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Using real data to solve specific problems, these use scenarios Service Oriented Architecture (SOA) as a framework, and
can be transformed into use cases and implemented within an describe the flow of steps as a “business process” using SOA
interoperable, distributed component architecture. Different terminology and build on the OpenModeller technology. In
parts of that infrastructure have already been established this paper, we extend the scope, and present an SOA
independently by the IPCC and by the Global Biodiversity architectural solution developed for analyzing the impact of
Information Facility (GBIF) in their own areas, respectively. climate change on biodiversity, including the required use
However, linking major infrastructures in separate scenario. Because acquiring and processing environmental
domains together will require additional sources of metadata data is a crucial step in this analysis, we describe the SOA
and related infrastructure services. That is, unless the framework and the developed architecture components and
integration is done using customized point-to-point protocols services which are standard-based according to GEOSS
where provider and user know each other but third parties are requirements. We present how these were used in the GEO
excluded. The Global Earth Observation System of Systems IV Summit in Cape Town in November 2007 for on-the-fly data
(GEOSS) now promises to make these disparate services discovery and selection (Nativi et al., 2007b). Finally, we
available through its Clearinghouse registry of registries describe the system and the experiments which are part of
system. Interoperability Pilot Process (IP3). This is an action of the
The Group on Earth Observations (GEO) currently includes GEOSS AR-07-01 Task (GEO, 2007–2009). Several components
76 member countries, the European Commission, and 51 and services are already registered in the GEOSS registers. We
intergovernmental, international, and regional organizations. believe that presentation of this work can help inform the
GEO envisioned a “system of systems” to help realize a future ecological and biodiversity community of the importance of
wherein decisions and actions for the benefit of humankind GEOSS for efficient macroecological research.
are informed via coordinated, comprehensive and sustained
Earth observations and information (GEO, 2005). The GEOSS 1.1. The Species Response to Climate Change use scenarios
Implementation Plan spans 10 years (2005–2015) and recog- for GEOSS IP3
nises nine Societal Benefit Areas (SBAs) including Climate,
Ecosystems and Biodiversity. The GEOSS strategy consists of The presented SOA framework was applied to implement and
leveraging existing systems and services and promoting demonstrate the Climate Change and Biodiversity use sce-
interoperability through the adoption of a Service Oriented nario of the GEOSS IP3.
Architecture (SOA) framework approach based on established The Interoperability Process Pilot Project (IP3) is part of the
standards from bodies such as the International Organization GEOSS task AR-07-01 (GEO, 2007–2009) aiming to prototype and
for Standardization (ISO) and Open Geospatial Consortium validate the implementation of the “Core” GEOSS infrastruc-
(OGC). ture and the processes for contributing and linking systems.
In this paper, we describe the results of linking the The IP3 was conceived as a way to exercise the process that has
infrastructures of Climate Change research and Biodiversity been defined for reaching interoperability arrangements
research together using an approach that is compatible with (Khalsa et al., submitted for publication). IP3 helps to identify
the GEOSS service-oriented framework. This interoperability the system components and discuss the standards, interface
is done for the purpose of enabling scientists to do large- protocols and interoperability agreements currently used by
scale ecological analysis. We describe a generic use scenario disciplinary systems, such as GBIF and IPCC.
