.)

Not included:

Derived or inferred data (like complex analyses)
Multimedia content (such as movies watched on a connected TV)

How does it work in practice?

Users (those who own, rent, or lease a connected product) can:

Access the generated data.
Share this data with third parties.
Request that the manufacturer (data holder) share the data with a third party.

FOR EXAMPLE:

Company with Excavator:** The excavator’s manufacturer is the data holder; the company operating the excavator is the user.

Connected Refrigerator:** The data holder can be both the company that manufactures the refrigerator and the one that offers the app to regulate the temperature.

Data Provision

Data holders must provide clear information about the types of data being generated and allow users easy and free access to this data.

Limitations and Protection

To encourage innovation and protect investment, the Data Act establishes that:

Data cannot be used to develop competing connected products.
There is no obligation to share data with third parties outside the EU.
Personal data can only be shared with a valid legal basis, such as user consent.

Exceptions and Protection of Trade Secrets

To protect trade secrets and ensure security:

Data holders and users can agree on measures to maintain confidentiality.
If these measures are violated, the data holder may suspend the sharing of data.
Refusal to share data must be reported to a competent authority, and the user can challenge this decision.

Some Benefits for Small Businesses: The Data Act is less strict for micro and small businesses, encouraging the development of new products and services based on data.

In summary, Chapter II of the Data Act aims to facilitate access to and sharing of data generated by connected products, while protecting trade secrets and security, and fostering innovation in the IoT market.

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Data Act (EU): seven reasons to understand its impact

Redacción — Tue, 27 Feb 2024 10:53:36 +0000

In recent years, the number of internet-connected products, such as smart devices, has rapidly increased in Europe. This growth generates a large amount of data that can be reused, driving innovation and competitiveness in the EU. The Data Act is a European Union regulation designed to boost the data-driven economy. Its goal is to make data more accessible and usable, promoting innovation and increasing its availability. The law also aims to ensure that the value of data is fairly distributed among all actors in the data economy. Additionally, it specifies who can use certain data and under what conditions.

One of the main benefits of this Data Act (EU) is the “Greater Control for Users,” as it gives individuals and businesses that own or use connected devices more control over the data they generate.

How does this law benefit users and businesses?

Greater Control for Users: It gives individuals and businesses that own or use connected devices more control over the data they generate.
Incentives for Innovation: It maintains incentives for those who invest in data technologies.
Fairness in the Cloud Market: It seeks a fairer and more competitive market for cloud computing services.
Protection against Unfair Contract Terms: It protects businesses, especially small and medium-sized enterprises, against unequal contracts related to data sharing.
Data Access in Emergencies: It allows public entities to request data in exceptional situations, such as during public emergencies.
Data Protection against Foreign Governments: It establishes safeguards to prevent third-country governments from illegally accessing data stored in the EU.
Interoperability: It ensures that data can flow smoothly between different sectors and countries within the EU.

Interoperability is another key benefit of the Data Act (EU), ensuring that data can flow seamlessly between different sectors and EU countries.

When does it come into effect?

The Data Act was published in the Official Journal of the EU on December 22, 2023, and will be applicable starting September 12, 2025. This law complements the Data Governance Act, which aims to build trust in voluntary data-sharing mechanisms. Together, both laws aim to establish a single data market in the EU, preventing duplication and conflicts.

How is the Data Act structured?

The Data Act is organized into several chapters that address specific topics:

Chapter I: General Provisions: Defines the scope of the law and key terms.
Chapter II: Data Sharing in IoT: Allows users of connected devices to access and use the data they generate.
Chapter III: Data Sharing Between Businesses: Sets clear conditions for mandatory data sharing between companies.
Chapter IV: Unfair Contract Terms: Protects businesses against unequal contracts.
Chapter V: Data Sharing with the Government: Allows public entities to access private data in exceptional situations.
Chapter VI: Switching Between Data Services: Facilitates interoperability and switching between cloud computing services.
Chapter VII: Illegal Data Access by Foreign Governments: Protects non-personal data from illegal access by third-country governments.
Chapter VIII: Interoperability: Sets criteria to ensure data flow between sectors and member states.
Chapter IX: Enforcement: Designates competent authorities in each member state to monitor and enforce the law.

