| Study programme competencies |
| Code | Study programme competences |
| A1 | CE1 - Know and understand the theoretical and methodological principles of information and documentation management to apply them in their professional activity |
| A8 | CE8 - Master the different methods of representation of data, information and knowledge that ensure efficient recovery |
| A13 | CE13 - Know and master the techniques and regulations for the creation and authentication, meeting, selection, organization, representation, preservation, recovery, access, dissemination and exchange, and evaluation of resources and information services |
| A16 | CE16 - Master and use criteria and indicators for the evaluation of products and services of information including metrics and qualitative studies |
| A20 | CE20 - Master the bases to develop research activities using multidisciplinary methods and principles |
| A21 | CE21 - Possess knowledge of statistics and quantitative analysis of information |
| A22 | CE22 - Acquire computational skills and management of new ICT |
| B1 | CB1 - Possess and understand knowledge that provides a basis or opportunity to be original in the development and / or application of ideas, often in a research context |
| B2 | CB2 - Apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of study |
| B3 | CB3 - Be able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments |
| B4 | CB4 - Know how to communicate their conclusions -and the knowledge and ultimate reasons that sustain them- to specialized and non-specialized audiences in a clear and unambiguous way |
| B5 | CB5 - Possess the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous |
| B6 | CG1 - Capacity for cooperation, teamwork and collaborative learning |
| B7 | CG2 - Capacity for reflection and critical reasoning |
| B8 | CG3 - Capacity for planning, organization and management of resources, information and operations |
| B9 | CG4 - Capacity for analysis, diagnosis and decision making |
| B10 | CG5 - Ability to work in an international and global context |
| B11 | CG6 - Ability to understand the importance, value and function of the Digital Information and Documentation Management in the current ICT society |
| C1 | CT1 - Express correctly, both orally and in writing, in the official languages ??of the autonomous community |
| C2 | CT2 - Use the basic tools of information and communication technologies (ICT) necessary for the exercise of their profession and for learning throughout their lives |
| C3 | CT3 - Develop oneself for the exercise of a citizenship that respects democratic culture, human rights and the gender perspective |
| C4 | CT4 - Understand the importance of the entrepreneurial culture and know the means available to entrepreneurs |
| C5 | CT5 - Acquire skills for life and habits, routines and healthy lifestyles |
| C6 | CT6 - Develop the ability to work in interdisciplinary or transdisciplinary teams, to offer proposals that contribute to a sustainable environmental, economic, political and social development |
| C7 | CT7 - Assess the importance of research, innovation and technological development in the socio-economic and cultural progress of society |
| C8 | CT8 - Have the ability to manage time and resources: develop plans, prioritize activities, identify criticisms, establish deadlines and comply with them |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| To know the main concepts, aspects and characteristics of bibliometrics, scientometrics, informetrics and altmetrics. | A1 A21 |
B1 B5 B7 |
C1 C3 C4 C5 C7 |
| To know and know how to handle the main bibliometric databases such as Scopus and Web of Science, including all the quantitative data analysis tools provided by their web platforms. | A1 A8 A13 A16 A20 A21 A22 |
B2 B9 B11 |
C2 C4 C6 C7 |
| Know, understand and know how to apply the main bibliometric indicators, cybernetic, scientometrics, and other quantitative tools and representation of citation analysis. | A1 A8 A13 A16 A20 |
B1 B2 B3 B7 B9 |
C1 C8 |
| To know the main rankings in the field of bibliometrics, to understand how they are constructed and to know how to interpret their quantitative indicators. | A1 A16 A20 A21 A22 |
B1 B7 B9 B11 |
C2 C4 C6 C7 C8 |
| Knowledge and acquisition of skills for data collection, data processing and the application of different statistical techniques in bibliometrics, scientometrics, informetrics and altmetrics, including, among others, exploratory methods, regression, inference, quality control and network analysis. | A1 A8 A16 A20 A21 A22 |
B1 B2 B3 B4 B5 B7 B9 |
C1 C2 C4 C7 C8 |
| Ability to apply and develop data visualization tools, including graphical network analysis techniques. | A8 A16 A21 A22 |
B2 B4 B6 B9 B10 B11 |
C2 C6 C7 C8 |
| Ability to use computational tools for statistical data analysis. | A8 A21 A22 |
B2 B3 B4 B5 B8 B9 B10 B11 |
C2 C4 C6 C7 C8 |
| Integrate theoretical and practical statistical knowledge as a way to adquire knowledge and reflective and totalizing thinking. | A16 A21 |