and related modelling workbench that implement an envir- IP3 developed a series of projects involving different SBAs,
onment for studying the impacts of climate change on working out a suite of demonstrations. Four systems/disciplines
biodiversity. were initially identified as sources for the pilot project, covering
The most widely used approach for describing the steps for Earth's water cycle, climate, seismology, and biodiversity
large-scale biodiversity data analysis is Ecological Niche (Khalsa et al., submitted for publication). One of them, namely:
Modelling (ENM), pioneered by Peterson et al. (2001, 2002) “Species Response to Climate Change” was developed into
and refined subsequently by many others (e.g. Elith et al., functional demonstrations building on the presented frame-
2006). ENM is now employed for a range of global change and work: Ecological Niche Modelling was used to predict present-
macroecological applications (e.g. White and Kerr 2007; Kerr day niches for different species (e.g. butterflies in Canada and
et al., 2007; Kharouba et al., in press). GBIF has promoted this Alaska and pikas in the North-West America) and then to
approach and organised several international workshops on predict their shifts under different global and regional climate
the topic.1 The modelling tools for ENM have diversified and change scenarios. These demonstrations were presented at the
are being made available as an open framework and web GEO IV Ministerial Meeting in Cape Town, South Africa
services2 through the OpenModeller project3 (see Canhos et al., November 2007 (Nativi et al., 2007b).
The steps that are required for ENM have recently been
described in detail by Santana et al. (2008). They use the 2. Scenarios definition
In the following, we briefly delineate the steps, with accom-
1 panying data needs, in a simple scenario intended to provide
http://openmodeller.cria.org.br/wikis/omgui/Use_Case_Scenario_ example outcomes for a topical purpose, namely predicting
for_Open_Modeller_Web_Services_API. shifts in the spatial distribution of species' niches as a
http://openmodeller.sourceforge.net/. consequence of climate change. Each step in the process we
E CO L O G I CA L IN F O R MA TI CS 4 ( 2 0 09 ) 23–3 3 25
Fig. 1 – Activity diagram for the use scenario of biodiversity and climate change.
outline reflects the business processes for ENM (Santana et al., those gaps. The need for more and better data can be
2008; Fig. 1). They are: communicated to policy makers.
3. Determine what environmental characteristics most likely
1. Identify taxa for which sufficient data exist to conduct influence target species' niches. Examples of data that are
broad-scale analyses aimed at predicting the impacts of most widely necessary include high resolution land cover and
global change on species distributions in the future. It is climate data. Climate and land use change models can help
useful for such data to have a historical dimension also, forecast future environmental conditions, but models of
reaching back 30 years or more, so that responses to future conditions are unlikely to match either present-day,
recently observed climatic and land use changes can be spatial observations of climatic or weather, or of land use. The
documented. Predictions for future niche shifts are likely to latter can be observed remote using very high resolution
be more accurate when limited to species that have recently satellite data (see Kerr and Ostrovsky, 2003) or in situ. Clearly,
responded predictably to climate changes that have been models of the future are subject to relatively large uncertain-
directly observed (Kharouba et al., in press). Although there ties but can nevertheless provide plausible forecasts of change
are many biodiversity datasets that satisfy these stringent that can, and should, be considered for planning purposes.
criteria, they are patchily distributed (e.g. birds from the 4. Determine what climatological data are needed for Ecolo-
United Kingdom, butterflies from Canada, etc.). ENM can be gical Niche Modelling of the selected group of organisms for
applied to these datasets. Identifying other datasets is a past, current, or future scenarios.
challenge but one that GBIF can help solve. If all required 5. Determine which modelling algorithms will most accurately
datasets are stored in a repository online, then data mining and precisely predict shifts in distribution and abundance for
techniques can be used to discover available, comprehen- the selected group of organisms. Identify the reporting needs
sive datasets. If caching or other central or distributed in terms of data accuracy and error propagation.
repositories are inaccessible or do not exist, expert advice 6. Collect the selected species occurrence data (e.g. from
may still successfully identify needed datasets. GBIF), environmental and climate data (e.g. from IPCC) to
2. After assembling biodiversity datasets and mapping their the modelling workbench.
spatial and temporal distributions, gaps in information 7. Run the models and present outputs as series of maps and
become clearer. These gaps can then imply new data predicted abundance numbers. Model accuracy should be
sharing opportunities within and among countries to fill in tested so uncertainty in model outputs under the range of
26 E CO L O G I CA L IN F O RM A TI CS 4 ( 2 0 09 ) 23–3 3
desired scenarios can be included to provide a realistic Fig. 2 shows the overall system architecture. It consists of
depiction of policy options. This step will eliminate model six main logical components:
outputs that are clearly inaccurate and consequently
minimize the likelihood that failed models will inadver- 1. Biodiversity Data Provider: a component providing biodi-
tently influence policy. This approach resembles that of the versity data. It supports two logical operations: a) getting
IPCC is presenting different climate change scenarios, an index of available datasets; b) getting data of a specific
depending on variations in emission reduction efforts. dataset.
