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2020/2021

Applied Technologies I: from Data to Information

Code: 44250 ECTS Credits: 6
Degree Type Year Semester
4317127 Digital Humanities and Heritage OB 0 1
The proposed teaching and assessment methodology that appear in the guide may be subject to changes as a result of the restrictions to face-to-face class attendance imposed by the health authorities.

Contact

Name:
Oriol Ramos Terrades
Email:
Oriol.Ramos@uab.cat

Use of Languages

Principal working language:
spanish (spa)

Prerequisites

To attend these studies, the general prerequisites of the MA degree on Humanities and Digital Heritage are necessary. In general, the student should have already some studies at BA-level on Humanities and / or Social Sciences disciplines. The course can also be useful to computer science graduates who want to specialize in the use of digital technologies in the field of Humanities and cultural studies, although they do not have previous experience on Humanities nor Cultural studies. Familiarity, at use level, with computers and standard office software is required. Although not mandatory, prior training, at a basic level, in the use of computerized databases, computer-assisted cartography, digital photography and statistics is recommended.

The basic and reference bibliography is in English, as well as the software to be used. Knowledge of English at the level of specialized reading is therefore recommended.

Objectives and Contextualisation

This module aims to introduce students to the design of databases and information systems and the processing of cultural and documentary information. Furthermore, the notion of “Big Data” is introduced and the possibilities of current applications in artificial intelligence and “Deep Learning” for information processing are evaluated. The applicability of computer techniques and tools is emphasized, so that they know their diversity and learn to use some of them in carrying out a specific project.

Competences

  • Act in a creative and original way with solidarity and spirit of scientific collaboration.
  • Analyse and extract relevant scientific information from documents and historical, artistic and literary digitized materials.
  • Critically analyse a particular scientific problem based on specific documentation.
  • Design and plan impact and cultural innovation projects which use the possibilities offered by information and computer technologies.
  • Ensure value and quality, self-discipline, rigour and responsibility in scientific work and dissemination.
  • Incorporate the use of computer technology in the communication and transmission of culture to specialist and non-specialist audiences and evaluate the results.
  • Knowledge and understanding that provide a basis or opportunity for originality in developing and / or applying ideas, often in a research context.
  • Manage cultural projects that use information and computer technologies in any area.
  • Recognise and use the appropriate computer tools for the acquisition, digitization, indexing and processing of documents and historical, artistic and literary materials.
  • Recognise and value the social consequences of the work carried out, taking into account the diversity of human communities in questions of gender, identity and multiculturality.
  • Recognise the main challenges in the area of study of digital humanities and heritage.
  • Students can communicate their conclusions and the knowledge and rationale underpinning these to specialist and non-specialist audiences clearly and unambiguously.
  • That students are able to integrate knowledge and handle complexity and formulate judgments based on information that was incomplete or limited, include reflecting on social and ethical responsibilities linked to the application of their knowledge and judgments.
  • That students have the learning skills that enable them to continue studying in a way that will be largely self-directed or autonomous.
  • That the students can apply their knowledge and their ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.
  • Work in interdisciplinary teams.

Learning Outcomes

  1. Analyse practical problems deriving from the application of computerised data analysis in the field of humanities and cultural studies.
  2. Apply criteria of scientific rigour in the production of academic and professional work.
  3. Apply ethical aspects in the analysis of cultural needs for a broad range of audiences.
  4. Demonstrate efficiency in the extraction of social and cultural information from humanistic documents using data management technology.
  5. Design the basic element of an information system using the ontologies and conceptual models of reference in humanities and digital heritage.
  6. Evaluate the real possibilities of reaching the public through cultural action.
  7. Explain computer technology for data base management in different areas of humanities and cultural studies.
  8. Explain computer technology for statistical processing and data mining in different areas of humanities and cultural studies.
  9. Form part of multidisciplinary working teams in which academic reflections and procedures are central.
  10. Highlight ethical aspects in cultural projects and respect for different opinions and way of being and doing things.
  11. Include proposals and reflections of work carried out linked to the perspectives of: gender, universal accessibility, multiculturality and intergenerationality.
  12. Knowledge and understanding that provide a basis or opportunity for originality in developing and / or applying ideas, often in a research context.
  13. Make innovations incorporating creativity and originality in humanistic and cultural studies with a clear commitment to quality.
  14. Make use of languages for data consultation based on the current standards in humanities and digital heritage.
  15. Propose innovative and competitive ideas based on knowledge acquired in fields which are not directly related a priori .
  16. Resolve practical problems related to data analysis and processing.
  17. Students can communicate their conclusions and the knowledge and rationale underpinning these to specialist and non-specialist audiences clearly and unambiguously.
  18. Summarise advanced knowledge existing in the field.
  19. That students are able to integrate knowledge and handle complexity and formulate judgments based on information that was incomplete or limited, include reflecting on social and ethical responsibilities linked to the application of their knowledge and judgments.
  20. That students have the learning skills that enable them to continue studying in a way that will be largely self-directed or autonomous.
  21. That the students can apply their knowledge and their ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their field of study.
  22. Theorise the use of multimedia technologies and focuses based on artificial intelligence to increase accessibility and communicability of data processing and analysis.

Content

INTRODUCTION TO DATABASES. Basic concepts. Historical evolution. Advantages and disadvantages of a database system.

