{"id":249096,"date":"2023-07-26T10:00:24","date_gmt":"2023-07-26T10:00:24","guid":{"rendered":"https:\/\/itelligent.es\/?p=249096"},"modified":"2024-07-31T10:36:55","modified_gmt":"2024-07-31T10:36:55","slug":"data-spaces-meaning-and-relevance","status":"publish","type":"post","link":"https:\/\/itelligent.es\/en\/data-spaces-meaning-and-relevance\/","title":{"rendered":"Data Spaces: Meaning and Relevance"},"content":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;4.16&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;Text&#8221; _builder_version=&#8221;4.23&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; hover_enabled=&#8221;0&#8243; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;]<\/p>\n<h2><strong>Why are data spaces necessary?<\/strong><\/h2>\n<p style=\"text-align: justify;\">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.<\/p>\n<p style=\"text-align: justify;\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-12325\" src=\"https:\/\/itelligent.es\/wp-content\/uploads\/data-spaces-netitelligent.jpg\" alt=\"data-spaces-netitelligent\" width=\"635\" height=\"357\" \/><\/p>\n<p>However, this can also introduce new complexities that must be resolved. Some of them are:<\/p>\n<ul>\n<li><strong>Interoperability<\/strong>. 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.<\/li>\n<li><strong>Data usage<\/strong>. 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.<\/li>\n<li><strong>Security<\/strong>. When sharing data digitally, we are introducing new risks as we open systems to third parties. For example, in a country&#8217;s customs system that was only used internally, exposing certain data to third parties can pose a security risk.<\/li>\n<li><strong>Data protection<\/strong>. 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.<\/li>\n<\/ul>\n<h2><strong>What are data spaces?<\/strong><\/h2>\n<p>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.<\/p>\n<p>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.<\/p>\n<h2><strong>KEY TECHNOLOGICAL ELEMENTS IN DATA SPACES<\/strong><\/h2>\n<p>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:<\/p>\n<h2><strong>DATA INTEROPERABILITY<\/strong><\/h2>\n<p>The technological building blocks that belong to this category are:<\/p>\n<ul>\n<li>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.<\/li>\n<li>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 &#8220;Context Broker&#8221; of the Connecting Europe Facility (CEF), recommended by the European Commission for sharing data at the right time among various organizations.<\/li>\n<li>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.<\/li>\n<\/ul>\n<h2><strong>DATA SOVEREIGNTY AND TRUST<\/strong><\/h2>\n<p>The technological building blocks that facilitate data trust and sovereignty are:<\/p>\n<ul>\n<li>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&#8217;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.<\/li>\n<li>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).<\/li>\n<li>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 &#8220;Publication and Services Marketplace&#8221; 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.<\/li>\n<\/ul>\n<h2><strong>DATA VALUE CREATION<\/strong><\/h2>\n<p>The technological building blocks that facilitate data value creation are:<\/p>\n<ul>\n<li>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.<\/li>\n<li>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).<\/li>\n<li>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.<\/li>\n<\/ul>\n<p>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.