Programming the Semantic Web

Steffen [email protected]

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Web Science & Technologies

University of Koblenz ▪ Landau, Germany

Programming the Semantic Web

Steffen Staab & Team@WeST


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This presentation contains program code, engineering, speculation and worse.It may be viewed as offensive by some viewers.


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Semantic Web: Great History, Still Long Way to Go!

Big Systems

Practice

Research influence

Wanted: mainstream adoption!

Target: ProgrammingTarget: Programming


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SEMANTIC WEB PROGRAMMING: BIRD‘S EYES VIEW


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Semantic Web Programming

Linked Data

SPARQL endpoint

RDF fileHypothesis:Semantic Web data is wonderful, but programming with Semantic Web has changed too little since 2000 and still is a mess.

We promise flexibility, but code

still hard to maintain.

Ontology


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Semantic Web Programming

Linked Data

SPARQL endpoint

RDF file

„Inside“Data Mgmt

Eclipse

Visual Studio

....

Ontology


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Semantic Web Impedance Mismatch

„Inside“http getDereferencingQuery executionUpdating IndexingTriplification IntegrationStreaming


Eclipse

Visual Studio

....

Mind the

Gap!


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Semantic Web

Linked Data

SPARQL endpoint

RDF file


„Outside“

Data Mgmt

Eclipse

Visual Studio

....

Ontology


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Semantic Web


„Outside“

Data Mgmt

Eclipse

Visual Studio

....

„Outside“ Understanding

by the developer „Search + Code“ „Browse + Code“

Triple-object mapping Code generation Process of federation

LD vs endpoint Models of federation

Abstraction layers that facilitate a developer‘s life


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Programming with Data: What does it cost?

Ctotal = t*Ctool + d*t*Clearn + s*Cdeu + s*Cmap + n*Ccode

Ctool : Costs for building t many tools, shared; almost free

Clearn: Costs for learning how to use technology per developer dCdeu: Costs for data engineering/understanding s sources

Cmap : Costs for mapping data structure for s sources to objects

Ccode : Actual costs for accessing/manipulating data n times

„Inside“Both „Outside“


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SWOT of Semantic Web Programming


threat

opportunity

opportunity

weakness

Not a strength, yet!

strength/weakness

Strong in flexibilitySomewhat weak in

performance

„Outside“

as good as RelDB is not good enough!


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Target cost scenario 1: Automated setup

Ctotal

n (as in n*Ccode )

SemWeb coding efforts

RelDB/XML coding efforts

Applies to small nD

iff.

cost

s fo

r le

arni

ngS

etup

co

st

0


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Target cost scenario 2: Manually perfected setup

Ctotal

n (as in n*Ccode )



„Perfect“ object model shields

developer from database

ideosyncracies

Set

up c

osts

0


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Intermediate conclusion

Minimize costs for setup:

Clearn: Costs for learning how to use technology per developer dCde: Costs for data engineering/understanding s sources

Cmap : Costs for mapping data structure for s sources to objects

Minimize costs for core programming:

Ccode : Actual costs for accessing/manipulating data n times

Costs for learning and understanding constitute a threat!

Need to be overcome!


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SEMANTIC WEB PROGRAMMING: IDENTIFYING SOME PITFALLS


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Example scenario: Jamendo

Data about license free music ~ 1 Million triples classes and predicates

from 18 different ontologies FOAF, Tag ontology,

music ontology, …

Simple programming task: List for every music artist,

all the records they made


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Software Development Process Overview

data model design

revised data model design

data model prototype

data queries

final data model

Creation of initial data

model

Exploration of the data

source

Creation of model in

code

Query design / implementation

Mapping of query results


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Accessing Artists Using Apache Jena


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From artists to songs

Observations SPARQL queries are strings Results are strings Requires good understanding of the data source

RDF Typing is lost


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Related Work on RDF Access

Static Typing Errors detected before

execution Misspelling discovered

by compiler! Anectode: 2nd place

because of misspelt var.

Static types are form of documentation Less knowledge about

data source required

Better IDE integration / autocompletion

Code generation Sommer Winter OntoMDE

Dynamic Typing E.g. ActiveRDF

(Oren et al 2007)) “convention over

configuration”

dynamic metaprogramming allows for slick code

Criticism


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SEMANTIC WEB PROGRAMMING:

LITEQ – OUR OUTSIDE APPROACH


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Programming against Jamendo

c1


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Node Path Query Language Using Autocompletion

Exploration of classes

Exploration of relations

Querying for instances


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Node Path Query Language Using Autocompletion




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Node Path Query Language: Query Formulation




Type set of mo:MusicArtist

No definition or declaration needed


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Node Path Query Language for Code Development




Developing code with queries

All translated into SPARQL queries at• Development time• Type inference at compile time

(but also as part of IDE)• Querying again at run time

One language to bind them all


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Node Path Query Language for Code Development




Developing code with queries

Developing code with new classes

All translated into SPARQL queries at• Development time• Run time update• Persistence!