INTRODUCTION TO EXISTING DATABASES AND TYPOLOGIES. Database architectures. Client / Server Architectures. Database typologies: relational and non-relational. Introduction to database management tools: Oracle, MongoDB, etc.

RELATIONAL DATABASES: THE ENTITY-RELATION MODEL. The entity-relationship model. Design criteria of an entity-relationship system. Design phases of a database. Capture and analysis of requirements. Analysis of the entity-relationship design of various documentary databases.

BASIC CONCEPTS OF RELATIONAL DATABASES. Data structure. Integrity rules. Data manipulation. Query languages. Introduction to SQL. 

NON-RELATIONAL DATABASES. Introduction to non-relational databases. Introduction to object-oriented databases. 

PRESERVATION OF FILES AND INTERNET. Preservation, durability and security of files of digitized information and digitally-born information. Access control and security. Concurrency control. Database recovery. Accessing data in the age of the Internet. Services "in the cloud".

ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS. Big Data, artificial intelligence and data analysis. Introduction to machine learning and “Deep learning”. 

SOURCES OF BIG DATA IN HUMANITIES AND SOCIAL SCIENCES. Europeana, CIDOC-CRM, ARIADNE-EU, ODOCH (Open Data and Ontologies for Cultural Heritage).

Methodology

Guided activities: theoretical classes with an explanation of computer techniques and their theoretical and methodological foundations. Seminars of critical discussion of specialized texts.

Supervised activities: Presentation of computer equipment. Practical work with hardware and software. Individualized tutorials to monitor the activities and work entrusted, and to apply the knowledge and skills acquired in the final work of the module.

Autonomous activities: search for documentation, elaboration of databases, exercises of application of the studied analysis techniques, reading of texts, writing of works. SQL practices with the auto-evaluation module.

Guided activities may be in person or online.

Activities

Title Hours ECTS Learning Outcomes
Type: Directed      
Theory sessions 36 1.44 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
Type: Supervised      
problem solving 25 1 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
Type: Autonomous      
Reading specialized literature and reference work 40 1.6 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
SQL queries module 41 1.64 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6

Assessment

Individual test on the topics explained in class (20% of the final grade).

Individual practice exam on SQL queries (10% of the final grade).

Reports and written work (individually or in groups). They can be a prospective study that assesses the need to apply any digital technology in the field of humanities or cultural heritage studies, a critical bibliographic study on computer methodology and its theoretical implications, where a practical application of one of the techniques explained with students' own data. They can also be written summaries of the practical sessions, emphasizing the positive and negative aspects of the techniques and methods explained (25% of the final grade).

Critical commentary of specialized texts, from the bibliography that will be suggested at the beginning of the course (25% of the final note).

Class participation (face-to-face or online), attendance at tutorials (face-to-face or online). 10% of the final grade.

Participation in conferences scheduled for the coordination of the master's degree and other complementary activities (10%).

At the time of carrying out / delivering each assessable activity, the teacher will inform (Moodle, SIA) of the procedure and date of review of the grades.

The student will receive the grade of No evaluated as long as he / she has not taken the individual test on the topics explained in class and has not delivered more than 50% of the summaries of the practical sessions and text comments. In the event that the student commits any irregularity that could lead to a significant variation in the grade of an assessment act, this assessment act will be graded with 0, regardless of the disciplinary process that may be instructed. In the event of several irregularities in theevaluation acts of the same subject, the final grade for this subject will be 0.

In the event that the tests cannot be done in person, their format will be adapted (maintaining their weighting) to the possibilities offered by the UAB’s virtual tools. Homework, activities and class participation will be done through forums, wikis and / or exercise discussions through Moodle, Teams, etc. The teacher will ensure that the student can access it or offer alternative means, which are available to them.

Assessment Activities

Title Weighting Hours ECTS Learning Outcomes
Attendance and active participation in class 10 0 0 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
Attendance to conferences and other complementary activities 10 3 0.12 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
Critical review of bibliography 25 0 0 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
SQL exam 10 2 0.08 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
Theory exam 20 3 0.12 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6
report delivery 25 0 0 1, 2, 3, 4, 10, 5, 7, 8, 14, 11, 13, 9, 15, 19, 21, 17, 20, 16, 18, 12, 22, 6

Bibliography

A. Silberschatz, H.F. Korth, S. Sudarshan, Fundamentos de Bases de Datos, 5a edición, McGraw-Hill, 2006.

C.J. Date, Introducción a los sistemas de Bases de Datos, Vol.1, 7a edición, Prentice Hall, 2001.

P.Rob, C. Coronel, Sistemas de Bases de datos. Diseño, implementación y administraciónThomson-Paraninfo, 2004.

M. Marqués, J.I. Aliaga, S. García, G. Quintana, SQL y desarrollo de aplicaciones en ORACLE 8Col.lecció; "Treball d'Informàtica i Tecnologia, 9, Universitat Jaume I, 2001.

Bruseker, G., Carboni, N., & Guillem, A. (2017). Cultural heritage data management: the role of formal ontology and CIDOC CRM. In Heritage and Archaeology in the Digital Age (pp. 93-131). Springer, Cham.

da Silva, J. R. (2019). CIDOC-CRM. In Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, September 9-12, 2019, Proceedings (Vol. 11799, p. 99). Springer Nature.