<\/p>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; admin_label=&#8221;section&#8221; _builder_version=&#8221;4.16&#8243; global_colors_info=&#8221;{}&#8221;][et_pb_row admin_label=&#8221;row&#8221; _builder_version=&#8221;4.16&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; global_colors_info=&#8221;{}&#8221;][et_pb_column type=&#8221;4_4&#8243; _builder_version=&#8221;4.16&#8243; custom_padding=&#8221;|||&#8221; global_colors_info=&#8221;{}&#8221; custom_padding__hover=&#8221;|||&#8221;][et_pb_text admin_label=&#8221;Text&#8221; _builder_version=&#8221;4.23&#8243; background_size=&#8221;initial&#8221; background_position=&#8221;top_left&#8221; background_repeat=&#8221;repeat&#8221; hover_enabled=&#8221;0&#8243; global_colors_info=&#8221;{}&#8221; sticky_enabled=&#8221;0&#8243;] 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 [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":249211,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"off","_et_pb_old_content":"<p style=\"text-align: justify;\"><strong>\u00bfPor qu\u00e9 son necesarios los espacios de datos?<\/strong><\/p>\r\n<p style=\"text-align: justify;\">Hoy en d\u00eda, hay sectores donde es requisito indispensable la compartici\u00f3n de datos entre los distintos actores de un mismo sector. Un ejemplo protot\u00edpico de esto, son las aduanas. En las fronteras, si se comparten datos entre los pa\u00edses lim\u00edtrofes, no s\u00f3lo se puede reducir el esfuerzo, evitando un doble chequeo, sino que adem\u00e1s se puede conseguir un funcionamiento \u00f3ptimo si se comparten datos. Por ejemplo, poder detectar de forma temprana un posible problema veterinario si el pa\u00eds de entrada conoce con antelaci\u00f3n la carga que trae un cami\u00f3n gracias a la informaci\u00f3n facilitada por el pa\u00eds de salida<\/p>\r\n<p style=\"text-align: justify;\"><img class=\"aligncenter wp-image-12325\" src=\"https:\/\/itelligent.es\/wp-content\/uploads\/data-spaces-netitelligent.jpg\" alt=\"data-spaces-netitelligent\" width=\"635\" height=\"357\" \/><\/p>\r\n<p style=\"text-align: justify;\">Sin embargo, esto tambi\u00e9n puede suponer introducir nuevas complejidades que deben ser resueltas. Algunas de ellas son:<\/p>\r\n\r\n<ul style=\"text-align: justify;\">\r\n \t<li style=\"text-align: justify;\"><strong>Interoperabilidad.<\/strong> En el momento en el que se comparten datos hay que definir alg\u00fan tipo de est\u00e1ndares para que ambos sistemas o ambas partes entiendan las caracter\u00edsticas de los datos compartidos. Por ejemplo, en el caso de las aduanas, es com\u00fan utilizar algunos de los est\u00e1ndares definidos por la OMA (Organizaci\u00f3n Mundial de Aduanas), que entre otros, estandariza los c\u00f3digos de los productos o materias primas.<\/li>\r\n \t<li style=\"text-align: justify;\"><strong>Uso de los datos.<\/strong> Al compartir los datos, dejamos de tener el control sobre los mismos. Esto puede ser un problema si no se exponen expl\u00edcitamente las condiciones de uso de dichos datos. Por ejemplo, en el caso de las aduanas, pueden existir datos que el pa\u00eds de salida podr\u00eda compartir con el pa\u00eds de entrada para una finalidad concreta, pero puede que tenga miedo de que el pa\u00eds de entrada los utilices con otros objetivos.<\/li>\r\n \t<li style=\"text-align: justify;\"><strong>Seguridad.<\/strong> Al compartir los datos de forma digital estamos introduciendo nuevos riesgos ya que abrimos los sistemas a terceros. Por ejemplo, en un sistema aduanero de un pa\u00eds que solo era utilizado de forma interna, exponer determinados datos a terceros, puede suponer un riesgo de seguridad.<\/li>\r\n \t<li style=\"text-align: justify;\"><strong>Protecci\u00f3n de datos.