=Paper=
{{Paper
|id=None
|storemode=property
|title=Supporting Content Provision in Environmental Information Infrastructures
|pdfUrl=https://ceur-ws.org/Vol-679/paper5.pdf
|volume=Vol-679
|dblpUrl=https://dblp.org/rec/conf/enviroinfo/SchadeD10
}}
==Supporting Content Provision in Environmental Information Infrastructures==
https://ceur-ws.org/Vol-679/paper5.pdf
Supporting Content Provision in Environmental
Information Infrastructures
Sven Schade1 and Laura Díaz2
1
Institute for Environment and Sustainability
European Commission, Joint Research Centre
Ispra, Italy
2
Institute of New Imaging Technologies
University Jaume I
Castellón, Spain
sven.schade@jrc.ec.europa.eu, laura.diaz@uji.es
Abstract. Information Infrastructures for managing and providing
environmental resources are requested by numerous initiatives on regional,
national, and international scales. While much research focuses on the
discovery and consumption of provided content, environmental data and model
provision is hardly addressed. Each time an expert creates new information or
develops a novel scientific algorithm it is delegated to an expert in information
and communication technology to make this content available in a given
Environmental Information Infrastructure (EII). From our point of view, this
workflow is a bottleneck in sharing environmental content that impedes the
efficient maintenance of EII. Accordingly, we have extended the classical three-
layered EII architecture with a middleware for assisted content publication and
deployment. A first implementation for data publishing is in place, while
investigations on the publication of environmental models are ongoing. In this
position paper, we briefly present the status of our work and discuss
possibilities for publishing environmental models. We point to related activities
and outline our future plans. We hope that our contribution will help to increase
content availability in EIIs in standard basis and thereby will aid content
discovery and model composition.
Keywords: INSPIRE, GEOSS, SDI, Environmental Information
Infrastructures, standard services, model web, publishing, deployment.
Introduction
Due to rising challenges of climate change and natural hazards, environmental content
sharing became a central need in environmental sciences [1]. Since many considered
phenomena, such as wild fires, floods or change in biodiversity, cross administrative
borders initiatives for establishing Environmental Information Infrastructures (EII) on
different scales emerged over the past years. Those include Infrastructure for Spatial
Information in Europe (INSPIRE) and Global Monitoring for Environment and
2 Sven Schade and Laura Díaz
Security (GMES) on European level, and Global Earth Observation System of
Systems (GEOSS) worldwide. An analysis of these three and their interplay has been
published recently [2]. In a nutshell, efforts on following INSPIRE implementing
rules in GMES are ongoing, while both can be seen as part of European contribution
to GEOSS. INSPIRE and GMES also contribute to the Shared Environmental
Information System (SEIS) initiative. The concepts behind SEIS focus mainly on
reporting but they are still evolving.
So far, EIIs assume that only Information and Communication Technology (ICT)
experts can provide content as services. This is because current EIIs are based on
Service Oriented Architectures (SOA) where services are implemented according to
international agreements and standards. The deployment mechanisms imply to
understand these standard service specifications and their implementations. ICT
experts became the only mediator between the environmental experts, who create the
content, and the infrastructure for content sharing [3] [4].
In order to improve the given situation, we suggested extending existing
architectures with components and mechanisms, which assist EII users in content
deployment [4]. The GEOSS Service Factory (GSF) realizes this proposal. In the next
section, we describe the GSF, and point to related work. As we intent to extend GSF
with deployment capabilities for (environmental) models, we discuss possibilities and
a future stepwise development. We conclude this position paper by summarizing our
findings and by outlining our future development plan.
Recent GSF Developments and Related Work
We enable content deployment by adding a (fourth) layer to the classical EII
architecture (Figure 1). This middleware layer (GSF, dashed lines in the figure), acts
as a mediator to provide content ‘as a Service’ to an EII, which is compliant with
INSPIRE and GEOSS. With the GSF, applications became able to push newly created
content into EIIs using common formats. Appropriate access services are selected
based on content types: Metadata, Data, Model, and Warning.