2. Climatological Data Provider: a component providing
The above scenario is but one example of a broad-scale climatological data. It supports two logical operations:
application for biodiversity data. Biodiversity is also affected a) collecting an index of available datasets;
by other factors such as tropical deforestation, for which other b) collecting specific data, after a suitable target dataset is
scenarios can be produced. identified.
Biodiversity is not only being impacted, but is also an 3. Catalog: a component performing queries on the available
essential component in providing ecosystem services for biodiversity and climatological datasets. It supports search
agriculture, health, the chemical industry, etc. However, operations. Such operation can be very complex, applying
these additional scenarios can be foreseen to build on the different kinds of filters based on spatial and/or temporal
same pool of primary biodiversity data as the described criteria. It performs search operation using indices from
climate change scenario. known data providers. This catalog implements distribu-
tion and mediation functionalities (i.e. distribution and
mediation for heterogeneous protocols, interaction style
3. The framework interface type, information model) through the same
service interfaces. It implements a broker service which
As explained above, the typical biodiversity application supports extended interfaces for asynchronous query
scenarios require modelling the impact of climate change on distribution and caching. Experience with initial imple-
species distribution. To build such models within a distributed mentations of the GEOSS architecture components has
computing environment, heterogeneous data resources (e.g. demonstrated the importance of a brokering service in
biodiversity, climatic and other environmental resources) and order to facilitate discovery across the GEOSS federation.
processing services (e.g. implementing ENM algorithms) must The mediation role applies to interoperability across
interoperate seamlessly. We have developed and thoroughly catalog services provided by the GEOSS Climate Change,
tested a conceptual framework to permit interoperability Biodiversity and other environmental communities.
testing for biodiversity applications. This framework also 4. Model Provider: a component that runs ENM techniques on
allows testing the GEOSS service architecture through the selected biodiversity and climatological datasets. It sup-
development of relevant scenarios that draw on data and ports a main operation to run the model by specifying the
information exchange from a series of systems intercon- algorithm, the parameter values, and the datasets to be
nected through SOA and by applying established standards. used.
Fig. 2 – The logical architecture of the framework.
E CO L O G I CA L IN F O R MA TI CS 4 ( 2 0 09 ) 23–3 3 27
5. Use Scenario Controller: a controller component that The catalog service is provided by the GI-Cat component that
implements workflow within the business process typical accesses the data servers' metadata/indexing interfaces to
of the biodiversity scenario described above. It is controlled perform queries (Nativi et al., 2007a; Bigagli et al., 2006). It
by the user through the GUI. implements and can be accessed through a standard OGC CS-W
6. Graphical User Interface (GUI): The component for user interface (OGC, 2007a,b).
interaction. It controls the workflow manager to perform The OpenModeller component implements the Model
the required operations for implementing the biodiversity Provider. It is able to run ENM according to different
basic scenario. algorithms and parameters. It exposes a proprietary SOAP
interface. Since it can work only on local files, it is necessary to
These components play the three typical roles of a SOA upload all required data locally. To avoid a double transfer
where Consumers discover Providers through a Registry. In our operation we added a Data Uploader component. This exposes
framework Data and Model providers are the Service Provi- a simple web interface that accepts a data description,
ders; the GUI-Controller pair acts as a Consumer and the including all the information required for accessing data.
