=Paper=
{{Paper
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|storemode=property
|title=Linked Data Platform as a novel approach for Enterprise Application Integration
|pdfUrl=https://ceur-ws.org/Vol-1034/MihindukulasooriyaEtAl_COLD2013.pdf
|volume=Vol-1034
|dblpUrl=https://dblp.org/rec/conf/semweb/MihindukulasooriyaGG13
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==Linked Data Platform as a novel approach for Enterprise Application Integration==
https://ceur-ws.org/Vol-1034/MihindukulasooriyaEtAl_COLD2013.pdf
Linked Data Platform as a novel approach for
Enterprise Application Integration
Nandana Mihindukulasooriya, Raúl Garcı́a-Castro, and
Miguel Esteban-Gutiérrez?
Center for Open Middleware, Ontology Engineering Group
Universidad Politécnica de Madrid, Spain
{nmihindu, rgarcia, mesteban}@fi.upm.es
Abstract. Enterprises are increasingly using a wide range of heteroge-
neous information systems for executing and governing their business
activities. Even if the adoption of service orientation has improved loose
coupling and reusability, applications are still isolated data silos requir-
ing complex transformation and mediation for integrating them. The
W3C Linked Data Platform (LDP) Working Group aims to standardize
a RESTful way to read and write Linked Data. This opens the door for
industry to benefit more effectively from Linked Data by building inter-
operable LDP applications and implementing new approaches for En-
terprise Application Integration (EAI). For a wide industrial adoption of
LDP-based EAI, the advantages of LDP have to be clearly illustrated and
LDP needs to be assessed for enterprise readiness. This paper analyses
LDP as an EAI approach by considering both its advantages over exist-
ing approaches and identifying the gaps and challenging enterprise EAI
requirements it has to satisfy. The paper also presents lessons learned
from a project that uses LDP for integrating open source Application
Lifecycle Management tools.
Key words: Linked Data, Linked Data Platform, Enterprise Applica-
tion Integration, Industry Adoption
1 Introduction
Enterprise information systems play a key role in providing a technology plat-
form for executing the business processes of organizations. However, these sys-
tems have to be integrated in order to have a consistent unified view of the whole
enterprise. Integrating heterogeneous applications, each with its own data model
and business restrictions, is a complex problem and Enterprise Application In-
tegration (EAI) has evolved over time taking different approaches to solve this
issue, such as following a Service-Oriented approach, which is currently the most
widely used approach in the industry [1].
?
This research is supported by the ALM iStack project of the Center for Open Mid-
dleware.
2 Mihindukulasooriya, Garcı́a-Castro, and Esteban-Gutiérrez
The Linked Data1 principles promote publishing data in a machine-readable
manner using Web standards and interlinking them. On top of it, the Linked
Data Platform2 (LDP) specification defines a RESTful protocol for accessing
read/write Linked Data. This protocol brings new opportunities to application
integration at the data level which were not easily possible in previous EAI ap-
proaches. In order to ensure a wide adoption of LDP-based EAI, it is important
to advocate the concrete benefits of Linked Data over existing approaches. Fur-
thermore, it is also important to identify the gaps that need to be filled in order
to make Linked Data-based approaches more promising to the industry and to
provide an assessment of any potential risks.
As seen in previous approaches for EAI, there is a set of highly-demanding
enterprise quality requirements that an EAI technology needs to satisfy to be
widely accepted in the industry, such as security, transactions, performance, and
interoperability. For example, starting from a few basic specifications, the Web
Service standards stack gradually grew in numbers in order to satisfy these indus-
trial requirements. Similarly, we can expect the Linked Data Platform specifica-
tion to evolve and LDP middleware and tool support to become more available.
For building an industrial Linked Data-based EAI ecosystem, we need to
answer a few concrete questions that early adopters raise:
– What are the concrete benefits that Linked Data-based EAI brings when
compared to the current approaches followed in industry?
– Is this approach mature and enterprise ready? If not, which are the gaps?
– What are the lessons learned from the current projects using LDP for EAI?
This paper discusses these questions based on experiences derived from the
ALM iStack project3 , which integrates Application Lifecycle Management tools
by using the Linked Data Platform protocol and a common ontology. The paper
is organized as follows. After an overview of EAI and existing approaches in
Section 2, Section 3 introduces the Linked Data Platform protocol. Section 4
discusses the benefits of using LDP for EAI and the foreseen challenges. Section 5
presents a real world case study of using LDP for EAI and the lessons learned.
Finally, Section 6 draws some conclusions.