<\/strong> Al compartir datos sensibles (por ejemplo. datos personales), es necesario garantizar que, la persona que recibe esos datos, mantenga los niveles de privacidad exigidos para el uso que se les vaya a dar. En algunos casos, esto conlleva utilizar t\u00e9cnicas de anonimizaci\u00f3n antes de compartir los datos.<\/li>\r\n<\/ul>\r\n<p style=\"text-align: justify;\"><strong>\u00bfQu\u00e9 son los espacios de datos o data spaces?<\/strong><\/p>\r\n<p style=\"text-align: justify;\">Los espacios de datos vienen a resolver las problem\u00e1ticas que se producen a la hora de compartir datos entre diferentes actores. Un espacio de datos es una forma de compartir datos entre distintos actores garantizando los derechos de cada uno de los participantes. La idea b\u00e1sica es pasar de un control de acceso de los datos a un control de uso de los datos.<\/p>\r\n<p style=\"text-align: justify;\">Como ejemplo, uno de los pilares b\u00e1sicos de la <a href=\"https:\/\/observatorio-ametic.ai\/aplicaciones-industriales-de-la-ia\/estrategia-europea-de-datos\">Estrategia Europea de Datos<\/a> es la creaci\u00f3n de Espacios de Datos comunes e interoperables en toda la UE en sectores estrat\u00e9gicos. El objetivo es superar las barreras (legales, t\u00e9cnicas, \u2026) que actualmente existen para el intercambio de datos, lo que sin duda permitir\u00e1 la puesta en marcha de proyectos innovadores sobre estos datos y la generaci\u00f3n de nuevas empresas y servicios. Para ello, es necesario poner en marcha las infraestructuras de datos y los marcos de gobernanza para facilitar la puesta en com\u00fan y el intercambio de datos.<\/p>\r\n<p style=\"text-align: justify;\"><strong>ELEMENTOS TECNOLOGICOS CLAVES EN LOS ESPACIOS DE DATOS<\/strong><\/p>\r\n<p style=\"text-align: justify;\"><img class=\"aligncenter wp-image-12353\" src=\"https:\/\/itelligent.es\/wp-content\/uploads\/data-spaces-building-blocks-technologies.jpg\" alt=\"data-spaces-building-blocks-technologies\" width=\"726\" height=\"526\" \/><\/p>\r\n<p style=\"text-align: justify;\">Desde una perspectiva t\u00e9cnica, un espacio de datos puede entenderse como una colecci\u00f3n de componentes t\u00e9cnicos que facilitan un flujo de datos\/informaci\u00f3n din\u00e1mico, seguro y continuo entre partes y dominios. Estos componentes se pueden implementar de muchas maneras diferentes y se pueden implementar en diferentes marcos de tiempo de ejecuci\u00f3n (por ejemplo, Kubernetes). Seg\u00fan <a href=\"https:\/\/www.opendei.eu\/\">Open DEI<\/a>, se pueden clasificar de la siguiente manera:<\/p>\r\n<p style=\"text-align: justify;\"><strong>INTEROPERABILIDAD DE DATOS<\/strong><\/p>\r\n<p style=\"text-align: justify;\">Los bloques de construcci\u00f3n tecnol\u00f3gica que pertenecen a esta categor\u00eda son:<\/p>\r\n\r\n<ol style=\"text-align: justify;\">\r\n \t<li><strong>Modelos y formatos de datos:<\/strong> este componente b\u00e1sico establece un formato com\u00fan para las especificaciones del modelo de datos y la representaci\u00f3n de datos en las cargas \u00fatiles de intercambio de datos. Combinado con el componente b\u00e1sico de las API de intercambio de datos, esto garantiza la interoperabilidad total entre los participantes.<\/li>\r\n \t<li><strong>API de intercambio de datos: <\/strong>este componente b\u00e1sico facilita el intercambio y el intercambio de datos (es decir, la provisi\u00f3n de datos y el consumo\/uso de datos) entre los participantes del espacio de datos. Un ejemplo de un bloque de construcci\u00f3n de interoperabilidad de datos que proporciona una API de intercambio de datos com\u00fan es el \"Context Broker\" (Broker de contexto) del <a href=\"https:\/\/ec.europa.eu\/cefdigital\">Connecting Europe Facility (CEF)<\/a>, recomendado por la Comisi\u00f3n Europea para compartir datos en el momento adecuado entre varias organizaciones.