Catalog plays the role of the Registry. Where necessary it also When a description is sent, the Data Uploader provides for the
acts as a Broker between Consumer and Providers. This fourth retrieval of the data and for local storage. Thus the logical
component is necessary for heterogeneous and federated interaction between the Controller and the Providers for data
systems. access (see Fig. 2) is implemented with an indirect interaction
The previous logical architecture has been implemented through the Data Uploader.
using a layered web architecture with a Service-Oriented The Controller component implements the business pro-
approach selecting or deploying specific data and model cess of the use scenarios. According to the instruction
providers, and introducing new components where required. provided by the user through the GUI, the Controller accesses
The functioning system includes multiple interacting the Catalog and Model Provider for searching, evaluating and
components and implements simple user interfaces (Fig. 3). choosing data, and for running models.
The GBIF Portal Server and the Climatological Data Server are
the data providers. Each of them has instances of interfaces
for accessing metadata and data. The GBIF Portal Server 4. Test scenario
implements a REST-based interface to retrieve taxonomic
information and species occurrences data through HTTP-GET A first demonstration dealt with the Canadian butterfly
operations directed on specific resources addressed by proper species (Amblyscirtes vialis) and its response to climate change.
URLs. The Climatological Data Provider implements an OGC This demonstration was presented at the GEOSS IV Ministerial
WCS interface (OGC, 2005) providing functionalities for Summit as part of the achievements of the GEOSS IP3 for the
retrieving index and metadata (i.e. getCapabilities and descri- Biodiversity and Climate Change SBAs (Species Response to
beCoverage) and data (i.e. getCoverage). Climate Change use scenarios) (Nativi et al., 2007b).
Fig. 3 – The framework main components.
28 E CO L O G I CA L IN F O RM A TI CS 4 ( 2 0 09 ) 23–3 3
Fig. 4 – The framework deployment architecture.
The deployment architecture realized for the demonstra- In the following paragraphs the main components are
tion is formalized by the schema depicted in Fig. 4. The GBIF described in more detail highlighting the technological con-
Portal Node is the instance of the GBIF Data Portal Server, while straints and choices.
a NCAR climatological server node hosts the Climatological
Data Server. A Catalog Server Node located at the CNR-IMAA 4.1. Biodiversity Data Provider
runs an instance of GI-Cat configured for returning CS-W
responses according to the ISO profile (OGC, 2007b). Another Biodiversity occurrences are discovered and accessed through
Node located at CNR-IMAA hosts the OpenModeller server web services published by the GBIF Data Portal5 and using
instance and the Data Uploader components — they must widely deployed biodiversity standards.6
reside on the same Node. The GBIF Data Portal provides unified access to over
The other interacting Node is the User Device which is 151 million primary species-occurrence records (both speci-
typically a device capable of running a Web Browser and a Java mens and observations) from some 266 data providers around
Virtual Machine, such as a desktop or laptop computer. In the the world, and covering a diverse range of taxa and ecosys-
browser, it runs the Use Scenario application allowing the data tems (Hobern and Saarenmaa, 2005). A high proportion of
uploading, the model description and running, and the data these records are geo-referenced, and ongoing efforts in the
visualization output. The search operations are performed data providing communities stress the necessity and value of
using a Java-based client of GI-cat (called GI-go GeoBrowser4) providing an accurate geo-location for records. The GBIF
for performances issues. virtual database represents a unique resource for Earth
Observation studies which require ground-truthing data,
E CO L O G I CA L IN F O R MA TI CS 4 ( 2 0 09 ) 23–3 3 29
Fig. 5 – Results of the model demonstrated at the GEO Ministerial Meeting in Cape Town, South Africa November 2007. The
model and its projections are the result of successful interoperation of all components of the system. A) The Amblyscirtes vialis
distribution projected for the year 2000; B) The Amblyscirtes vialis distribution projected for the year 2050 under the IPCC climate
change scenario. Light marks correspond to 100% of probability; gray marks to 50% of probability (photo by Erik Nielsen).