2 Enterprise Application Integration
Business processes comprise a set of activities performed by several stakeholders
of an organization in coordination with the organizational and technical envi-
ronment to realize a business goal [2]. Business applications help organizations
to carry out these processes more efficiently and generally consist of (1) business
logic or rules of a domain, (2) data stores managing the application persistent
state, and (3) a set of interfaces to interact with the applications (e.g., GUIs,
1
http://www.w3.org/DesignIssues/LinkedData.html
2
http://www.w3.org/TR/ldp/
3
https://sites.google.com/a/centeropenmiddleware.com/alm-istack/
Linked Data Platform for Enterprise Application Integration 3
services, APIs). Since business processes spread across several applications, there
is a high demand for integrating applications without making significant changes
to those applications or their underlying data models [3].
Enterprise Application Integration (EAI), defined as “the unrestricted shar-
ing of data and processing among any connected applications and data sources
in the enterprise” [4], aims to solve this problem by combining the technologies
and processes that enable business applications to exchange business level infor-
mation in formats and contexts that each understand [5]. However, often these
applications are backed by relational databases (or recently NoSQL databases)
and act as isolated data silos. This forces duplication of data and hinders in-
terlinking and the possibility of traversing through different applications that
manage the different aspects of a business process.
EAI can be viewed in three main levels: (i) physical integration (interconnec-
tion of devices via computer networks), (ii) application integration (integration
of software applications and database systems), and (iii) business integration (co-
ordination of functions that manage, control and monitor business processes) [6].
EAI can be designed using several topologies including point-to-point, message
broker, or service bus and can be implemented through different approaches:
shared database, file transfer, remote procedure calls, or message bus.
Service-Oriented Architecture (SOA), which is currently the most popular
approach for EAI in the industry [1, 7], is an architectural style for building
enterprise applications using independent business-aligned services that can be
combined into agile and flexible business processes [8]. Services are well-defined,
self-describing, and platform-agnostic computational elements that provide dis-
crete units of business functionality through a service contract and support a
rapid and low-cost composition of distributed applications [8, 9]. The standard
and discoverable interfaces provided by services help overcoming the application
connectivity challenge of EAI; however, the information integration challenges
require handling complex transformations between the different domain models
used by the applications. Furthermore, applications still act as data silos that are
not linked but duplicated in many applications. Despite Service-Oriented sys-
tems foster application communication and interoperability, they do not address
the semantic interoperability problem [6].
As an attempt to solve this, Semantic Web Services (SWS) try to com-
bine Web Services with Semantic Web technologies by annotating services with
semantic markup. Nevertheless, prominent SWS approaches like OWL-S [10],
WSMO [11], and SA-WSDL4 are still grounded on heavyweight XML-based
Web Service standards like SOAP, WSDL and XML Schema.
Representational State Transfer (REST) is an architectural style that is be-
coming popular in the industry and that defines a set of constraints for de-
signing a hypermedia system: (i) resource identification, (ii) uniform interfaces,
(iii) self-descriptive messages, (iv) hypermedia as the engine of application state
(HATEOAS), and (v) stateless interactions [12]. These principles allow building
scalable applications that can discover links to other resources at runtime us-
4
http://www.w3.org/TR/sawsdl/
4 Mihindukulasooriya, Garcı́a-Castro, and Esteban-Gutiérrez
ing identifiers within a resource representation and interact with these resources
through uniform interfaces without having previous knowledge [13]. Properly us-
ing the Linked Data and REST principles by design solves the data silos problem
by making data global and allowing the development of interlinked applications.
3 Linked Data Platform
RDF provides a simple and flexible data model that is well-suited for data inte-
gration and the conceptualization of domain models can be expressed in terms
of RDF Schema and OWL ontologies. The Linked Data principles help creating
a global data space [14] with typed links between data from different sources
[15], hence breaking isolated data silos. Machine-readable structured data with
explicit formal semantics that are expressed using standards makes merging, in-
tegrating, processing, and analyzing data possible without needing out-of-band
knowledge or proprietary tools. Links to related entities in data make it possi-
ble to start from a piece of data and traverse through different sources with a
follow-your-nose approach5 in order to discover more entities and get context
information.
The LDP protocol brings benefits from both the REST and Linked Data
worlds to application integration. The LDP specification provides a set of best
practices and a simple approach for a read-write Linked Data architecture, based
on HTTP access to web resources that describe their state using the RDF data
model. LDP introduces two main building blocks for building Linked Data ap-
plications: LDP Resources (LDPR) and LDP Containers (LDPC). LDPRs are
HTTP resources whose state is represented in RDF and that can be retrieved,
updated, and deleted using HTTP methods (adhering to the constraints enforced
by the LDP specification). LDPCs are specialization of LDPR which helps or-
ganizing other resources (i.e., LDPRs) as its members. LDPC serves two main
purposes: enumeration of its member resources and creation of new member
resources. In addition, the LDP specification provides a standard way for pagi-
nating large RDF resources and ordering triples inside LDP containers.