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NPQL

NPQL (Node Path Query Language) Intensional Queries

Describing RDF classes and properties for reuse in IDE and in host language metaprogramming

Extensional Queries Class instances and property instances

Compilation to SPARQL for reuse of existing endpoints

Ongoing discussion about details of NPQL


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LITEQ

NPQL (Node Path Query Language) Intensional Queries Extensional Queries Compilation to SPARQL

LITEQ (Language Integrated Types, Extensions and Queries) Implementation of NPQL as F# Type Provider in Visual Studio Autocompletion using NPQL queries Automatic typing

of extensional query resultsby intensional queries


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Cost savings


Ctool : open source

Clearn: not free – though autocompletion reduces cognitive load

Cdeu: not free – understanding the RDF schema from your IDE

Cmap : 0

Ccode : a lot less than for dotNet RDF (Apache Jena?!!)little bit more than for a fictitious perfect object model


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Halstead metrics for different tasks:

Conventional Semantic Web programming approaches waste up to 50% of your efforts!


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Speculation 1

Ctotal

n (as in n*Ccode )



Applies to small n

Diff

. co

sts

for

lear

ning

Speculation 1: Using ontologies and RDF schemata, we can develop more efficiently

using the right tools!


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Halstead metrics for different tasks:

If someone gives me a perfect RDF-to-OO mapping for freethen I will not care about whether it is RDF or RelDB

underneath!


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Speculation 2

Ctotal

n (as in n*Ccode )



„Perfect“ object model shields

developer from database

ideosyncracies

Diff

. co

sts

for

setu

pSpeculation 2: For large programmes, our tools need to offer better support to reduce

setup costs!


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Issues

No schema many LOD sources do not have schema


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Issues


Useless schema

New kinds of (?) schema induction!


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Issues


Useless schema Property-based schemata

Cf. Homoceanu et al ISWC 2013• ask for all movies – not possible by asking for class movie,

but only for different property combinations


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Outlook wrt LITEQ

Integration of schema induction

Programming the Semantic Web as a whole Federated queries link traversal-based queries

More expressive query language Composed data types in tractable DL

More precise integrated type inference (composed) types from RDF data source type inference in host language


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CONCLUSION


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Semantic Web: Make Developers More Productive

Linked Data

SPARQL endpoint

RDF file


„Outside“

Data Mgmt

Eclipse

Visual Studio

....

Ontology


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Semantic Web

Social Web & Web Retrieval

Interactive Web & Human Computing

Web & Economy

Software & Services

Web Science & Technologies Team & Research

Computational Social Science

Thank You!

Ralf Lämmel

EvelyneViegas


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References

S. Scheglmann, A. Scherp, S. Staab. Declarative Representation of Programming Access to Ontologies. In: 9th Extended Semantic Web Conference (ESWC2012), Heraklion, Greece, May 27-31, 2012.

Daniel Oberle. How Ontologies Benefit Enterprise Applications. Semantic Web Journal. http://www.semantic-web-journal.net/content/how-ontologies-benefit-enterprise-applications-0

S. Homoceanu, P. Wille, W.-T. Balke. ProSWIP: Property-Based Data Access for Semantic Web Interactive Programming. In: ISWC-2013

C. Saathoff, S. Scheglmann, S. Schenk. Winter: Mapping RDF to POJOs revisited.

E. Oren, R. Delbru, S. Gerke, A. Haller, S. Decker: ActiveRDF: object-oriented semantic web programming. WWW 2007: 817-824

S. Scheglmann, S. Staab, M. Thimm, G. Gröner. Locking for Concurrent Transactions on Ontologies. In: 10th Extended Semantic Web Conference (ESWC2013), Montpellier, France, May 26-30, 2013.

M. Konrath, T. Gottron, S. Staab, A. Scherp. SchemEX – Efficient Construction of a Data Catalogue by Stream-based Indexing of Linked Data. In: Journal of Web Semantics. Special issue on Semantic Web Challenge Winners 2011. Elsevier, Volume 16, November 2012, pp. 52-58.

W. Cook, A. Ibrahim. Integrating Programming Languages & Databases: What’s the Problem?? http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.66.7169&rep=rep1&type=pdf

Programming the Semantic Web

Technology

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