Background
This fourth edition of the ENVRI FAIR School represents another unmissable opportunity to learn about FAIRness in the framework of Research Infrastructures. After dealing with Data FAIRness and Data Management during previous editions, this edition of the school focuses on Services for FAIRness, from their design to their development and publication.
 
Learning Objectives
It is expected that, by the end of the training, participants will be better positioned to:
1. Examine approaches and methodologies to webservices for data;
2. Map tools and their related characteristics;
3. Illustrate potential security threats and related solutions;
4. Design (step by step) data services; 
5. Develop and publish a data service.
 
Contents and Structure
Training Sessions:
1. Overview on the ENVRI project and goals;
2. Design webservices for data;
3. Develop webservices for data;
4. Publish and secure data services by means of APIs;
5. Best practices and lessons learned (experts panel).
 
Target Audience
The resource is aimed at ENVRI data centres staff, RIs representatives, IT experts, researchers and PhD candidates and individuals interested in developing webservices.

Background 

The ENVRI Community International Winter School 2021 'ENVRI-FAIR Resources: Access & Discoverability' focuses on Data FAIRness focuses and covers semantic navigation, Jupyter environments for visualisation and data discovery, resource access tools and cloud computing. Aiming at supporting end users to make the best use of the data, the School establishes the end user perspective as a crucial element to develop good user interfaces and services to interact with data.


Learning Objectives

It is expected that, by the end of the training, participants will be better positioned to:

1. Discuss basic concepts of semantics presenting how they can enrich data resources, enhance FAIRness and foster discoverability of data resources;

2. Examine the full life cycle of an 'on demand' model run and results visualization for the creation of a new data product;

3. Illustrate how resources (datasets, services, workflows) can be created, published and accessed on a metadata catalogue (LifeWatch ERIC Metadata Catalogue);

4. Demonstrate the basic steps to run a legacy application in cloud, develop native cloud applications, automate application deployment and auto-scale a runtime application.


Content and Structure

Training Sessions:

1. Semantics;

2. VREs, Data analysis and Visualization;

3. Resource Access Tools;

4. Cloud computing for developing and operating data management services.


Target Audience

The resource is aimed at data centres staff, RIs representatives, IT experts and individuals interested in data access and discoverability.

Background 

In recent years, one of the major challenges in the Environmental and Earth Science has been managing and searching larger volumes of complex data, collected across multiple disciplines. Many different standards, technologies and common practices have been developed to support each phase of the Data Lifecycle. This training focuses on the creation and reuse of FAIR data and services in the Environmental and Earth sciences.


Learning Objectives

It is expected that, by the end of the training, participants will be better positioned to:

1. Discuss basic concepts of semantics presenting how they can enrich data resources, enhance FAIRness and foster discoverability of data resources;

2. Examine the full life cycle of an 'on demand' model run and results visualization for the creation of a new data product;

3. Illustrate how resources (datasets, services, workflows) can be created, published and accessed on a metadata catalogue (LifeWatch ERIC Metadata Catalogue);

4. Demonstrate the basic steps to run a legacy application in cloud, develop native cloud applications, automate application deployment and auto-scale a runtime application.


Content and Structure

Training Sessions:

1. Semantics;

2. VREs, Data analysis and Visualization;

3. Resource Access Tools;

4. Cloud computing for developing and operating data management services.


Target Audience

The resource is aimed at data centres staff, RIs representatives, IT experts and individuals interested in data access and discoverability.

This section, currently under construction, will contain online courses and learning resources and activities of the E-BIODIVERSITY AND ECOSYSTEM SCIENCES (EBES) Master's Degree. The EBES Master's focuses on the theoretical foundations of biodiversity organization and ecosystem functioning and the issue of eco-informatics, recognizing the biodiversity-ecosystem nexus as an information enterprise, requiring analytical and synthetic capabilities in the generation of services for solving environmental challenge (climate change, emerging ecosystem threats, biodiversity loss, waning natural resources) and the promotion of sustainability.