Applications Applications
Workflow Engine Application Logic Service Connector Workflow Engine Application Logic Service Connector
Warning
Warning Services as a
Service
Model
Geospatial Networking Services as a
Processing Services
Discovery Download View Processing Service
Data
Data and Metadata Services as a
Discovery View Download Service
Deploy
(GEOSS) Service Factory as a
Service
Geospatial Content Geospatial Content
Metadata Data Models Metadata Data Models Warnings
Figure 1: Extending the classical EII architecture (left) with GSF (right).
Supporting Content Provision in Environmental Information Infrastructures 3
It might be noticed that the service layer was extended by Warning Services in order
to address upcoming requirements for event notification. Among other information
resources, warnings are created in the application layer, for example by spatial
decision support systems that integrate available models and execute them on the
available data sets. Warning Services are used for managing all warnings that have
been published within the EII and distribute according notifications to the EII users.
These notifications may follow push or pull based approaches.
In order to provide GSF as a (web) service itself. We decided to use a common
geospatial standard, the Web Processing Service (WPS) [5]. WPS specification allows
encapsulating all kinds of functionality, and it has been proven as mature to expose
processing functionality in EII [6], therefore it looks appropriate to describe the GSF
interface to provide content publication capability. The added value is that due to the
fact that the use of WPS is increasing as well as the number of implementations both
for service and client side. To access to GSF from any application any generic WPS
client can be used [new7]1.
We designed the GSF using the Abstract Factory pattern from software
engineering [8]. The pattern provides a central entry point for content
creation/deployment (the Factory), which encapsulated task delegation to specialized
deployment components. In this way, the current implementation is easy to extend. As
an abstract factory, the GSF holds a group of concrete factories; each of them dealing
with a distinct service type and deploying content via transactional service interfaces.
A proof of concept is provided for data deployment in the context of the European
Forest Fire Information System EFFIS [9]. Here, GSF is able to provide a unique
entry point to deploy vector data (shape files), raster data (GeoTIFF) and even user
contributed content (KML) in a View Service and in a Download Service existing in
EFFIS. GSF is also able to register basic metadata in a Discovery Service. So far,
GSF is not able to deploy processing content such as environmental models, like fire
risk calculations or procedures for burned area assessment.
Much research on model deployment has been carried out, including the Model
Web concept [10], work on model decomposition [6], and outcomes of the projects
that are listed on the web page of this workshop (envip 2010). Still we require
scenarios of using GSF for model deployment and have to specify a development
plan.
Model Deployment with GFS
At this stage, we remark the following options for model deployment (order indicates
complexity, from simple to most difficult implementation):
1 We have used a generic HTTP client for testing, and a self developed java client [9] but many
projects such as 52North and uDIG already provide graphical user interfaces for WPS
execution.
4 Sven Schade and Laura Díaz
(1) Deploy conceptual model descriptions to a repository. First, we concentrate on
the description of scientific models, which create environmental information.
For example, the processing steps, required to generate a burned area map, may
be described and deployed as standard encoding of a workflow language. We
suggest using the Business Process Modeling Notation (BPMN) [11] for this
purpose. Such information helps to understand the model to generate
environmental data. Discussions on model improvements may be triggered.
However, BPMN does not provide information on model semantics. We
propose using a vocabulary, which is shared within the EII community, for this
purpose. It should be available from a shared registry and should be used for
labeling the various BPMN elements.
(2) Deploy executable files to repository. Following the initial ideas of the Model
Web [10] and in line with GEOSS, models may be provided as executables (as
*.exe, *.jar, etc) in a repository or Web Accessible Folder (WAF) following
GEOSS terminology. Users looking for models may just be provided with a
simple list of available files and their formats. For example, a package for
statistical calculations of burned area characteristics can be offered stand alone.
Execution will still require download and invocation in a suited environment,
but at least models become sharable.