<\/li>\r\n \t<li><strong>Procedencia y trazabilidad de los datos:<\/strong> este bloque de construcci\u00f3n proporciona los medios para rastrear y rastrear en el proceso de provisi\u00f3n de datos y consumo\/uso de datos. Por lo tanto, proporciona la base para una serie de funciones importantes, desde la identificaci\u00f3n del linaje de los datos hasta el registro de transacciones a prueba de auditor\u00edas. Tambi\u00e9n permite la implementaci\u00f3n de una amplia gama de casos de uso de seguimiento a nivel de aplicaci\u00f3n, como el seguimiento de productos o flujos de materiales en una cadena de suministro.<\/li>\r\n<\/ol>\r\n<p style=\"text-align: justify;\"><strong>SOBERANIA Y CONFIANZA DE DATOS<\/strong><\/p>\r\n<p style=\"text-align: justify;\">Los bloques de construcci\u00f3n tecnol\u00f3gica que facilitan la confianza y la soberan\u00eda de los datos son:<\/p>\r\n\r\n<ul style=\"text-align: justify;\">\r\n \t<li><strong>Gesti\u00f3n de identidades (IM):<\/strong> el componente b\u00e1sico de IM permite la identificaci\u00f3n, autenticaci\u00f3n y autorizaci\u00f3n de las partes interesadas que operan en un espacio de datos. Garantiza que las organizaciones, las personas, las m\u00e1quinas y otros actores reciban identidades reconocidas, y que esas identidades puedan autenticarse y verificarse, incluido el aprovisionamiento de informaci\u00f3n adicional1, para que los mecanismos de autorizaci\u00f3n los utilicen para habilitar el control de acceso y uso. El bloque de construcci\u00f3n de IM se puede implementar sobre la base de plataformas de IM f\u00e1cilmente disponibles que cubren partes de la funcionalidad requerida. Ejemplos de soluciones de c\u00f3digo abierto son la infraestructura <a href=\"https:\/\/www.keycloak.org\/\">KeyCloak<\/a>, la plataforma de mensajer\u00eda instant\u00e1nea <a href=\"https:\/\/syncope.apache.org\/\">Apache Syncope<\/a>, la plataforma de mensajer\u00eda instant\u00e1nea de c\u00f3digo abierto del <a href=\"https:\/\/www.shibboleth.net\/\">Shibboleth Consortium <\/a>o el marco <a href=\"https:\/\/github.com\/FIWARE\/catalogue\/tree\/master\/security\">FIWARE IM<\/a>. La integraci\u00f3n del componente IM con el componente eID del\u00a0<a href=\"https:\/\/ec.europa.eu\/digital-building-blocks\/wikis\/display\/DIGITAL\/Digital+Homepage\">Connecting Europe Facility (CEF)<\/a>, que respalda la identificaci\u00f3n electr\u00f3nica de usuarios en toda Europa, ser\u00eda particularmente importante. La creaci\u00f3n de identidades federadas y de confianza en espacios de datos puede estar respaldada por normativas europeas como EIDAS.<\/li>\r\n \t<li><strong>Intercambio confiable:<\/strong> este bloque de construcci\u00f3n facilita el intercambio de datos confiable entre los participantes, asegurando a los participantes en una transacci\u00f3n de intercambio de datos que los otros participantes son realmente quienes dicen ser y que cumplen con las reglas\/acuerdos definidos. Esto se puede lograr mediante medidas organizativas (por ejemplo, certificaci\u00f3n o credenciales verificadas) o medidas t\u00e9cnicas (por ejemplo, atestaci\u00f3n remota).