B1 B2 B3 B4 B6 B7 B8 B9 B10 |
C1 C4 C6 C7 C8 |
| Capability of analysis and synthesis applied to the management and organization of information. | A8 A13 A20 |
B3 B4 B5 B7 B8 B9 |
C1 C4 C6 C7 C8 |
| Contents |
| Topic | Sub-topic |
| Introduction to information metric studies. | Preliminary concepts, historical evolution, objectives and relevance. Informetrics, Bibliometrics, Scientometrics and Altmetrics. |
| Sources of bibliometric information. | Web of Science and the Journal Citation Report. Scopus. Google Scholar. Other sources of bibliometric information. Case studies. |
| Informatics indicators and software for statistical analysis. |
Indicators calculated from the number of publications and/or citations, journal indicators, patent indicators, webometric indicators, economic indicators, indicators of the reputation of institutions and researchers, indicators of scientific collaboration. Software for statistical analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. Case studies. |
| Multivariate statistical methods for analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. | Descriptive statistical analysis in Bibliometrics, Scientometrics, Informetrics and Altmetrics. Study of the relationship between bibliometric variables. Correspondence analysis. Cluster analysis in Informetrics. Introduction to network analysis and scientific maps. Case studies with R. |
| Rankings of higher education institutions. |
Introduction and objectives. National rankings. International rankings. Case studies with R. |
| Bibliometric laws and estimation of regression models |
Preliminary concepts. Regression model fitting. Bibliometric laws: Price, Lotka, Zipf. Case studies with R. |
| Statistical quality control in libraries, science and information systems. |
Library databases. Six Sigma methodology. Basic tools of statistical quality control. Practical cases with R. |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Guest lecture / keynote speech | A1 A8 A16 A20 A21 B1 B3 B7 C4 C7 | 21 | 0 | 21 |
| ICT practicals | A13 A16 A20 A22 B10 B11 C2 | 17 | 0 | 17 |
| Case study | A1 A8 A16 A20 A21 B2 B3 B4 B5 B6 B7 B8 B9 C1 C8 | 10 | 10 | 20 |
| Supervised projects | B2 B4 B5 B6 B8 B9 B10 C1 C3 C5 C6 C8 | 1 | 88 | 89 |
| Objective test | A21 B1 B2 | 2 | 0 | 2 |
| Personalized attention | 1 | 0 | 1 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Guest lecture / keynote speech | They will be expository sessions in which the various topics of the subject will be introduced and described through presentations (using appropriate audiovisual media) that will include theory and examples. |
| ICT practicals | Practical classes will be developed using statistical software. Its programming and application will be introduced based on real and simulated cases. |
| Case study | The bibliometric and statistical techniques taught in the subject will be applied to solve exercises and real and simulated case studies in the field of informetrics. |
| Supervised projects | Individual and/or group works will be carried out under the supervision of the teachers of the subject. These assignments may deal with the resolution of practical exercises or specific case studies related to the field of computer science. For this purpose, bibliometric and, in general, statistical techniques may be applied, using specific quantitative analysis software such as the R package, in addition to qualitative analysis. A review study on a specific topic of the subject or in relation to the software used may also be carried out. The works can be proposed by the teachers or by the students themselves (the proposals will be taken into account or not always according to the teacher's criteria). |
| Objective test | It will consist of a multiple-choice test on the contents taught in the subject, which, optionally, may contain questions to be developed in writing. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| ICT practicals | A13 A16 A20 A22 B10 B11 C2 | Attendance and/or performance of the students in the practical classes with the statistical software will be evaluated. | 20 |
| Supervised projects | B2 B4 B5 B6 B8 B9 B10 C1 C3 C5 C6 C8 | Individual and/or group work will be carried out under the supervision of the teachers of the subject. These works may include the resolution of practical exercises or specific case studies related to the field of Informetrics. For this purpose, bibliometric and, in general, statistical techniques may be applied, using specific quantitative analysis software such as the R package, in addition to qualitative analysis. A review study on a specific topic of the subject or in relation to the software used may also be carried out. The work may be proposed by the teachers or by the students themselves (the proposals will be taken into account or not always according to the teacher's criteria). | 40 |
| Objective test | A21 B1 B2 | A multiple-choice test that, optionally, may contain some questions to be developed in writing. | 40 |