Whether RESTful applications are enterprise ready, i.e., they can fulfill the
quality requirements of EAI such as advanced security scenarios and handling
business transactions [13], is one of the concerns of LDP early adopters. As most
enterprise applications operate on a controlled environment where closed world
assumptions apply, whether Semantic Web languages such as OWL and RDF
Schema (which operate under an open world assumption) are still suitable for
data validation and ensuring data quality is another concern.
Furthermore, regarding Linked Data there is a major misconception about
the fact that data should always be publicly available under an open license.
Though this is true for Linked Open Data, it is possible to keep the data private
as Linked Closed Data [16] or Linked Enterprise Data [17] with limited access
within intranets protected by firewalls similar to most Enterprise Information
Systems in use today in industry.
5
http://patterns.dataincubator.org/book/follow-your-nose.html
Linked Data Platform for Enterprise Application Integration 5
4 Integrating Enterprise Applications using LDP
LDP enables a novel approach for integrating applications. Applications that
support the LDP protocol can expose all or part of their data using one or
more vocabularies and can consume Linked Data from other applications. In
contrast to traditional applications, the data that LDP applications expose and
consume can have links to data in other applications. Thus, these applications
are capable of crawling Linked Data, traversing through data according to their
business needs, and interacting with applications that expose those data using
the LDP protocol.
The first logical step towards adopting the LDP protocol in an industrial
ecosystem is to provide LDP interfaces to existing applications. There are two
approaches, shown in Figure 1, for achieving this: (a) to provide native support
for LDP by modifying the application or (b) to provide LDP support via an
adapter or a wrapper. On the one hand, providing native support will be more
preferable to take full advantage of the Linked Data principles by designing
applications that can benefit of the follow-your-nose approach of Linked Data.
On the other hand, providing an adapter would be a more feasible adoption path
in the beginning as it does not require any changes to existing applications. In
this case, however, protocol conversion might introduce some overhead and the
application business logic may not be aware of the links in the data.
Fig. 1. (a) Native LDP support vs (b) LDP adapters.
4.1 LDP Applications in the Context of EAI
EAI involves integration at different levels: physical integration, application in-
tegration, and business integration [6].
Physical integration of LDP applications uses the de-facto Internet protocol
suite infrastructure (TCP/IP) similar to traditional Web Service-based EAI.
Application integration, where most benefits from LDP are visible, can again
be divided into two different levels: application connectivity (interfaces) and data
integration. Even if both Web Services and LDP use the HTTP protocol to
connect applications, their use of it is different: while SOAP Web Services use
6 Mihindukulasooriya, Garcı́a-Castro, and Esteban-Gutiérrez
HTTP as a tunneling protocol with protocol layering [18], LDP uses HTTP as
an application protocol by using dereferenceable URIs for identifying resources
and HTTP headers to convey the interaction semantics, enabling applications
to discover affordances on resources only by using the HTTP protocol without
requiring any additional heavyweight protocol.
In data integration, there are three heterogeneity problems to be solved: syn-
tactic heterogeneity, structural heterogeneity, and semantic heterogeneity [19].
The usage of standardized data exchange formats solves the syntactic hetero-
geneity problem for both traditional and LDP-based EAI. The graph-based flex-
ible RDF data model obsoletes the structural heterogeneity problem and makes
integration from multiple data sources possible even if their schemas differ or
are unknown. Traditional EAI based on hierarchal XML data types with strict
structural schemas requires complex schema transformations. Ontology-based
data integration approaches can be used to overcome the semantic heterogene-
ity problem either by using a global ontology, multiple ontologies, or a hybrid
approach [20]. By following the links created according to the Linked Data prin-
ciples, new ontologies can be discovered which can be mapped to the ones that
the application is aware of with the help of ontology alignment techniques.
Approaches for business integration at the process level depend on how much
each application is aware of the whole business process and on who is driving
the process. Orchestration and choreography are two ways in which business
processes can be described and implemented [21]. In orchestration, the busi-
ness process is controlled and driven by an orchestrator in a centralized manner
and in choreography interactions are implemented as a distributed collaboration
between applications where each application is aware of its part of the whole pro-
cess. LDP applications can support both approaches. Further, LDP applications
can use the fourth Linked Data rule (i.e., include links to other dereferenceable
URIs so that they can discover more things) and the HATEOAS REST principle
to discover new applications without any previous knowledge about them and
to communicate with them using the LDP protocol, thus enabling agile business
processes. This is a major advantage over the existing approaches.
