Open Conceptual Data Models

Making the Conceptual Layer Real

via

RDF Linked Data

Conceptual Data Models in the Linked Data Web

Linked Data Vision:

The transition of the Web

from a Web of linked documents

to a Web of interlinked structured data items (aka: entities, data objects, resources)

Concurrent trend in the IT industry:

A recognition of the benefits of conceptual data models vs logical data models

The Big Question:

To what extent does the Linked Data support conceptual level data models ?

Open Conceptual Data Models

Topics:

Conceptual & Logical Data Models

Conceptual Models for the Semantic Web

Realizing Conceptual Models through Ontologies & Linked Data

Virtuoso RDF Views

ADO.NET Data Services & the Entity Data Model

Conceptual & Logical Data Models

Describe a software system’s target problem space

Typically, in today’s database-driven applications

Three levels of data model

Physical

How data is physically represented on disk

Logical (aka logical schema)

Expresses problem domain in terms of data management technology (tables / columns)

e.g. relational schema

Conceptual (aka conceptual schema)

Purely semantic description of problem space

Describes things (entities), their characteristics (attributes) & associations between things (relationships)

Logical Data Model

Most prominent of the three data model types

Main focus of database applications

Due to pervasiveness of SQL in application code

Weaknesses

Impedance mismatch

Loss of semantics during development process

Heterogeneous databases & interoperability

Logical Data Model Weaknesses

Impedance Mismatch

SQL expresses queries in terms of tables / views

=> targets logical schema

Normalization fragments the data model

Entities & their attributes may be split across several tables

Navigation between objects requires relational joins over two or more tables

Table rows must be reconstituted into higher level conceptual entities

Conceptual level data model is desirable to:

Remove impedance mismatch

Isolate application from changes to logical data model

Provide framework for human level interaction

Loss of Semantics During Development

Process:

Develop conceptual model (E-R modelling)

Transform to logical model for implementation

Derive physical model from logical model

Problems:

Each move to a lower level model discards meaning

Higher level model typically not retained

Model semantics fragmented across schema / business rules / application code

Application must know logical data model

Must be hardcoded or inferred (imperfectly) from system tables

Heterogeneous Databases & Interoperability

Logical data model

Describes problem domain in terms of tables/columns

Requires SQL to navigate model

Application

Exposed to specifics of a particular vendor’s RDBMS

In heterogeneous database environment , must handle

Different SQL dialects

Different schemas

No explicit data model. No explicit semantics.

Interoperability/integration = perpetual problem for IT depts

Conceptual Models for the Semantic Web

Growing recognition in the industry of the benefits of a conceptual, rather than logical, model for data-centric applications

e.g. Microsoft’s Entity Data Model / Entity Framework

Semantic Web technologies provide powerful tools for this paradigm shift

Benefits of Conceptual Models

How the Semantic Web benefits

More faithfully represents human view of domain of interest

Conceptual model & semantics

Explicit & available globally

Not implicit & fragmented across business logic / UI etc

Better / explicit semantics promises better search engines

Much easier heterogeneous data integration

Data on the Web is inherently heterogeneous

Application Areas – Present & Future

Social networking, e-commerce, collaborative working

Require shareable, standards-based, cross-platform conceptual views of data

Data portability

Needed as Web users maintain multiple points of presence – blogs, social network accounts etc.

Open business models

Require exchange & integration of large amounts of data

Scientific research – sharing of knowledge & findings

Requires transparent access to distributed heterogeneous data

Requires database integration using global schema

Autonomous intelligent agents

Free humans from large-volume information processing

Semantic Web Technology Benefits

What Semantic Web technologies bring:

Ontologies

Can represent common semantics

Spanning databases, applications, enterprises, on-line communities

Act as a shared conceptual model

Provide common models (FOAF, SIOC etc)

Common Semantics (Ontologies) & Common Data Representation (RDF)

Enable cross data source querying using SPARQL

Content from several sites can be combined / explored

Querying using proprietary APIs unnecessary

Brute force data merging unnecessary

Open Data Formats, Platform Independence, Common Models

Allow data portability and data integration

Realizing Conceptual Models

Ontologies

Provide the building blocks of Semantic Web conceptual models

Define the concepts and their relationships in a domain of interest

Describing Classes & Properties – Ontology Languages

RDFS

Introduces the notions of concepts (classes) & instances

OWL

Adds more vocabulary for describing:

relations between classes

cardinality

richer typing of properties, etc.

Goodness of Fit

RDF was designed from the ground up as a metadata data model

RDF / RDFS / OWL work directly at the level of conceptual models

Conceptual model terminology matches RDF/OWL terminology

Concepts, entities, attributes, relationships

A natural fit!

RDF lends itself naturally to describing conceptual models

Semantic Expressivity

DDL-based Relational Model

Relationship between two entities isn’t explicit

Foreign key relating two rows in separate tables doesn’t express the nature of the relationship

Semantics must often be inferred from table definitions

RDF-based Conceptual Model

Relationship between two entities is stated explicitly by predicate in subject-predicate-object triple

Semantic expressivity of RDF/RDFS/OWL is much better than DDL

Has richer semantic content than equivalent DDL-based logical/relational model

RDF Conceptual Model – Artist / Records / Tracks

Global Granular Information Sharing

Traditional Logical/Relational Data Model

Schema described by DDL is internal to DBMS

Primary keys identifying an individual table row (i.e. entity instance) not globally unique, not easily usable outside host DBMS

Gives rise to ‘data silos’

RDF’s use of HTTP-based URLs

Externalises the data and schema

Makes both globally accessible & scalable

Provides globally unique IDs for entities/relations/classes

A vehicle for granular, global information sharing down to the equivalent of the record level

Linked Data – What is It?

