Information integration is the merging of heterogeneous information from various data sources to a homogenous, clean dataset. This lecture introduces this ever-important topic. It will cover the basic technologies, such as distributed database architectures, techniques for virtual and materialized integration, and data cleansing technologies.
| Introduction to Information Integration | 01:25:41 | |
|---|---|---|
| Introduction | 00:21:42 | |
| Organisation | 00:23:31 | |
| Information Systems | 00:40:28 |
| Verteilung, Autonomie und Heterogenität | 01:20:25 | |
|---|---|---|
| Überblick | 00:08:34 | |
| Verteilung | 00:18:05 | |
| Autonomie | 00:17:44 | |
| Syntaktische Heterogenität | 00:23:52 | |
| Strukturelle Heterogenität | 00:12:10 |
| Verteilung, Autonomie und Heterogenität (2) | 01:29:02 | |
|---|---|---|
| Schematische Heterogenität | 00:19:55 | |
| Semantische Heterogenität | 00:24:00 | |
| Gebundene und Freie Variablen | 00:45:07 |
| Materialisierte vs. virtuelle Integration | 01:26:09 | |
|---|---|---|
| Überblick: Zwei wesentliche Modelle | 00:36:38 | |
| Materialisierte Integration | 00:07:02 | |
| Virtuelle Integration | 00:06:19 | |
| Vergleich | 00:36:10 |
| Web Tables und Architekturen | 01:24:26 | |
|---|---|---|
| History | 00:07:53 | |
| Challenges | 00:03:38 | |
| Applications | 00:39:10 | |
| Architekturen | 00:21:17 | |
| Mediator-Wrapper-Architekturen | 00:12:28 |
| SchemaSQL | 01:21:31 | |
|---|---|---|
| Mediator-Wrapper-Architektur | 00:22:14 | |
| Peer-Data-Management | 00:12:30 | |
| Wiederholung | 00:21:04 | |
| SchemaSQL | 00:25:43 |
| SchemaSQL & Schema Mapping | 01:25:21 | |
|---|---|---|
| SchemaSQL | 00:43:36 | |
| Motivation Schema Mapping | 00:41:45 |
| Schema Mapping & Schema Matching | 01:25:01 | |
|---|---|---|
| Schema Mapping | 00:18:24 | |
| Klassifikation von Schema Matching Methoden | 00:40:57 | |
| Erweiterungen | 00:22:00 | |
| Globales Matching | 00:03:40 |
| Schema Matching & Mapping Interpretation | 01:26:28 | |
|---|---|---|
| Globales Matching | 00:20:00 | |
| Mapping Interpretation | 01:06:28 |
| Global-as-View: GaV | 01:12:02 | |
|---|---|---|
| Motivation | 00:04:33 | |
| Korrespondenzen | 00:05:49 | |
| Übersicht Anfrageplanung | 00:24:36 | |
| Modellierung | 00:27:31 | |
| Anfragebearbeitung | 00:09:33 |
| Local-as-View: LaV | 01:10:26 | |
|---|---|---|
| Modellierung | 00:29:05 | |
| Anwendungen | 00:24:26 | |
| Anfragebearbeitung | 00:16:55 |
| Local as View (LaV) & Global Local as View (GLaV) | 01:10:16 | |
|---|---|---|
| Closed World Assumption und Open World Assumption | 00:17:51 | |
| Containment | 00:43:00 | |
| Global Local as View (GLaV) | 00:04:22 | |
| Vergleich | 00:05:03 |
| Bucket Algorithmus | 01:32:38 | |
|---|---|---|
| Nutzbarkeit und Nützlichkeit von Views | 00:37:52 | |
| Bucket Algorithmus am Beispiel | 00:27:10 | |
| Bucket Algorithmus en detail | 00:27:36 |
| Duplicate Detection | 01:20:42 | |
|---|---|---|
| Duplicate Detection | 00:32:41 | |
| Similarity Measures | 00:48:01 |
| Duplicate Detection Part 3 & Data Quality | 01:25:02 | |
|---|---|---|
| Partitioning | 00:14:10 | |
| Sorted Neighborhood | 00:08:48 | |
| Data Sets and Evaluation | 00:35:33 | |
| Data Fusion | 00:09:09 | |
| Information Quality | 00:17:22 |
| Data Quality | 01:25:20 | |
|---|---|---|
| IQ Criteria | 00:30:32 | |
| IQ Assessment | 00:03:54 | |
| Cleansing Tasks | 00:33:09 | |
| IQ Anecdotes | 00:17:45 |
