Web Data Integration (HWS2022)

Data integration is one of the key challenges in many IT projects and it is estimated that data scientists spend about 80% of their time on data integration and cleansing. In the enterprise context, data integration techniques are applied whenever data from separate sources needs to be combined for new applications or data analysis projects. Within the context of the Web, data integration lays the foundation for taking advantage of the ever growing number of publicly-accessible data sources and enables applications such as product comparison portals, job portals, or data search engines.

In the course, students will learn and experiment with techniques for integrating and cleansing data from large sets of heterogeneous data sources. The course will cover the following topics:

  1. Heterogeneity and Distributedness

  2. The Data Integration Process

  3. Structured Data on the Web

  4. Data Exchange Formats

  5. Schema Mapping and Data Translation

  6. Identity Resolution

  7. Data Quality Assessment

  8. Data Fusion

The course consists of a lecture as well as accompanying practical projects. The lecture (IE670) covers the theory and methods of web data integration and is concluded by a written exam (3 ECTS). In the projects (IE683), students will gain experience with web data integration methods by applying them within a real-world use case of their choise. Students will work on their projects in teams and will report the results of their projects in the form of a written report as well as an oral presentation (together 3 ECTS). While the lecture and the project can be attended in seperate years, it is highly recommended to attend both in the same semester as the schedule of the lecture and project are aligned to each other.

Time and Location

  • Wednesday, 15:30-17:00. Location: A5 C015 (Starting: 7.9.2022)
  • Thursday, 10:15-11:45. Location: B6 A101 (Starting: 8.9.2022)

ECTS

  • 3 ECTS: Lecture with written exam (IE670)
  • 3 ECTS: 70 % project report, 30 % presentation (IE683)

Requirements

  • Programming skills in Java are required for the projects as we are going to use the Winte.r framework.

Registration and Participation

  • The lecture and the projects are open to students of the Mannheim Master in Data Science and Master Business Informatics.
  • The lecture (IE670) is not restricted on the number of participants, but you still need to register in Portal2 for the course.
  • The projects (IE683) are restricted to altogether 75 participants. The registration for the projects (IE683) is done via Portal2. The registration period is 15. August to 5. September 2022.

Outline

Week Wednesday (Room: A5 C015)Thursday (Room: B6 A101)
07.9.2022Lecture: Introduction to Web Data IntegrationLecture: Structured Data on the Web
14.9.2022Lecture: Data Exchange FormatsLecture: Data Exchange Formats
21.9.2022Lecture: Schema MappingLecture: Schema Mapping
28.9.2022Project: Introduction to Student ProjectsExercise: Introduction to MapForce
05.10.2022Project: Feedback about Project OutlinesCoaching: Schema Mapping
12.10.2022Project Work: Schema MappingLecture: Identity Resolution
19.10.2022Lecture: Identity ResolutionExercise: Identity Resolution
26.10.2022Project Work: Identity ResolutionCoaching: Identity Resolution
02.11.2022Project: Work Identity ResolutionCoaching: Identity Resolution
09.11.2022Lecture: Data Quality and Data FusionLecture: Data Quality and Data Fusion
16.11.2022Exercise: Data Quality and Data FusionProject Work: Data Quality and Data Fusion
23.11.2022Project Work: Data Quality and FusionCoaching: Data Quality and Fusion
30.11.2022Project Work: Data Quality and FusionCoaching: Data Quality and Fusion
07.12.2022Presentation of Project ResultsPresentation of Project Results