B2SAFE is a robust, safe and highly available service which allows community and departmental repositories to implement data management policies on their research data across different geographical and administrative domains in a trustworthy manner. B2SAFE is a way to distribute and store large volumes of data for a long-term to those sites which are providing powerful data processing, analysis and data access facilities. The service operates on the domain of registered data: data objects are made referenceable via globally unique persistent identifiers (PID) which are managed by the corresponding administrative domains.
A distributed service for storing, managing and accessing persistent identifiers (PIDs) and essential metadata (PID records) as well as managing PID namespaces. The implementation of the service relies on the DONA/Handle persistent identifier solution. B2HANDLE can be used by middleware applications, end-user tools and other services to reliably identify data objects over longer timespans and through changes in object location or ownership.
A secure and trusted data exchange service for researchers and scientists to keep their research data synchronized and up-to-date and to exchange with other researchers. An ideal solution to store and exchange data with colleagues and team members, synchronise multiple versions of data and ensure automatic desktop synchronisation of large files.
B2SHARE is a user-friendly, reliable and trustworthy way for researchers, scientific communities and citizen scientists to store and share small-scale research data from diverse contexts. B2SHARE is a solution that facilitates research data storage, guarantees long-term persistence of data and allows data, results or ideas to be shared worldwide. Standard. For the individual researchers who do not have adequate facilities for storing, preserving and sharing data, B2SHARE Service is a customer-facing service which provides a safe repository for scientific data and an easy way to share it in the research community.
B2ACCESS is the EUDAT federated cross-infrastructure authorisation and authentication framework for user identification and community-defined access control enforcement. B2ACCESS allows users to authenticate themselves using a variety of credentials. B2ACCESS service is a customer facing service that provides federated access to the services in a trusted way.
ROHub is a holistic solution for the storage, lifecycle management and preservation of scientific investigations, campaigns and operational processes via research objects. It makes these resources available to others, allows to publish and release them through a DOI, and allows to discover and reuse pre-existing scientific knowledge. ROHub supports scientists and other stakeholders (e.g., companies R&D department directors) throughout the research lifecycle to create and maintain high-quality research objects that can be interpreted and reproduced. Built entirely around the research object concept and inspired by sustainable software management principles, ROHub is the reference platform implementing natively the full research object model and paradigm, which provides the backbone to a wealth of RO-centric applications and interfaces across different scientific communities.
The Advanced geospatial Data Management platform (ADAM) is a tool to access a large variety and volume of global environmental data. User-friendly web viewer and Application Programming Interface (API) allow extracting global as well as local data, from the past, current time, to short term forecast and long-term projections. Most of the data are updated daily to allow users having always fresh data to play with. The data services developed upon ADAM can benefit of full, fast, flexible and effective data-as-a-service platform that boosts any web data solution from micro thematic services to massive data processing services including AI based tools. ADAM facilitates sharing and manipulation of data for data processors, data handling and re-use by managing large volume, need of speed, variety, complexity, diversity, dispersed data sources. ADAM fully supports Open Science communities and initiatives funded under the European Open Science Cloud, including NEANIAS (http://neanias.eu/) and RELIANCE projects (https://www.reliance-project.eu).
The semantic enrichment process is in charge of generating new metadata out of the text content of files or collections of resources as research objects. This metadata comprise the main concepts found in resources containing text, the main knowledge areas in which these concepts are most frequently used, the main expressions, known in computational linguistics as noun phrases, found in the text, and named entities that are further classified in people, organization and places. The core of the semantic enrichment process is expert.ai software. Expert.ai uses a proprietary semantic network, where words are grouped into concepts with other words sharing the same meaning, and the concepts are related between them by linguistic relations such as hypernyms or hyponyms among many others. Therefore, the semantics of the generated metadata is explicit since the concepts are grounded to the semantic network. Information retrieval processes, including search engines and recommender systems, can benefit of working with concepts instead of character strings representing words, mainly to provide a more complete and accurate set of results, and enabling the exploration of file collections by means of facets where the semantic metadata is available.
The recommender system suggests research objects that might be of interest according to user’s research interests. The recommender system follows a content-based approach in the sense that it compares the research object content with the user interest to draw the list of recommended items. This comparison is based on the annotations added by the semantic enrichment process. The user interests are identified from the top concepts in the user’s research objects. These concepts are then compared with the concepts that annotate the research objects in the whole collection. The user interest can be increased by i) adding specific research objects from other users or ii) adding a different scientist. In the former case the main concepts of the research object are added to the user’s interests and in the latter case the scientist interests are added to the user’s interests. The recommender system has a rest API and a web user interface called Collaboration Spheres
The index used by the search service hosts the collection of research objects from the ROHub platform which have been previously enriched. These annotations, added to the original metadata of the research object, are leveraged to produce more accurate results and to provide new facets to explore the research object collection. This index also serves as core for the recommendation api, which returns recommended research objects from this collection. This api aims to improve the exploration of the research object collection hosted by ROHub and to allow the users to make facet and semantic searching over them based on their text content. The index has six facets: Concepts (most frequent concepts mentioned in the text), Expressions (Most relevant phrases or collocations found in the text), Domains (fields of knowledge in which the main concepts are most commonly used), People, Places and Organizations. These facet fields, along the rest of documents hosted by the index, are updated every time a research object is created or updated in ROHub. Each indexed document has attached other related information as the title, the description or the creator, which can be accessed through the API.