In order to make such an implementation usable, we face a model description
problem. We require metadata for model evaluation and use. To make a model
executable, users will require information about: input and output parameters,
required operation systems, versions, and libraries. All may be affected by
licensing issues. Additionally, supported interfaces should be described in a
common manner. Again, descriptions of model semantics are required.
Approaches, such as Web Service Modelling Ontology (WSMO) [12], try to
address such issues for web services, but can this be projected to multiple types
of executables?
Complementary to the above, we face the practical problem of obsolescence,
i.e. required basic technology or software may simply be outdated and not
available anymore. Open archives try to tackle these problems of long-term
data preservation [13]. Nevertheless, it has to be ensured that all needs to
execute the specific environmental modeling algorithms are covered.
(3) Deploy executable model descriptions to a Processing Service. WPS has been
proven as a technology useful to expose and share processing capabilities in the
EII domain [6]. Existing WPS software like 52North implements transactional
capabilities [14], to be added to extend the upcoming version 2.0 of WPS.
Among other new functionalities WPS 2.0 is considering to deploy new
processes in running instances. In other words WPS will support the concept of
Composition as a Service (CaaS) [15].
We consider deploying executable process descriptions (using, for instance,
Business Process Execution Language (BPEL)) as a next deployment step. In
this case, chainable service instances have to be available within the EII and
the model has to be provided as an executable process description. For
example, assuming all required data is available as Download Service and each
processing task as a WPS, the complete burned areas calculation workflow
could be made available. A Processing Factory within the GSF would deploy
Supporting Content Provision in Environmental Information Infrastructures 5
that script and the composed model will be directly available as a distributed
Processing Service described with WPS interface. The BPEL deployment
functionality of the 52north implementation of WPS [14] may serve as a
starting point. However, the use of BPEL limits possible service compositions
to components, which operate via SOAP/WSDL.
(4) Deploy existing software to a Processing Service. The final step, to expose
scientific models fully, is to migrate binary-encoded model components as
Processing Services [6]. In order to assist the domain expert and to automate
this process as much as possible, we require sophisticated deployment
mechanisms and a methodology for workflow modeling with domain experts.
Challenges, such as deployment of software developed in diverse programming
languages (FORTRAN, Java, etc) must be overcome. Similar issues hold for
the operating platforms (windows, unix) in which the models have been
developed. Distributed computing, and in particular the ‘mobile code
approach’ [16], in which executable algorithms are sent across a network and
executed at distinct nodes, may provide solutions. The relations to grid
computing, cloud computing, and virtualization require further exploration.
We believe that the overall solution can only be semi-automatic. For
example, only distinct parts of EFFIS can be provided as decoupled processes,
due to software packages and dependencies. As for all other options, model
semantics still have to be defined in some form of metadata.
Conclusions and Future Work
We argued that content deployment to EIIs faces complex deployment issues and a
central bottleneck in environmental information sharing. The GEOSS Service Factory
(GSF) was proposed as a solution. Although the GSF concept is supported by a proof
of concept implementation for providing environmental data, detailed elaborations for
model deployment remain challenging. We pointed to related research and projects.
On this basis, we argued for four possible approaches for model provision. As these
complement each other, we plan to address them sequentially. Implementations will
be guided by the EFFIS example. The GSF will help to increase content availability in
EIIs and thereby will aid information discovery and model composition.
Offering GSF as a service provides means to secure deployment. According
implementations may be considered in future. This notably differs from a ‘secure’
execution of models on external machines. The latter is out of the scope of our work.
Acknowledgements
The presented work was partially founded by EUROGEOSS (FP7-ENV-2008-1-
226487). The authors thank their colleagues from the Spatial Data Infrastructure Unit
of the Joint Research Centre for numerous discussions that shaped the GSF principle.
Four anonymous reviewers provided constructive comments for improving an earlier
version of this document.
6 Sven Schade and Laura Díaz
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