<\/li>\r\n \t<li><strong>Control\/pol\u00edticas de acceso y uso:<\/strong> este componente garantiza el cumplimiento de las pol\u00edticas de acceso y uso de datos definidas como parte de los t\u00e9rminos y condiciones establecidos cuando los recursos o servicios de datos se publican (consulte el componente b\u00e1sico \"Mercado de publicaciones y servicios\" a continuaci\u00f3n) o se negocian entre proveedores y consumidores. Un proveedor de datos normalmente implementa mecanismos de control de acceso a datos para evitar el uso indebido de recursos, mientras que los mecanismos de control de uso de datos normalmente se implementan en el lado del consumidor de datos para evitar el uso indebido de datos. En cadenas de valor de datos complejas, los prosumidores combinan ambos mecanismos. El control de acceso y el control de uso se basan en la identificaci\u00f3n y la autenticaci\u00f3n.<\/li>\r\n<\/ul>\r\n<p style=\"text-align: justify;\"><strong>CREACI\u00d3N DE VALOR DE DATOS<\/strong><\/p>\r\n<p style=\"text-align: justify;\">Los bloques de construcci\u00f3n tecnol\u00f3gica que facilitan la creaci\u00f3n de valor de los datos son:<\/p>\r\n\r\n<ul style=\"text-align: justify;\">\r\n \t<li><strong>Metadatos y protocolo de descubrimiento:<\/strong> este componente b\u00e1sico incorpora mecanismos de publicaci\u00f3n y descubrimiento para recursos y servicios de datos, haciendo uso de descripciones comunes de recursos, servicios y participantes. Dichas descripciones pueden ser tanto independientes del dominio como espec\u00edficas del dominio. Deben estar habilitados por tecnolog\u00edas de web sem\u00e1ntica e incluir principios de datos vinculados.<\/li>\r\n \t<li><strong>Contabilidad del uso de datos:<\/strong> este bloque de creaci\u00f3n proporciona la base para contabilizar el acceso y\/o el uso de datos por parte de diferentes usuarios. Esto, a su vez, respalda importantes funciones de compensaci\u00f3n, pago y facturaci\u00f3n (incluidas las transacciones de intercambio de datos sin la participaci\u00f3n de los mercados de datos).<\/li>\r\n \t<li><strong>Servicios de publicaci\u00f3n y mercado:<\/strong> Para respaldar la oferta de recursos y servicios de datos bajo t\u00e9rminos y condiciones definidos, se deben establecer mercados. Este componente b\u00e1sico admite la publicaci\u00f3n de estas ofertas, la gesti\u00f3n de procesos vinculados a la creaci\u00f3n y el seguimiento de contratos inteligentes (que describen claramente los derechos y obligaciones para el uso de datos y servicios) y el acceso a datos y servicios.<\/li>\r\n<\/ul>\r\n<p style=\"text-align: justify;\">En funci\u00f3n de las necesidades t\u00e9cnicas, se pueden ejecutar los procesos de backend correspondientes para calificaci\u00f3n, compensaci\u00f3n y facturaci\u00f3n. Por lo tanto, el bloque de construcci\u00f3n facilita la ampliaci\u00f3n din\u00e1mica de los espacios de datos con m\u00e1s partes interesadas, recursos de datos y servicios de an\u00e1lisis\/procesamiento de datos (como servicios de an\u00e1lisis de big data, servicios de machine learning o servicios basados \u200b\u200b\u200b\u200ben modelos de procesamiento estad\u00edstico para diferentes funciones comerciales).\u00a0Debe comprender capacidades para publicar recursos de datos siguiendo los est\u00e1ndares DCAT (Data Catalogue Vocabulary) ampliamente aceptados, y para recopilar datos de plataformas de publicaci\u00f3n de datos abiertos existentes.<\/p>","_et_gb_content_width":"","footnotes":""},"categories":[1196],"tags":[1203,1206,1145,1204,1205],"class_list":["post-249096","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-spaces","tag-data-interoperability","tag-data-protection","tag-data-spaces-en","tag-data-usage-policy","tag-data-usage"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Data Spaces: Meaning and Relevance<\/title>\n<meta name=\"description\" content=\"Nowadays, there are sectors where it is essential to share data among the agents within them. 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