4.2 Challenging EAI Requirements
In addition to being able to integrate heterogeneous applications, EAI imposes
several requirements that have to be fulfilled for an approach to be adopted
and used in production. This section looks at some challenging requirements for
LDP-based EAI and their current state of the practice in RESTful and Linked
Data applications in the industry.
Data validation is a vital step for ensuring the quality of data in applications
and expressive schema languages and related tools are essential for effective
data validation. Both relational databases and XML have expressive schema
languages for defining the structure and the constraints on data. In RDF, which is
built upon the Open World Assumption and the Non-unique Name Assumption,
data validation becomes a challenge as the languages currently used to describe
these constraints (i.e., RDF Schema and OWL) are more suited for inferring
Linked Data Platform for Enterprise Application Integration 7
than for data validation and using them for validation could lead to unexpected
results [22]. Most applications require some validation to be done under a (local)
closed world assumption; the work done for tackling this problem includes adding
integrity constraints to OWL [23], closed world reasoning [24], SPARQL and
SPIN-based solutions [25], and Resource Shapes [22]. There is not a standard
for RDF data validation, though we can see a recent movement6 in that direction.
There are several security requirements including authentication, authoriza-
tion, integrity, confidentiality, and non-repudiation. A few authentication pro-
tocols are widely used by RESTful web applications: HTTP Basic Authenti-
cation and Digest Access Authentication7 , TLS8 , and SSL9 . Recently, a set of
user-centric decentralized URI-based identity systems became popular, includ-
ing OpenID10 , BrowserID11 , and WebID [26], and fit well with Linked Data
approaches. Regarding authorization, OAuth 2.012 is a widely used authoriza-
tion framework for web applications and Web Access Control13 (WAC) is a
decentralized system for authorizing users and groups where users are identified
by WebIDs and groups are identified by HTTP URIs. The S4AC [27], PPO [28],
RelBAC [29], and AMO [30] ontologies define fine-grained models for defining
and implementing access control for Linked Data. Though there is no standard
security stack for LDP applications, like in the case of the WS-Sec* stack [31],
we can see emerging technologies like WebID and WAC that have the poten-
tial of becoming W3C recommendations. However, there is work done on other
security requirements, such as digitally signing and encrypting RDF data [32].
Usually, a business process is composed of several business transactions [33],
i.e., consistent changes from one state of the business to another state that are
driven by a well-defined business function. These transactions need to support
ACID (Atomicity, Consistency, Isolation, Durability) to ensure that a system
is always at a consistent state. With REST gaining traction in the industry,
several RESTful transaction models have been proposed in the last few years
[34] including the Try-Cancel/Confirm pattern [35], action resources that expose
workflow-related operations on the parent resource [36], lockable resources [34,
37, 38], or Optimistic Concurrency Control [39]. In order to have interoperability
at industrial level, one of these has to become a standard.
However, the usage of a strong consistency model introduces other problems.
As the CAP (or Brewer’s) theorem states, a distributed application cannot pro-
vide the following three guarantees simultaneously: (1) consistency, all nodes
see the same data at the same time; (2) availability, every request receives a
response about whether it was successful or failed; and (3) partition tolerance,
6
http://www.w3.org/2012/12/rdf-val/
7
http://tools.ietf.org/html/rfc2617
8
http://tools.ietf.org/html/rfc5246
9
http://tools.ietf.org/html/rfc6101
10
http://openid.net/specs/openid-authentication-2_0.html
11
http://persona.org/
12
http://tools.ietf.org/html/rfc6749
13
http://www.w3.org/wiki/WebAccessControl
8 Mihindukulasooriya, Garcı́a-Castro, and Esteban-Gutiérrez
the system continues to operate despite arbitrary message loss or failure of part
of the system [40, 41].
There exists a trend for using weaker consistency models in distributed ap-
plications so that high-availability and partition tolerance can be guaranteed. A
popular model is that of eventual consistency, which ensures that if no new up-
dates are made to a given data item, eventually all read accesses to that item will
return the last updated value (the system converges) [42]. Distributed systems
based on this model provide BASE guarantees (Basically Available, Soft-state
with Eventual-consistency) in contrast to the ACID guarantees provided by tra-
ditional transaction-based applications [43].