whether historical (to study change over time) or contempor- 3. Google Earth mapping service providing 1-degree cell
ary. In addition to the web based interface which provides the density data or placement marks.
user with three main routes into the data served by the GBIF 4. Prototype OGC compliant Web Map Service.
network – a user can explore by species, by country or by
dataset with options to download the data – GBIF also exposes GBIF works closely with Biodiversity Information Stan-
the data through several web services. These are described in dards (BIS) /TDWG,7 an international organisation that de-
the following section. velops standards and protocols for sharing biodiversity data.
The main components of the network contributed by GBIF Foremost amongst these, and deployed widely in the GBIF
are: network are the following:
1. Data providing nodes — currently some 266 distributed 1. Darwin Core8: a standard designed to facilitate the
around the world and growing. exchange of information about the geographic occurrence
2. A central registry of the data providing nodes — imple- of species and the existence of specimens in collections. It
mented using UDDI. includes an extension mechanism to allow inclusion of
3. A central indexing and caching system of the data provided other information. Its geospatial extension is particularly
by the nodes. relevant for GEOSS applications.
4. A data portal front end providing unified access to all nodes 2. ABCD Schema9: (Access to Biological Collection Data), more
on the network. comprehensive than Darwin Core, this is also designed to
5. Web services for programmatic access to data on the promote accessibility to biological collection data.
network. 3. DiGIR10: Distributed Generic Information Retrieval, based
on HTTP, XML and UDDI, is a protocol designed for unified
The GBIF data portal provides a number of web services: access to distributed databases.
4. TAPIR11: (TDWG Access Protocol for Information Retrieval)
1. A registry of data providing nodes implemented using is a newer HTTP/XML based protocol standard developed
SOAP to UDDI. by BIS/TDWG for accessing structured data stored in
2. Several related REST style web services for data resources distributed databases. It combines and extends the fea-
within the GBIF network, including: tures of BioCASe (a protocol based on DiGIR and developed
1. Taxon data web service: providing access to records of for the EU funded project BioCASE for use with ABCD
taxon concepts. encoded data) and DiGIR to provide a more generic
2. Occurrence record data web service: providing access to protocol.
records of the occurrence of organisms.
3. Occurrence density data web service: providing access to 8
records showing the density of occurrence records by 9
one-degree cell. 10
4. Provider web service: providing access to records 11
describing the data providers. Specification_2008-09-18.html.
30 E CO L O G I CA L IN F O RM A TI CS 4 ( 2 0 09 ) 23–3 3
Fig. 6 – Client application: user-interface.
4.2. Climatological Data Provider oil and gas) availability, rapid pace and direction of techno-
logical change favoring balanced development.
Climatological data were obtained from the NCAR GIS portal12 A1B Scenario Run set is represented by the five ensemble
which provides web access to free global datasets of climate members. Climate models are an imperfect representation of
change scenarios. These data (spanning 50 years from 2000 to the earth's climate system and climate modellers employ a
2050) have been generated for the 4th Assessment Report of technique called ensembling to capture the range of possible
the Intergovernmental Panel on Climate Change (IPCC) by the climate states. A climate model run ensemble consists of two
Community Climate System Model (CCSM) (IPCC, 2007). This or more climate model runs made with the exact same
service can be discovered using the GEOSS Clearinghouse climate model, using the exact same boundary forcings,
(include URL?). where the only difference between the runs is the initial
The portal provides several climate change scenarios, as conditions.
