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This article presents a work-in-progress version of a Dublin Core Application Profile (DCAP) developed to serve the Social and Solidarity Economy (SSE). Studies revealed that this community is interested in implementing both internal interoperability between their Web platforms to build a global SSE e-marketplace, and external interoperability among their Web platforms and external ones. The Dublin Core Application Profile for Social and Solidarity Economy (DCAP-SSE) serves this purpose. SSE organisations are submerged in the market economy but they have specificities not taken into account in this economy. The DCAP-SSE integrates terms from well-known metadata schemas, Resource Description Framework (RDF) vocabularies or ontologies, in order to enhance interoperability and take advantage of the benefits of the Linked Open Data ecosystem. It also integrates terms from the new essglobal RDF vocabulary which was created with the goal to respond to the SSE-specific needs. The DCAP-SSE also integrates five new Vocabulary Encoding Schemes to be used with DCAP-SSE properties. The DCAP development was based on a method for the development of application profiles (Me4MAP). We believe that this article has an educational value since it presents the idea that it is important to base DCAP developments on a method. This article shows the main results of applying such a method.

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This project has been motivated by the need to standardize, preserve, and share the data sets of the Laboratory of Vibrations and Structural Monitoring (ViBest, www.fe.up.pt/vibest) of FEUP, produced by several long term projects individually managed. The solution presented is meant to support the process of Structural Health Monitoring, offering features to catalogue the projects, their goals and components, to store and visualize their acquired and processed data through time, and to preserve the data in a standardized form for all the research unit and extensible to future applications. The result is a digital archive with automatic ingestion of new data files and a Web interface with access control and tools for information management. There is a batch export functionality to deal with large data transfers. It is being used on monitoring data related with different kinds of structural health monitoring applications. The standardization and preservation of all data sets acquired in multiple applications will be certainly a solid basis for further research, either at a local basis or in the context of international joint cooperation.

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Research datasets in the so-called "long-tail of science" are easily lost after their primary use. Support for preservation, if available, is hard to fit in the research agenda. Our previous work has provided evidence that dataset creators are motivated to spend time on data description, especially if this also facilitates data exchange within a group or a project. This activity should take place early in the data generation process, when it can be regarded as an actual part of data creation. We present the first prototype of the Dendro platform, designed to help researchers use concepts from domain-specific ontologies to collaboratively describe and share datasets within their groups. Unlike existing solutions, ontologies are used at the core of the data storage and querying layer, enabling users to establish meaningful domain-specific links between data, for any domain. The platform is currently being tested with research groups from the University of Porto.

Abstract
Most current research data management solutions rely on a fixed set of descriptors (e.g. Dublin Core Terms) for the description of the resources that they manage. These are easy to understand and use, but their semantics are limited to general concepts, leaving out domain-specific metadata. The textual values for descriptors are easily indexed through free-text indexes, but faceted search and dataset interlinking becomes limited. From the point of view of the relational database schema modeler, designing a more flexible metadata model represents a non-trivial challenge because it means representing entities with attributes unknown at the time of modeling and that can change in time. Those traits, combined with the presence of hierarchies among the entities, can make the relational schema quite complex. This work demonstrates the approaches followed by current opensource platforms and proposes a graph-based model for achieving modular, ontology-based metadata for interlinked data assets in the Semantic Web. The proposed model was implemented in a collaborative research data management platform currently under development at the University of Porto. © 2014 ACM.

Abstract