The Data Act is a significant step toward creating a single data market in the EU. By establishing clear and fair rules, it fosters innovation and competitiveness, ensuring that the value of data is distributed equitably for the benefit of the European economy and society.

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Discover step by step how a data connector works in a Data Space

Redacción — Tue, 19 Dec 2023 12:52:53 +0000

The main element for interacting with a Data Space is a connector. A data connector allows access to the functionalities offered by a Data Space through a web interface. These data connectors must comply with certain rules to ensure interoperability, meaning the coordinated, secure exchange of data under a standard.

In this post, we will visually explain how to work in a Data Space through the web interfaces that a connector based on the IDSA standard offers us. This data connector has been developed by ITELLIGENT within the framework of a research project.

We assume that the Data Space infrastructure is already operational, and we will see step by step how to interact with it, whether you want to share data with the Data Space (Data Provider) or access third-party data in the Data Space (Data Consumer).

DATA PROVIDER: HOW TO USE THE CONNECTOR TO SHARE OUR DATA WITH THE DATA SPACE

Suppose we have a data source that we want to share through the Data Space (Data Provider), how will we use the data connector for this? We will need to perform the following three steps:

STEP 1. Define the data source to be shared. The first thing we need to do is add the data sources in the Data Space connector.

STEP 2. Establish a Usage Policy. We must establish a Usage Policy for the dataset that we are going to make available to third parties. This can be done through the Data Space connector, which allows us to interact via a web interface. For example, in this video, we show how this data connector works and how to generate a Usage Policy for the data we will offer to the Data Space:

STEP 3. Create the data offer. In this third step, the data offer is created, which will then be available through the Data Space. Here, we show you how to generate the data offer from the data connector:

DATA CONSUMER: HOW TO CONSUME THIRD-PARTY DATA THROUGH A DATA SPACE CONNECTOR

When consuming data, a connector offered by the Data Space is necessary. This data connector has a unique identifier that can control what you do and check everything you do within the Data Space. Once we have an established data connector, we will show how to access third-party data to consume it (Data Consumer).

To do this, we explain how it works in this video:

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Data Spaces: Meaning and Relevance

Redacción — Wed, 26 Jul 2023 10:00:24 +0000

Why are data spaces necessary?

Nowadays, there are sectors where it is essential to share data among different actors within the same sector. A prototypical example of this is customs. At the borders, if data is shared between neighboring countries, not only can effort be reduced by avoiding double checks, but optimal functioning can also be achieved if data is shared. For example, being able to detect a potential veterinary issue early if the entry country knows in advance the load a truck is carrying thanks to the information provided by the exit country.

However, this can also introduce new complexities that must be resolved. Some of them are:

Interoperability. When sharing data, standards must be defined so that both systems or both parties understand the characteristics of the shared data. For example, in the case of customs, it is common to use some of the standards defined by the WCO (World Customs Organization), which, among others, standardizes product or raw material codes.
Data usage. When sharing data, we lose control over it. This can be a problem if the conditions of use of these data are not explicitly stated. For example, in the case of customs, there may be data that the exit country could share with the entry country for a specific purpose, but it may be afraid that the entry country uses them for other purposes.
Security. When sharing data digitally, we are introducing new risks as we open systems to third parties. For example, in a country’s customs system that was only used internally, exposing certain data to third parties can pose a security risk.
Data protection. When sharing sensitive data (e.g., personal data), it is necessary to ensure that the person receiving this data maintains the privacy levels required for the use that will be given to them. In some cases, this involves using anonymization techniques before sharing the data.

What are data spaces?

Data spaces aim to solve the problems that arise when sharing data among different actors. A data space is a way to share data among different actors while ensuring the rights of each participant. The basic idea is to move from data access control to data usage control.

As an example, one of the basic pillars of the European Data Strategy is the creation of common and interoperable data spaces throughout the EU in strategic sectors. The goal is to overcome the barriers (legal, technical, etc.) that currently exist for data exchange, which will undoubtedly enable the implementation of innovative projects on this data and the generation of new businesses and services. To achieve this, it is necessary to implement data infrastructures and governance frameworks to facilitate data pooling and exchange.