A method for exposing, sharing & connecting data on the Web

A term coined by Tim Berners-Lee that describes HTTP-based Data Access by Reference for the Web

Open Data Access & Connectivity mechanism for the Web

A richer linking mechanism for the Web that takes us from Hypertext Links (Document to Document) to Hyperdata Links (across things that documents are about)

Linked Data – Why Is It Important

It exposes the compound nature of Web Resources

Information resources (Containers) are uniquely identified & referenceable

Entities within Containers are uniquely identified & referencable

It provides an Open Data Access & Connectivity mechanism for the Web

It delivers a powerful mechanism for meshing disparate and heterogeneous data sources

Linked Data Model Changes the focus from linked documents to linked entities The document as a data container becomes less relevant

Hyperdata Links Between Data Objects

Linked Data Benefits – Natural Navigation

Natural Navigation Through Typed Links

RDF entities are identified by dereferencable URIs (URLs)

Navigating from one data item to another is easy

One click to dereference in Semantic Web Browser

e.g. OpenLink Data Explorer

URI of object in an RDF statement is a typed link

Link’s “type” is defined by the statement predicate

Relational/Logical Model

Cumbersome

Requires SQL joins + typically Object-Relational mapping

e.g. in C# : track = lennonAlbum.Tracks[“Imagine”]

Linked Data Benefits - Aggregatable Data

Often desirable to have an integrated view of all the data available about an item or topic

Database Realm

Integration problematic, difficult to combine logical schemas

Semantic Web

Data aggregation is easy: every resource has a unique URI

Individual items can be linked

Conceptual models can be linked

Cross-domain links enrich domain knowledge

Different facets of the same entity may be described by different URIs minted by different authors

Can be linked. e.g. owl:sameAs, rdf:type predicates

May expose facts not directly represented in any one source

Linked Data – Data Aggregation

Linked Data Benefits - Self Describing Data

RDF

A technology for creating self-describing Web resources

Entity’s type definition ‘accompanies’ it using rdfs:type

An RDF dataset can be queried using SPARQL without knowing anything beforehand about the data

Provides the basis for powerful data exploration tools

Logical / Relational Schema

Users / applications need a detailed understanding of the schema to use and navigate the data

Application’s knowledge of the schema typically hardcoded

Ad-hoc end-user data exploration potentially error prone

Linked Data Benefits - SPARQL

If a user agent has no built-in knowledge of a particular RDF subject, predicate or object, it can use the URI to retrieve the information

The Power of SPARQL

Discover what sorts of things a data source contains

select distinct ?URI ?ObjectType where { ?URI a ?ObjectType }

Determine all the properties of an entity class

select * where { <http://my.org/resourceTypes/Department> ?property ?hasValue }

Determine all the properties and values of an entity instance

DESCRIBE <http://my.org/resource/Accounts>

No prior knowledge of the RDF data source is needed

Virtuoso - Linked Data Generation Options

Conceptual layer insulates Linked Data consumers from RDFization infrastructure & data source heterogeneity

Virtuoso RDF Views

Expose relational data as RDF

Provide the means to move from a logical model view to a conceptual model view

Available for querying through SPARQL or SPASQL (SPARQL embedded in SQL)

No physical regeneration of relational data

RDF Views =

Virtuoso RDF Meta-Schema +

Meta-Schema Language

MSL =

A domain specific, declarative language for mapping a logical SQL data model to a conceptual RDF data model

Northwind Demo Database: RDF View Definition Extract prefix northwind: <http://www.openlinksw.com/schemas/northwind#> … create iri class northwind:Customer <http://^{URIQADefaultHost}^/Northwind/Customer/%U#this> (in customer_id varchar not null) … alter quad storage virtrdf:DefaultQuadStorage … from Demo.demo.Customers as customers from Demo.demo.Orders as orders … { Demo.demo.Customers Northwind RDF View Definition create virtrdf:NorthwindDemo as graph iri (“http://^{URIQADefaultHost}^/Northwind”) { … northwind:Customer(customers.CustomerID) a foaf:Organization as virtrdf:Customer-CustomerID ; northwind:companyName customers.CompanyName as … ; … northwind:fax customers.Fax as virtrdf:Customer-fax . … } } northwind:Customer(orders.CustomerID) northwind:has_order northwind:Order(orders.OrderID) as virtrdf:Order-has_order . Country Phone Postal Code Address City Fax Contact Title Contact Name Company Name Customer ID

Northwind Demo Database: Customer Table to RDF Entity Mapping Orders Table Germany Country 030 - 0074321 Phone 12209 Postal Code Obere Str. 57 Address Berlin City 030 - 0076545 Sales Represe-ntative Maria Anders Alfreds Futterkiste ALFKI Fax Contact Title Contact Name Company Name Customer ID companyName contactName contactTitle address city PostalCode country phone fax Alfreds Futterkiste Maria Anders Sales Representative Obere Str. 57 Berlin 12209 Germany 030-0074321 030-0076545 … Order/10643#this has_order Order/10692#this … has_order Customer/ALFKI#this prefix <http://demo.openlinksw.com/Northwind/> has_customer has_customer … ALFKI 10643 … ALFKI 10692 … Customer ID Order ID

LinqToRdf + Virtuoso

LinqToRdf to MusicBrainz - Conceptual Model Veneer

ADO.NET Data Services & Entity Data Model