Information Integration (academic year 2017/2018)

This is one of the two sections of the course Large Scale Data Management. The lectures of this section will be held in March-April 2018.

For whom is this course. This 3 credits course is actually one of the two sections of the course Large Scale Data Management for the students of the Master in Computer Engineering (School of Engineering) of Sapienza Università di Roma.
Prerequisites. A good knowledge of the fundamentals of Programming Structures, Programming Languages, Databases (SQL, relational data model, Entity-Relationship data model, conceptual and logical database design) and Database systems, as well as a basic knowledge of Mathematical Logic is required.
Course goals. Information integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing information integration systems is important in current real world applications, and is characterized by a number of issues that are interesting from both a theoretical and a practical point of view. In the last years, there has been a huge amount of research work on data integration, and a precise, clear picture of a systematic approach to such problem is now available. This section will present an overview of the research work carried out in the area of data integration, with emphasis on the theoretical results that are relevant for the development of information integration solutions. Special attention will be devoted to the following aspects: architectures for information integration, modeling an information integration application, ontology-based data access and integration, processing queries in information integration, data exchange, and reasoning on queries.

  • News
    • March 26, 2019 New dates for the exam have been added (see below).
    • March 15, 2018 The complete set of slides on the theory of data integration are available in the Moodle system.
  • Topics covered
    • Architectures for information integration
    • Distributed data management
    • Data federation
    • Data exchange and data warehousing
    • ETL (Extraction, Transformation and Loading), data cleaning and data reconciliation
    • Data integration
    • Ontology-based data integration
  • Teaching material
    • Before the beginning of the lectures, students are invited to (re)study the basic notions of propositional and first-order logic. For this purpose, students may use the material they used in previous courses, or have a look at:
    • Slides
      The lecture notes can be downloaded from the course page in Moodle

    • Book
      A good book on information integration is: Principles of data integration, by AnHai Doan, Alon Halevy, Zachary Ives.

    • Papers
      This is a list of papers that students can read if they are interested in specific topics:

      • Reasoning about schema mapping
        • Ronald Fagin, Phokion G. Kolaitis, Lucian Popa, Wang Chiew Tan. Composing schema mappings: Second-order dependencies to the rescue. ACM Trans. Database Syst. 30(4): 994-1055 (2005)
        • Bogdan Alexe, Balder ten Cate, Phokion G. Kolaitis, Wang Chiew Tan: Characterizing schema mappings via data examples. ACM Trans. Database Syst. 36(4): 23 (2011)
      • Query answering
        • Alon Y. Levy, Alberto O. Mendelzon, Yehoshua Sagiv, Divesh Srivastava. Answering Queries Using Views. PODS 1995: 95-104
        • Rachel Pottinger, Alon Halevy. MiniCon: A scalable algorithm for answering queries using views.The VLDB Journal” The International Journal on Very Large Data Bases, Volume 10, Issue 2-3 (September 2001)
        • Oliver M. Duschka, Michael R. Genesereth, Alon Y. Levy. Recursive Query Plans for Data Integration. J. Log. Program. 43(1): 49-73 (2000)
        • George Konstantinidis, José Luis Ambite. Scalable query rewriting: a graph-based approach, SIGMOD '11 Proceedings of the 2011 international conference on Management of data.
      • Probabilistic data integration
        • Xin Luna Dong, Alon Y. Halevy, Cong Yu. Data integration with uncertainty. VLDB J. 18(2): 469-500 (2009)
      • Query answering under inconsistencies
        • Andrea Calì, Domenico Lembo, Riccardo Rosati. On the decidability and complexity of query answering over inconsistent and incomplete databases. PODS 2003: 260-271
        • Marcelo Arenas, Leopoldo E. Bertossi, Jan Chomicki. Consistent Query Answers in Inconsistent Databases. PODS 1999: 68-79
        • Balder ten Cate, Gaëlle Fontaine, Phokion G. Kolaitis: On the Data Complexity of Consistent Query Answering. Theory Comput. Syst. 57(4): 843-891 (2015)
      • Data cleaning and reconciliation
        • Douglas Burdick, Ronald Fagin, Phokion G. Kolaitis, Lucian Popa, Wang Chiew Tan: Expressive Power of Entity-Linking Frameworks. ICDT 2017: 10:1-10:18
        • Anja Gruenheid, Xin Luna Dong, Divesh Srivastava: Incremental Record Linkage. PVLDB 7(9): 697-708 (2014)
      • Ontology-based data integration
        • Diego Calvanese, Giuseppe De Giacomo, Domenico Lembo, Maurizio Lenzerini, Antonella Poggi, Mariano Rodriguez-Muro, Riccardo Rosati: Ontologies and Databases: The DL-Lite Approach. Reasoning Web 2009: 255-356
  • Exams
    The following are the rules for the exam. There are three possibilities for the exam:

    • Study a tool for data integration, data federation, ETL or data exchange, and then make a presentation (in English), where the characteristics of the tool are described, the position of the tool in the spectrum of information integration principles illustrated in the course is discussed, and a demo of the tool is presented. For a complete picture of the available tools for data integration, the student should search on the web. Here is an incomplete list of possible tools: Karma, IBM Infosphere, Oracle data integrator, CloverETL, Pentaho, TEIID, Talend, Jitterbit, Adeptia, Open Refine etc.
    • Choose a set of data sources with data relevant for a certain phenomenon (for example, data taken from open data published on-line, or data taken from a database or from csv files, or from xls files known by the student), and develop a data integration or data exchange application using such data sources (and using any tool selected by the student). This work can be carried out in a group of at most two students.
    • Choose a coordinated project with the section on Big Data Management taught by Prof. Lembo. Just to give an idea of possibile coordinated projects, here is a(n incomplete) list of possible projects: (1) the part related to Information Integration can be an ETL system integrating interesting data sources into a data warehouse using a chosen tool, and the parte on Big Data Management can be an application of OLAP operations over the integrated data in order to carry out interesting analyses. (2) The part related to Big Data Management can be the set up of heterogeneous data sources, including NoSQL data sources, and the part on Information Integration can be a system integrating such data sources using a chosen tool. (3) The part related to Information Integration can be a system integrating interesting data sources into a NoSQL source (such as a graph database), and the part on Big Data Management can be the implementation of queries over the integrated data.

    In all the above cases, once the student has chosen the topic, (s)he should send an email message to prof. Lenzerini (and, in case of a joint project with Big Data Management, to Prof. Lembo too), with the description of the topic, and wait for confirmation, or a request to change the topic. Also, once the student has decided on the date for the exam, (s)he should send an email message to prof. Lenzerini with the indication of the date. Here are the dates for January/February 2019 (the exam will be held in the office of Prof. Lenzerini):

    • April 30, 2019 at 4pm

  • Schedule of exams
    • First exam: June 2018
    • Second exam: July 2018
    • Third exam: September 2018
    • First special session: October 2018
    • Fourth exam: January 2019
    • Fifth exam: February 2019
    • Second special session: April 2019
  • Lectures
    • When: Monday, 9:00am - 11:00am, Thursday, 2:00pm - 5:00pm,
      starting from February 26, 2018.

    • Where: Classroom A5, via Ariosto 25, Roma
    • Schedule

      Week Monday (9:00am - 11:00am)
      classroom A5
      Thursday (2:00pm - 5:00pm)
      classroom A5
      01 (Feb 26)
      02 (Mar 05)
      Lectures 1,2,3
      - Introduction to information integration
      - Propositional logic: syntax and semantics
      03 (Mar 12) Lectures 4,5
      - Predicate: syntax and semantics
      Lectures 6,7,8
      - Relationship between logic and data management
      04 (Mar 19) Lectures 9,10
      - Formalization of data integration
      Lectures 11,12,13
      - Mapping languages
      05 (Mar 26) Lectures 14,15
      - Algorithms for query answering in GAV without axioms
      06 (Apr 02)
      Lectures 16,17,18
      - Tool for mapping specification: KARMA
      07 (Apr 09) Lectures 19,20
      - Algorithms for data exchange in GLAV without axioms
      Lectures 21,22,23
      - Virtual data integration in GLAV without axioms
      - Data integration with axioms in the global schema
      08 (Apr 16) Lectures 24,25
      - Ontology-based data integration
      09 (May 07)

      Lectures 26,27,28
      - Student presentations

  • Past editions
  • Office hours. Tuesday, 5:00 pm, at the Dipartimento di Informatica e Sistemistica "Antonio Ruberti",
    via Ariosto 25, Roma, second floor, room B203 (if available), or room B217 (otherwise) -- please, look at the last
    minute news for the next office hours