KEY TECHNOLOGICAL ELEMENTS IN DATA SPACES

From a technical perspective, a data space can be understood as a collection of technical components that facilitate a dynamic, secure, and continuous flow of data/information between parties and domains. These components can be implemented in many different ways and can be implemented in different runtime frameworks (e.g., Kubernetes). According to Open DEI, they can be classified as follows:

DATA INTEROPERABILITY

The technological building blocks that belong to this category are:

Data models and formats: this basic component establishes a common format for data model specifications and data representation in data exchange payloads. Combined with the basic data exchange API component, this ensures total interoperability between participants.
Data exchange API: this basic component facilitates the exchange and sharing of data (i.e., data provisioning and consumption/use) between data space participants. An example of a data interoperability building block that provides a common data exchange API is the “Context Broker” of the Connecting Europe Facility (CEF), recommended by the European Commission for sharing data at the right time among various organizations.
Data provenance and traceability: this building block provides the means to track and trace in the data provisioning and consumption/use process. Therefore, it provides the basis for a number of important functions, from identifying data lineage to logging auditable transactions. It also enables the implementation of a wide range of application-level tracking use cases, such as product tracking or material flow tracking in a supply chain.

DATA SOVEREIGNTY AND TRUST

The technological building blocks that facilitate data trust and sovereignty are:

Identity Management (IM): the IM basic component enables the identification, authentication, and authorization of stakeholders operating in a data space. It ensures that organizations, individuals, machines, and other actors receive recognized identities, and that these identities can be authenticated and verified, including provisioning of additional information1, for authorization mechanisms to use to enable access control and use. The IM building block can be implemented on the basis of readily available IM platforms that cover parts of the required functionality. Examples of open-source solutions are the KeyCloak infrastructure, the Apache Syncope instant messaging platform, the Shibboleth Consortium’s open-source instant messaging platform, or the FIWARE IM framework. Integration of the IM component with the eID component of the Connecting Europe Facility (CEF), which supports electronic identification of users across Europe, would be particularly important. The creation of federated and trusted identities in data spaces may be supported by European regulations such as EIDAS.
Trusted exchange: this building block facilitates reliable data exchange among participants, assuring participants in a data exchange transaction that the other participants are who they say they are and that they comply with the defined rules/agreements. This can be achieved through organizational measures (e.g., certification or verified credentials) or technical measures (e.g., remote attestation).
Access/use control/policies: this component ensures compliance with data access and use policies defined as part of the terms and conditions established when data resources or services are published (see the “Publication and Services Marketplace” basic component below) or negotiated between providers and consumers. A data provider typically implements data access control mechanisms to prevent misuse of resources, while data use control mechanisms are typically implemented on the data consumer side to prevent misuse of data. In complex data value chains, prosumers combine both mechanisms. Access control and use control are based on identification and authentication.

DATA VALUE CREATION

The technological building blocks that facilitate data value creation are:

Metadata and discovery protocol: this basic component incorporates mechanisms for publishing and discovering data resources and services, making use of common descriptions of resources, services, and participants. Such descriptions can be both domain-independent and domain-specific. They must be enabled by semantic web technologies and include linked data principles.
Data usage accounting: this building block provides the basis for accounting for data access and/or usage by different users. This, in turn, supports important clearing, payment, and billing functions (including data exchange transactions without data market participation).
Publication and services marketplace: To support the offering of data resources and services under defined terms and conditions, markets must be established. This basic component supports the publication of these offerings, the management of processes related to the creation and tracking of smart contracts (which clearly describe rights and obligations for the use of data and services) and access to data and services.

Depending on technical needs, the corresponding backend processes for qualification, clearing, and billing can be executed. Therefore, the building block facilitates the dynamic expansion of data spaces with more stakeholders, data resources, and data analysis/processing services (such as big data analysis services, machine learning services, or statistical processing model services for different business functions). It must include capabilities to publish data resources following the widely accepted DCAT (Data Catalogue Vocabulary) standards, and to gather data from existing open data publishing platforms.

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