provided by IPCC: a scenario is a description of a possible outlook The datasets are processed to generate grid coverages at 1°
for the future state of the world, not a forecast of the future. The resolution in the ESRI ARCGrid format and served through the
constant 20th century forcing shows the least increase in future standard OGC WCS (Web Coverage Service) interface version
surface temperature, the B1 and A1B scenarios displays moderate 1.0 (OGC, 2005). Fig. 5 depicts the results obtained for a use case
increases and the A2 scenario results in the largest response. dealing with the Canadian common roadside skipper butterfly
The interoperability experiments mainly considered the (A. vialis). This use case was demonstrated at the GEO
A1B scenario. The A1 storyline and scenario family describes a Ministerial Meeting in Cape Town, South Africa November
future world of very rapid and successful economic develop- 2007 (Nativi et al., 2007b).
ment, low population growth, and the rapid introduction of
new and more efficient technologies. Major underlying 4.3. Catalog service
themes are convergence among regions, capacity building
and increased cultural and social interactions, with a sub- GI-cat (Bigagli et al., 2004) is a distributed catalog providing a
stantial reduction in regional differences in per capita income. unique and consistent interface that enables the interrogation
The A1 scenario family develops into four groups that describe of biodiversity and climatological data resources. GI-cat
alternative directions of technological change in the energy exposes an OGC CS-W/ISO interface (OGC, 2007b) and is able
system. Main characteristics of A1B scenario include: low to federate heterogeneous catalogs and access servers that
population growth, very high GDP growth, very high energy implement international geospatial standards (e.g. OGC OWS).
use, low–medium land use changes, medium resource (mainly In addition, GI-cat implements a mediation server, making it
possible to federate components that apply non-standard
http://www.gisclimatechange.org. services (e.g. THREDDS/OPenDAP servers) and GEOSS Special
E CO L O G I CA L IN F O R MA TI CS 4 ( 2 0 09 ) 23–3 3 31
Arrangements for interoperability (e.g. GBIF). While waiting - Model Output access: OpenModeller saves the model outputs
for the GEOSS Clearinghouse to provide an openly documen- in a local directory. To make them accessible we simply
ted interface, an interoperability arrangement was introduced expose the directory through a Web Server.
for the GBIF portal services, consisting of the introduction of a
formal mapping for the GBIF data model to the ISO 19115 core Environmental and biodiversity data searching on a catalog
metadata profile, and the GI-cat to GBIF service protocols service was implemented through the transparent interoper-
adaptation. ability with GI-cat.
4.4. Model service 4.5. The client application
OpenModeller,13 an open source Ecological Niche Modelling To implement the use scenario business logic and the user-
(ENM) framework, was used as the component for processing system interface we developed a client application running in a
collected data and generating future projections. It is currently Web browser environment using AJAX15 technologies. With this
being developed by the Centro de Referência em Informação tool, the user is guided through the process of: 1) discovering
Ambiental (CRIA), Escola Politécnica da USP (Poli), and the data (by submitting queries to GI-cat) and accessing selected
Instituto Nacional de Pesquisas Espaciais (INPE) as an open- data through the GBIF and WCS/NCAR data servers; 2) creating
source initiative. It is developed as a stand-alone application the model; 3) running ENM projections; 4) showing results.
(OpenModeller Desktop) but the modelling kernel is accessible The user interface reflects the typical use scenario work-
also through specific modules implementing external inter- flow (see Fig. 6). A different tab is dedicated to each of the four
faces like SOAP and SWIG (Simplified Wrapper and Interface main operations: Data Search and Access, Model Creation,
Generator).14 In our demonstration we use the SOAP server Model Projection and Output View. A fifth tab is used for
module implemented as a CGI component of an Apache Web debugging. Inside each tab the respective sub-operations are
Server. available through “accordion” menus whose content is
The proprietary OpenModeller SOAP interface implements dynamically updated. The user interface is implemented in
are: graphical effects and GUI widgets.
The application implementing the required business logic
2. getAlgorithms for viewing the available modelling algorithms; has been developed to interact with the OpenModeller Server.
3. createModel for creating a model based on selected environ- The client application provides functions that implement: the
mental layers and the provided species occurrences data; access to the required services, the building of request
4. projectModel for projecting a pre-generated model according to messages, the presentation of response messages, and the
selected environmental layers (e.g. climate model outputs). interaction with the user.