In addition to these requirements, there are several others that have to be
supported including performance requirements (throughput or response time),
discovery requirements (finding vocabularies and data model restrictions), relia-
bility requirements (reliably do operations on an unreliable infrastructure includ-
ing network failures, unavailability of the destination system and other possible
error conditions), and contract requirements (expressing quality agreements such
as SLA contracts [44]). Further, unlike in the Web, enterprises may want to en-
sure data consistency and link maintenance [15], i.e., there are no dead links or
dangling pointers when resources are deleted or moved and links always point
to the correct resources, which is a challenge which may require notifications or
eventing.
5 Application Lifecycle Management with Linked Data
This section briefly describes a case study of using the LDP protocol for building
a proof-of-concept that integrates the Application Lifecycle Management (ALM)
tools used by a software development organization.
The software development process involves a set of activities including project
planning, requirements gathering, software design, software development, testing
and quality assurance, deployment, support, etc. Each of these activities produce
and consume different sets of artifacts like project plans, software requirement
specifications, architecture documents, source code, or test cases and involves
possibly different teams carrying out these activities using different tools. Col-
lective management, coordination and governance of all these activities and ar-
tifacts is called ALM [45].
Successful ALM requires the horizontal integration of heterogeneous infor-
mation systems that track the different activities of the process in order to have
an overall view of such process. This becomes a complex integration problem
because it involves a set of heterogeneous tools coming from different vendors
and open source communities and using different technologies. As a concrete ex-
ample, a software development team using open source tools may use Eclipse for
software development, Bugzilla for issue tracking, TestLink for test case man-
agement, and so on.
The ALM iStack project is developing LDP middleware and a proof-of-
concept application to demonstrate how open source ALM tools can be seam-
Linked Data Platform for Enterprise Application Integration 9
Fig. 2. Architecture of ALM iStack Proof-of-Concept
lessly integrated using the Linked Data Platform protocol and a common vo-
cabulary. The project uses a hybrid integration approach [20] with an enhanced
version of the vocabularies defined by Open Services for Lifecycle Collabora-
tion14 (OSLC), an open community that has the goal of building specifications
for the integration of ALM software following the Linked Data principles. The
strategy followed is to develop LDP adapters for each ALM tool and to integrate
them using an LDP client that acts as an orchestrator of the process (Figure 2).
Adapters expose the existing application data as Linked Data by minting
dereferenceable HTTP URIs for those entities. There has been much work done
in exposing legacy data as Linked Data and specifications like W3C R2RML15
provide guidance for this. To increase performance and reduce HTTP traffic and
application response times, the adapters are designed to expose LDP resources
with proper granularity and to use composite resources when appropriate.
The developed adapters expose data using a shared ALM ontology. The mis-
match between the application data model and this ontology is handled by the
adapters by persisting the extra information they require to handle the mis-
match. In addition, adapters use a SPARQL-based approach to verify integrity
constraints and validate data.
The security of the adapter is decoupled from the security mechanism used
by the application using the trusted subsystem security pattern16 ; thus, adapters
are free to use its own security approach.
14
http://open-services.net/
15
http://www.w3.org/TR/r2rml/
16
http://msdn.microsoft.com/en-us/library/aa905320.aspx
10 Mihindukulasooriya, Garcı́a-Castro, and Esteban-Gutiérrez
For managing coreferences of entities residing in different applications, ALM
iStack includes a coreference service (i.e., Identity Management Service) [46]. For
the time being, no support for transactions or reliable messaging is provided.
6 Conclusions
Linked Data-based EAI has several advantages over current EAI approaches
when it comes to application and data integration. To summarize, (a) Linked
Data allows having global identifiers for data that can be accessed using the
Web infrastructure and typed links between data possibly from different appli-
cations (b) the graph-based RDF data model allows consuming and merging data
without having to do complex structural transformations, and (c) application-
specific domain conceptualizations expressed in terms of RDF Schema or OWL
ontologies can be aligned and mapped to other applications using knowledge
representation techniques much easier than in traditional approaches.
The Linked Data Platform protocol provides a standard uniform interface for
managing these data. Having a standard for building interoperable Linked Data
applications is a big step towards the industrial adoption of Linked Data as an
application integration approach. LDP allows breaking data silos in applications
and helps building integrated applications that can link to data in related ap-
plications using standards, enabling clients to discover and interact with those
applications in a scalable manner.
However, there is still some work to be done on fulfilling the quality require-
ments imposed by the industry to make the approach enterprise ready and ex-
ploit the full potential of LDP such as supporting advanced security scenarios,
transactions, data consistency, link maintenance, notifications, eventing, data
validation, and discovery of vocabularies and data model restrictions. At the
moment, some of these requirements are fulfilled by LDP applications using their
own proprietary mechanisms but having interoperable standard mechanisms will
help LDP to be more widely adapted as a novel approach for EAI.
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