Towards personalization in digital libraries through ontologies

In this paper we describe a browsing and searching personalization system for digital libraries based on the use of ontologies for describing the relationships between all the elements which take part in a digital library scenario of use. The main goal of this project is to help the users of a digital library to improve their experience of use by means of two complementary strategies: first, by maintaining a complete history record of his or her browsing and searching activities, which is part of a navigational user profile which includes preferences and all the aspects related to community involvement; and second, by reusing all the knowledge which has been extracted from previous usage from other users with similar profiles. This can be accomplished in terms of narrowing and focusing the search results and browsing options through the use of a recommendation system which organizes such results in the most appropriate manner, using ontologies and concepts drawn from the semantic web field. The complete integration of the experience of use of a digital library in the learning process is also pursued. Both the usage and information organization can be also exploited to extract useful knowledge from the way users interact with a digital library, knowledge that can be used to improve several design aspects of the library, ranging from internal organization aspects to human factors and user interfaces. Although this project is still on an early development stage, it is possible to identify all the desired functionalities and requirements that are necessary to fully integrate the use of a digital library in an e-learning environment

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.This paper has been partially supported by the MESOLAP (TIN2010-14860) and GEODAS-BI (TIN2012-37493-C03-03) projects from the Spanish Ministry of Education and Competitivity. Alejandro Maté is funded by the Generalitat Valenciana under an ACIF grant (ACIF/2010/298)