There are no prerequisites, but it is recommended to have passed the course Statistical Data Analysis.

The aim of the course is to know the theoretical foundations and the basic concepts related to the metric studies of the information, as well as the methodology for its realization and the practical aspects that allow to propose analyses using the appropriate indicators and interpreting and contextualizing the results. Students will need to acquire a range of basic and transversal skills, as well as specific ones. Basic and transversal: Basic skills tahta llow them to collect and understand data relevant to making judgements, including scientific, social and ethical reflections, To know the models and methods of research in the area of digital information and the basic methodology of research of sources, analysis and understanding to achieve the integration of knowledge in academic work. Have the ability to organize and plan their work, taking the right decisions based on available information, gathering and interpreting relevant data to make judgments and critical thinking. Specifics: To apply knowledge of statistics and quantitative analysis of information. To understand and apply the main indicators of the metric studies of information, as well as of the economic and statistical area

K1: Know the principles and values of democracy and sustainable development, in particular, respect for human rights and fundamental rights, gender equality and non-discrimination, the principles of universal accessibility and climate change. K3: Identify and analyze research methodologies and sources to develop academic work in the field of digital information management K4: Understand and apply the fundamental theories, instruments and techniques to manage information in digital media, covering its organization, control, communication and preservation K5: Know the fundamental theories, instruments and techniques for managing information in digital media, covering its organization, control, communication and preservation K7: Understand the fundamentals of statistics and quantitative analysis to interpret data, as well as the appropriate techniques for their collection and processing, understanding different structures, social contexts and user needs. S1: Plan and organize teamwork by making correct decisions based on available information and gathering data in digital environments. S2: Use the information by interpreting relevant data, avoiding plagiarism, and in accordance with the academic and professional conventions of the area of study, being able to evaluate the reliability and quality of said information. S3: Apply digital information management principles in different organizational environments, ensuring effective communication of processes and results to stakeholders. S5: Be able to design, manage, and operate with information through database systems, demonstrating skill in information retrieval and the use of query languages to meet complex information needs. S6: Be able to collect, process, cleanse and aggregate data by understanding the needs of users and organizations and how they need them. S7: Experiment with data visualization tools to represent information intuitively, properly presenting the results to different types of audiences. S8: Develop skills in the creation of digital content and multimedia editing by applying usability principles. S10: Apply statistical analysis techniques and metric studies to evaluate and measure the impact of data in digital environments. S12: Be able to advise on the definition of strategy and project management regarding tracking, indexing, content structuring, link building, etc C1: Know and be able to manage interpersonal skills on initiative, responsibility, conflict resolution, negotiation, among others, which are required in the professional field. C2: Be able to apply knowledge in a professional way in solving specific digital information management problems using the tools and techniques learned in the academic field C3: Demonstrate ability in the development and execution of digital content projects autonomously working in multidisciplinary teams. C4: Capacity for continuous autonomous learning that facilitates adaptation to new situations and the updating of knowledge in the field of digital information.

1. introduction to the course. 2. Introduction to information metric techniques: basic concepts, definitions, objectives and links with other disciplines. 3. Analysis of the models involved in scientific communication. 4. Analysis of the regularities observed in the production and consumption of information. 5. Data sources for metric information studies. 6. Methodological aspects of metric information studies: indicators and technological tools. 7. Applications of information metric techniques in different environments of research, innovation and management.

- Acquisition of theoretical and practical knowledge (3 ECTS) through theoretical classes, teaching materials prepared by the teacher, online tutorials, specialized readings and commentary on the readings, as well as students' personal study. - Acquisition of skills and abilities (3 ECTS) in practices in which the knowledge acquired will be applied to analyse the regularities of the production and consumption of scientific information and scientific communication models through the critical use of indicators and their interpretation.