Concept and measurement: the cultural borders of meaning

Paper submitted to the Sixth International Conference on Social Science Methodology, Amsterdam, The Netherlands, August 16-20, 2004.

Overcoming resistance to change in business innovation processes

This paper summarizes the experience gained in dealing with resistance to change appeared in the companies when they develop innovative processes related to the adoption of new technologies, tools, equipment, infrastructure and methodologies. Technological innovation is rapidly absorbed by society on a personal level. But at the enterprise level, resistance to innovation can occur at any hierarchical level of the company and may appear with different intensity. Depending on the type of enterprise, the hierarchical level of the employee, the intensity of resistance and other factors, the measures taken are different. In this paper we summarize our experience in the cataloging of the resistance to innovation in terms of impact on workers and showing how technology education and business training can help overcome these resistance forces. This paper describes the experience acquired over 22 projects deployed in the period 2005 to 2011 and that has affected a total of 264 workers of different cultural, technological, business and hierarchical levels.

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.