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Data Integration (standalone course)
Data Integration module of Data Curation

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Course Description for Data Curation (of which "Data Integration" is the first module).

Objectives. The Data Integration course addresses a variety of problems related to the integration of heterogenous data sources, that range from structured data (such as relational databases), over semi-structured data (such as data on the Web, and tree- and graph-structured data), to unstructured (textual) data. It overviews foundational techniques for data integration, such as schema mappings, data and schema matching, and query processing in data integration, and does so considering different data representations that go beyond the relational model, such as RDF data, linked open data, and knowledge graphs. Architectures for data integration and data federation and their adoption to build comprehensive data integration solutions are studied. By attending the course, students will also learn how to design and build a data integration system, possibly exploiting existing data access and data federation technologies.

Prerequisites. Knowledge of relational databases, as taught in an introductory course at the BSc level. Basic knowledge of first-order logic, as taught in a BSc course in logic or discrete mathematics. Java programming skills for the project part.

Teaching material

• Data Integration. Anhai Doan, Alon Halevy, Zachary Ives. Morgan Kaufmann, 2012.
  Available at University Library Bozen: 13-Textbook Collection (ST 270 D631).
  
• Data Integration (Course Slides). Diego Calvanese. 2021.
  The slides will be made available during the course and can be downloaded from the MS Team for the Data Integration course.
• Esercises solved in class.
  The exercises will be assigned for the exercise hours, and the solutions will be made available in the following week on MS Team for the Data Integration course.

• Office hours
• Schedule: The course is taught in the 2nd semester: from 2 March 2020 to 10 June 2020, typically in Lecture Room E4.20:
  • Lectures:
    • Tuesday 10:00-12:00
    • Wednesday 8:00-10:00
  • Exercises: Monday 16:00-18:00
  See also the on-line timetable page for changes.
  
• Exam dates
  • Summer session: TBD
  • Autumn session: TBD
  • Winter session: TBD
• Rules for the exam
  • The final mark will be based on:
    1. a project [50% of mark], and
    2. a final oral exam [50% of mark].
    The final mark is computed as the average of the oral exam mark (50%) and the project mark (50%).
  • The oral exam consists of a discussion of the project, and an examination about the topics covered in the course.
    • The discussion of the project will take between 15 and 20 minutes, and will include showing the functionalities of the developed data integration application. Projects developed by two students in collaboration will be discussed by the two students together.
    • For the examination, each student will be assigned three topics, among which the student should choose two for the discussion in oral form, in roughly 10 minutes each. The three topics will be assigned to the student roughly 15 minutes in advance of the discussion, so that the student has time to prepare herself/himself. The student can (and actually is encouraged to) prepare during these 15 minutes written notes that can aid her/him during the discussion. No additional written material can be used during the preparation of the notes or during the discussion.
  • The exam is considered passed when both marks are valid, i.e., in the range 18-30. Otherwise, the individual valid mark (if any) is kept for all 3 regular exam sessions, until also ther other part is completed with a valid mark. After the 3 regular exam sessions, all marks become invalid.
• Guidelines for the data integration project