• February 28, 2020 The April session exam will be held on April 14, at 4:00pm, on-line.

• 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

• 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:
  • Introduction to propositional logic (paper)
  • Introduction to first-order logic (paper)
• 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 and tools
  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

  Here is an incomplete list of possible tools to study/experiment in a small project: Karma, IBM Infosphere, Oracle data integrator, CloverETL, Pentaho, Jedox, TEIID, Apatar, Talend, Jitterbit, Myddleware, Adeptia, Open Refine etc.

• Study a paper on or a tool for data integration, data federation, ETL or data exchange, and then make a presentation (in English), where the characteristics of the paper or the tool are described, and the position in the spectrum of information integration principles illustrated in the course is discussed.
• 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 April 2020 (the exam will be held in the office of Prof. Lenzerini, at 4:00pm):

• April 14, 2020, at 4:00pm in via Ariosto 25 (room B217)

• First exam: June 2019
• Second exam: July 2019
• Third exam: September 2019
• First special session: October 2019
• Fourth exam: January 2020
• Fifth exam: February 2020
• Second special session: April 2020

• When: Thursday, 8:00am - 10:00am, starting from March, 2019 (sometimes, also Tuesday, from 5pm to 7pm).
• Where: Classroom A5, via Ariosto 25, Roma
• Schedule
  

  Week	Tuesday (4:00pm-7:00pm) OR Thursday (8:00am - 10:00am) classroom A5	Thursday (10:00am - 01:00pm) classroom A5
  01 (Feb 25)	--------	Lectures 1,2,3 - Introduction to information integration - Propositional logic: syntax and semantics
  02 (Mar 04)	--------	--------
  03 (Mar 11)	--------	Lectures 4,5,6 - First-order logic - Relationship between logic and data management
  04 (Mar 18)	--------	Lectures 7,8,9 - The various forms of information integration - Logical formalization of data integration
  05 (Mar 25)	--------	Lectures 10,11,12 - The notion of certain answers - GAV mappings - LAV mappings
  06 (Apr 01)	--------	Lectures 13,14,15 - Exercises on mapping specification
  07 (Apr 08)	--------	Lectures 16,17,18 - Materialized integration in GAV without constraints - Virtual integration in GAV without constraints
  08 (Apr 15)	--------	--------
  09 (Apr 22)	--------	--------
  10 (Apr 29)	(Thursday, May 2) Lectures 19,20 - Data exchange	Lectures 21,22,23 - Data exchange - Materialized integration in LAV without constraints
  11 (May 06)	(Tuesday, May 9) Lectures 24,25,26 - Virtual integration in LAV without constraints	--------
  12 (May 13)	(Thursday, May 16) Lectures 27,28 - Ontology-based data integration	Lectures 29 - Ontology-based data integration
  13 (May 20)	(Tuesday, May 21) Lectures 30,31,32 - Big data integration (with a seminar by Ing. Luca Vallarelli - Microsoft)	Lectures 33,34,35 - Information extraction and integration (with a seminar by Ing. Ilaria Bordino - Unicredit R&D)
  14 (May 27)	(Thursday, May 30) Lectures 36,37 - Project discussion	Lectures 38,39,40 - Project discussion

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