| Assessment comments | |||
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Primeira oportunidade Realizarase unha proba de resposta múltiple de 10 a 20 preguntas que representa o 40% da nota (opcionalmente, poderanse incluir preguntas a desenvolver por escrito). Por outra banda, a avaliación continua constará da asistencia e/ou entrega de prácticas relacionadas coa aprendizaxe e aplicación do software para a resolución de problemas no campo da Informetría (20% da nota global), ademais da entrega dun ou varios traballos de aplicación de técnicas bibliométricas e, en xeral, estatísticas, para a resolución de casos de estudo en Informetría (alternativamente poderán ser traballos de revisión ou ampliación da materia) que representa o 40% da nota total. Segunda oportunidade Na avaliación da segunda oportunidade se seguirá o mesmo criterio que na primeira. Convocatoria adiantada Todas as observación previas son aplicables aos estudantes que soliciten a convocatoria adiantada do exame. Calificación de non presentado En calquera das dúas oportunidades anuais figurará un NON PRESENTADO naqueles casos nos que o alumnado non acuda ó exame oficial da materia. Estudiante con recoñecemento de dedicación a tempo parcial e dispensa académica de exención de asistencia No caso do alumnado con recoñecemento de dedicación a tempo parcial e dispensa académica de exención de asistencia que decida non asistir a clases, este será avaliado nas dúas oportunidades como o resto do alumnado que se atopa nunha situación similar. A realización fraudulenta das probas ou actividades de avaliación implicará directamente a calificación de suspenso "0" na materia na convocatoria correspondente, invalidando así calquera calificación obtida en todas as actividades de avaliación de cara á convocatoria extraordinaria. |
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| Sources of information |
| Basic |
Moed, H. F. (2017). Applied evaluative informetrics. Berlin: Springer International Publishing
Dervi?, H. (2019). Bibliometric analysis using Bibliometrix an R Package. Journal of Scientometric Research, 8(3), 156-160
Williams, G. (2011). Data mining with Rattle and R: The art of excavating data for knowledge discovery. Springer Science & Business Media
Tarrío-Saavedra, J., Orois, E., & Naya, S. (2017). Estudio métrico sobre la actividad investigadora usando el software libre R: el caso del sistema universitario gallego. Investigación bibliotecológica, 31(SPE), 221-247
Qiu, J., Zhao, R., Yang, S., & Dong, K. (2017). Informetrics: theory, methods and applications.. Springer
Roemer, R. C., & Borchardt, R. (2015). Meaningful metrics: A 21st century librarian's guide to bibliometrics, altmetrics, and research impact. Association of College and Research Libraries
Fernández Casal, R., Lafuente Rego, B., Lombardía, M.J., Costa, J. & Tarrío-Saavedra, J. (2020). scimetr: paquete en R para el análisis bibliométrico. https://rubenfcasal.github.io/scimetr/articles/docs/R_packages.html |
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| Recommendations | ||
| Subjects that it is recommended to have taken before | ||
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| Subjects that continue the syllabus |
| Other comments | |
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To help to achieve a sustainable environment and meet the objective of action number 5: “Healthy and sustainable environmental and social teaching and research” of the "Green Campus Ferrol Action Plan": 1.- The delivery of the documentary works carried out in this subject: 1.1. It will be requested in virtual format and/or computer support. 1.2. It will be done through Moodle, in digital format without the need to print them. 1.3. If done on paper: -Plastics will not be used. - Double-sided prints will be made. - Recycled paper will be used. - Draft printing will be avoided. 2.- A sustainable use of resources and the prevention of negative impacts on the natural environment must be made. 3.- The importance of ethical principles related to the values ??of sustainability in personal and professional behavior must be taken into account. 4.- As it is included in the different regulations of application for university teaching, the gender perspective must be incorporated in this subject (non-sexist language will be used, bibliography of authors of both sexes will be used, intervention in student class will be encouraged and students...). 5.- We will work to identify and modify prejudices and sexist attitudes, and the environment will be influenced to modify them and promote values ??of respect and equality. 6. Situations of discrimination based on gender must be detected and actions and measures will be proposed to correct them. 7. The full integration of students who, due to physical, sensorial, psychic or sociocultural reasons, experience difficulties in an ideal, egalitarian and profitable access to university life will be facilitated |