The interfaces to the most time demanding operations
(createModel and projectModel) are implemented in an asyn- 5. Conclusions
chronous way. Each operation call returns a ticket which can
be used in a getProgress operation. In this paper, we have described how linking distributed
At the time of the demonstration implementation we components needed for research on biodiversity conse-
needed to resolve some interoperability issues for integrating quences of global climate change could be achieved. An
OpenModeller SOAP Server in our framework: informatics framework was presented and discussed. This
framework was successfully demonstrated at the GEO IV
- Environmental data access: OpenModeller was not able to Ministerial Meeting in Cape Town, South Africa November
access remotely located environmental data. Thus we 2007, as part of the GEOSS IP3 task.
added the Data Uploader to retrieve the required data and The framework described in this paper is the first to make
to store it in a proper local directory. ENM available to any user with a web browser and through
- Occurrence data access: OpenModeller required providing web services. It is an example of an electronic scratch-book for
occurrence data in the createModel request message. We data analysis, automating the steps of the workflow. Such
would like to have the same approach both for environ- capabilities will be needed from the GEOSS Portal in future.
mental data and biodiversity data. We solved this issue by The framework present valuable innovations such as: an
uploading occurrence data in a Web folder using the Data OpenModeller service online with an AJAX client, the Open-
Uploader. Then the Controller could access the required Modeller environmental and biodiversity data searching
data and properly build the request message. integrated in a transparent way through the interoperability
- Occurrence data format: OpenModeller required a specific with a standard catalog service (i.e. the CS-W implemented by
format for occurrence data. For performances reasons the GI-cat), and the mapping of GBIF standard metadata to the ISO
format translation is worked out by the Data Uploader 19115 core profile (the metadata model applied by GI-cat).
during the upload.
32 E CO L O G I CA L IN F O RM A TI CS 4 ( 2 0 09 ) 23–3 3
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Another important lesson learned was the need to include
Kerr, J.T., Ostrovsky, M., 2003. From space to species: ecological
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The framework components described here do not yet Evolution 18, 299–305.
make use of the GEO Portals, as they were not available at the Khalsa, S.J., Nativi, S., Shibasaki, R., Ahern, T., Rainer, J.M., 2007a.
time when this work was done (the 1st half of 2007). This The GEOSS Interoperability Process Pilot Project, EGU
interoperability topic will be developed in the next future. In proceedings, Vienna (Austria), 15–20 April 2007.
fact, the IP3 framework will be extended and its multi- Khalsa, S.J., Nativi, S., Shibasaki, R., Ahern, T., Thomas, D., 2007b.
The GEOSS Interoperability Process Pilot Project, IGARSS '07,
disciplinary capabilities will be strengthened, demonstrating
Barcelona (Spain), July 2007.
the impact of local Climate Change on Biodiversity (2008– Khalsa, S.J., Nativi, S., Geller, G., submitted for publication, The
2009). GEOSS Interoperability Process Pilot Project (IP3), Submitted to
In our opinion, this pilot framework and its successful IEEE TGARS Special Issue on Data Archiving and Distribution.
implementation demonstrate the importance of GEOSS for Kharouba, H.M., Algar, A., and Kerr, J.T., in press. Historically
efficient macroecological research. calibrated predictions of butterfly species' range shift using
global change as a pseudo-experiment. Ecology.
Nativi, S., Bigagli, L., Mazzetti, P., Mattia, U., Boldrini, E., 2007a.
Discovery, query and access services for Imagery Gridded and
Acknowledgment Coverage Data: a clearinghouse solution. IGARSS '07, Barcelona
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We thank Siri Jodha Khalsa, leader of the IP3 initiative, for his Nativi, S., Mazzetti, P., Saarenmaa, H., Kerr, J., Kharouba, H.,
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