Desarrollo de una aplicación web de localización en las facultades de la UPV/EHU

En este Proyecto de Fin de Carrera se ha creado la aplicación web FindPlace, así como su web de administración FindPlaceAdmin. La finalidad de FindPlace es poner a disposición del usuario la información sobre las ubicaciones (laboratorios, aulas, despachos, etc.) y detalles acerca del personal de cualquier facultad asociada a la UPV/EHU. FindPlace ha sido implementada con un Responsive Web Design, lo cual permite que la página web se visualice adecuadamente independientemente del dispositivo en el que se represente. Para la consecución de este proyecto se ha seguido una metodología ágil que ha permitido que la idea inicial haya ido evolucionando y adaptándose a las nuevas necesidades surgidas a lo largo del desarrollo.

Desarrollo de servicios para vigilancia tecnológica

[EN]If a frog is placed in boiling water, it will jump out; but if it is placed in cold water that is slowly heated, it will not perceive the danger and will be cooked to death. Without de ability to observe changing environmental conditions, the frog can find itself boiled alive before realizing it is in trouble. This is known as the boiling frog syndrome. In the same manner, it is impossible to be competitive without knowing and being aware of the environmental changes. From here comes the necessity for the Technological Watch and Competitive Intelligence. The main goals of this project are to evaluate the current Technological Vigilance System of the IK4-Tekniker research center and to develop services that help in improving the system. For that purpose, first of all the Technological Vigilance is going to be placed in the business field and its origins are going to be explained. Following that, the Technological Vigilance system of IK4-Tekniker is going to be analyzed for its evaluation. Finally the creation of the services previously mentioned are going to be described in detail, showing the technologies and tools used for that purpose like the Responsive Web Design.

Automatically exposing OpenLifeData via SADI semantic Web Services

Background: Two distinct trends are emerging with respect to how data is shared, collected, and analyzed within the bioinformatics community. First, Linked Data, exposed as SPARQL endpoints, promises to make data easier to collect and integrate by moving towards the harmonization of data syntax, descriptive vocabularies, and identifiers, as well as providing a standardized mechanism for data access. Second, Web Services, often linked together into workflows, normalize data access and create transparent, reproducible scientific methodologies that can, in principle, be re-used and customized to suit new scientific questions. Constructing queries that traverse semantically-rich Linked Data requires substantial expertise, yet traditional RESTful or SOAP Web Services cannot adequately describe the content of a SPARQL endpoint. We propose that content-driven Semantic Web Services can enable facile discovery of Linked Data, independent of their location. Results: We use a well-curated Linked Dataset - OpenLifeData - and utilize its descriptive metadata to automatically configure a series of more than 22,000 Semantic Web Services that expose all of its content via the SADI set of design principles. The OpenLifeData SADI services are discoverable via queries to the SHARE registry and easy to integrate into new or existing bioinformatics workflows and analytical pipelines. We demonstrate the utility of this system through comparison of Web Service-mediated data access with traditional SPARQL, and note that this approach not only simplifies data retrieval, but simultaneously provides protection against resource-intensive queries. Conclusions: We show, through a variety of different clients and examples of varying complexity, that data from the myriad OpenLifeData can be recovered without any need for prior-knowledge of the content or structure of the SPARQL endpoints. We also demonstrate that, via clients such as SHARE, the complexity of federated SPARQL queries is dramatically reduced.