This work presents a comparative study on the RDF processing APIs implemented in PHP. We took into consideration diferent criteria including, but not limited to: the solution for storing RDF statements, the support for SPARQL queries, performance, interoperability, and implementation maturity.

1. Modern PHP RDF toolkits:
a comparative study
Marius-Gabriel Butuc
Alexandru Ioan Cuza University, Department of Computer Science,
Iasi, Romania
,
mbutuc@info.uaic.ro
http://www.infoiasi.ro/
Abstract. This work presents a comparative study on the RDF pro-
cessing APIs implemented in PHP. We took into consideration different
criteria including, but not limited to: the solution for storing RDF state-
ments, the support for SPARQL queries, performance, interoperability,
and implementation maturity.
Key words: API, PHP, RDF, SPARQL.
1 Introduction
Today, we can find a myriad of Web applications that can be considered in-
telligent, accomplishing the visionary ideas that were once considered ahead of
one’s time. Since we are relaxing more and more the constraint of physicality of
information, we now take the challenge of finding the ultimate way of exchang-
ing information. Following this path, the Semantic Web development aims at
defining the meaning of information and services on the Web, allowing enhanced
information discovery, data integration and the automation of a variety of tasks.
At the core of the Semantic Web we find the Resource Description Framework
(RDF) and all the specifications and tools that provide solutions for structuring
and semantically describing data.
For the rest of this paper, we will compare the current solutions addressing
these perspectives. We will start by discussing the architecture of a Semantic
Web application in Section 2, briefly browse the history of the PHP toolkits
developed so far in Section 3 and continue by comparing the two main pure-
PHP RDF application programming interfaces (API) today.
2 Architecture of a Semantic Web Application
RDF allows us to model information as statements–sets of triples which can be
exchanged over the Web. Believing that a connected Web is a smarter Web, the
Semantic Web goal goes far beyond building a web of machine-processable data,
aiming at enriching lives through access to information [1]. Given this goal, many
companies began developing components of Semantic Web applications both as

2. free software and commercial. The main components that embody a Semantic
Web deployment [2] are:
– RDF Parser: a system component that reads and interprets the statements
from RDF files. A RDF parser can understand one or more serialization
formats (e.g., RDF/XML, N3, Turtle, N-Triples etc.).
– RDF Serializer: the component that writes the triples to file in one of the
several serialization formats.
– Scraper: an instrument for extracting structured information from websites.
– Converter: an instrument for transforming data from one form (e.g., rela-
tional databases) into RDF.
– RDF Store: a purpose-built database optimized for the storage and retrieval
of triples. It is also called a triplestore and one of its main operations is to
merge RDF stores.
– RDF Query Engine: brings the ability to retrieve information from the
triplestore using a query language, habitually SPARQL.
– Inference Engine: frequently integrated with the query engine, it performs
inferences according to given inferencing rules.
– Application Interface: uses the data from the triplestore in the interaction
with users.
The relation between these components is depicted in Fig. 1
Fig. 1. The relation between Semantic Web application components [2]
3 Brief History of PHP RDF Toolkits
Given the new technologies, two complementary perspectives [3] arose:
1. How can PHP developers benefit from the Semantic Web (technologies)?
2. How can Semantic Web projects benefit from PHP (developers)?
Facing this challenge, several new projects emerged developing from the PHP
version of Repat RDF parser [4] to battle tested Drupal components and even
full blown APIs like ARC and RAP. As we can see in Fig. 2, only some of them

3. Fig. 2. Searching for modern pure-PHP RDF APIs.
survived [5], while there are still parts of the Semantic Web big picture that are
not within reach for PHP developers (e.g., Description Logic reasoners).
For the rest of this work we only focus only on ARC RDF Classes for PHP [6]
and RAP: RDF API for PHP [7] because those APIs provide most of the com-
ponents of a Semantic Web application, as detailed in Fig. 3.
Fig. 3. Components implemented in both Semantic Web APIs

4. 4 ARC vs. RAP
RAP is a Semantic Web toolkit for PHP developers. RAP started as an open
source project at the Freie Universit¨t Berlin in 2002 and has been extended
a
with internal and external code contributions since then.
The motivation behind ARC [3] was the need for a set of tools that are
easy to combine with existing software, in contrast with contemporary toolkits
that had non-standard extensions. There was a need for supporting the already
existing Web 2.0 data formats (e.g., microformats, JSON, Atom, RSS2), for a
toolkit that was light-weight and optimized for PHP. Thereby, ARC uses object-
oriented code for its components and methods, but the processed data structures
consist of simple associative arrays, which leads to faster operations and less
memory consumption. Also, as of June 2008, ARC’s structures are aligned with
the Talis platform.
4.1 API-Paradigm
Both solutions offer Statement-centric and Resource-centric APIs, but RAP goes
one level further, offering an Ontology-centric API in extension to the Resource-
centric one.
4.2 RDF Parser/Serializer
RAP supports RDF/XML, N-Triples, N3, TriX, GRDDL and RSS/ATOM, while
ARC has both generic and specific parsers for RDF/XML, Turtle, N-Triples, RSS
2.0, SPOG or HTML and can only serialize in RDF/XML, RDF/JSON, Turtle
and N-Triples.
4.3 Triplestore and Query Engine
Both toolkits offer in-memory and database storage. While ARC only supports
MySQL as RDBMS, RAP supports any ADOdb compliant databases (30+).
Even if both solutions support SPARQL, here ARC takes the lead, supporting
SPARQL+ which is a subset of the SPARQL Update [8].
A protocol-compliant endpoint class which can be used for HTTP-based data
access as well as a client for remote SPARQL endpoints is delivered by both APIs.
4.4 Licence
Both toolkits are Free Open Source Software, RAP being distributed under
LGPL and ARC under GPL + W3C Licence.

5. 5 Conclusions
We can use both APIs servers running PHP5 as well as PHP4, but after test-
ing, the ARC toolkit proves to be more focused on core tasks (e.g., parsing
RDF/XML) thus providing better performance. Still, this performance comes
to the cost of lacking functionality, especially compared to RAP which delivers
from the essential reasoning support (e.g., RDFS and some OWL Rules) till a
GUI for managing database-backed RDF models, or a graph visualization mod-
ule, and an in-depth documentation for all features. While RAP stagnates at
version 0.9.6 since February 2006, ARC enjoy a more effervescent development
and community, the latest ARC2 release dating November 2009.
As a bottom line, it’s best to master them both and to use one or the other
depending on your projects requirements.
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