The added value of a European Reference Network on rare and complex connective tissue and musculoskeletal diseases: insights after the first 5 years of the ERN ReCONNET.

In order to address the main challenges related to the rare diseases (RDs) the European Commission launched the European Reference Networks (ERNs), virtual networks involving healthcare providers (HCPs) across Europe. The mission of the ERNs is to tackle low prevalence and RDs that require highly specialised treatment and a concentration of knowledge and resources. In fact, ERNs offer the potential to give patients and healthcare professionals across the EU access to the best expertise and timely exchange of lifesaving knowledge, trying to make the knowledge travelling more than patients. For this reason, ERNs were established as concrete European infrastructures, and this is particularly crucial in the framework of rare and complex diseases in which no country alone has the whole knowledge and capacity to treat all types of patients.It has been five years since their kick-off launch in Vilnius in 2017. The 24 ERNs have been intensively working on different transversal areas, including patient management, education, clinical practice guidelines, patients' care pathways and many other fundamental topics. The present work is therefore aimed not only at reporting a summary of the main activities and milestones reached so far, but also at celebrating the first 5 years of the ERN on Rare and Complex Connective Tissue and Musculo-skeletal Diseases (ReCONNET), in which the members of the network built together one of the 24 infrastructures that are hopefully going to change the scenario of rare diseases across the EU.

Enhancing discovery in spatial data infrastructures using a search engine.

A spatial data infrastructure (SDI) is a framework of geospatial data, metadata, users and tools intended to provide an efficient and flexible way to use spatial information. One of the key software components of an SDI is the catalogue service which is needed to discover, query and manage the metadata. Catalogue services in an SDI are typically based on the Open Geospatial Consortium (OGC) Catalogue Service for the Web (CSW) standard which defines common interfaces for accessing the metadata information. A search engine is a software system capable of supporting fast and reliable search, which may use 'any means necessary' to get users to the resources they need quickly and efficiently. These techniques may include full text search, natural language processing, weighted results, fuzzy tolerance results, faceting, hit highlighting, recommendations and many others. In this paper we present an example of a search engine being added to an SDI to improve search against large collections of geospatial datasets. The Centre for Geographic Analysis (CGA) at Harvard University re-engineered the search component of its public domain SDI (Harvard WorldMap) which is based on the GeoNode platform. A search engine was added to the SDI stack to enhance the CSW catalogue discovery abilities. It is now possible to discover spatial datasets from metadata by using the standard search operations of the catalogue and to take advantage of the new abilities of the search engine, to return relevant and reliable content to SDI users.