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INFORMATION PROCESSING IN AGRICULTURE 2 (2015) 51–63

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Management and control applications in
Agriculture domain via a Future Internet Businessto-Business platform
Sokratis Barmpounakis a,*, Alexandros Kaloxylos b, Aggelos Groumas a,
Lampros Katsikas a, Vasileios Sarris a, Konstantina Dimtsa a, Fabiana Fournier d,
Eleni Antoniou c, Nancy Alonistioti a, Sjaak Wolfert e
a

Department of Informatics and Telecommunications, University of Athens, Greece
Department of Informatics and Telecommunications, University of Peloponnese, Greece
c
OPEKEPE, Greek Payment Authority of Common Agricultural Policy (C.A.P.) Aid Schemes, Greece
d
IBM-Research Haifa, Israel
e
Logistics, Decision and Information Sciences Group, Wageningen University, Netherlands
b

A R T I C L E I N F O

A B S T R A C T

Article history:

The Agriculture business domain, as a vital part of the overall supply chain, is expected to

Received 9 July 2014

highly evolve in the upcoming years via the developments, which are taking place on the

Received in revised form

side of the Future Internet. This paper presents a novel Business-to-Business collaboration

28 April 2015

platform from the agri-food sector perspective, which aims to facilitate the collaboration of

Accepted 30 April 2015

numerous stakeholders belonging to associated business domains, in an effective and flex-

Available online 14 May 2015

ible manner. The contemporary B2B collaboration schemes already place the requirements
for swift deployment of cloud applications, capable of both integrating diverse legacy sys-

Keywords:

tems, as well as developing in a rapid way new services and systems, which will be able to

Future Internet

instantly communicate and provide complete, ‘‘farm-to-fork’’ solutions for farmers, agri-

FI-WARE

food and logistics service providers, ICT companies, end-product producers, etc. To this

Generic Enablers

end, this conceptual paper describes how these requirements are addressed via the FIspace

B2B platform

B2B platform, focusing on the Greenhouse Management & Control scenarios.

Agriculture 

2015 China Agricultural University. Production and hosting by Elsevier B.V. All rights
reserved.

Internet of Things

1.

Introduction

ICT and agriculture originate from disparate human needs,
nevertheless, the first domain proves to be of upmost

significance to the second in order to facilitate modern complex business processes related to agriculture. ICT application
in agriculture has been an emerging field for some years,
attempting to enhance the agricultural processes through
sophisticated information and communication developments. Aspects of the agriculture industry such as crop cultivation management and control, quality management,
transport of food products and food preservation may all be
enhanced by taking into account their domain-specific
requirements and translating them into the respective functional design, development and applications by ICT experts.

* Corresponding author at: Department of Informatics and
Telecommunications, National & Kapodistrian University of
Athens, Panepistiomopolis, Ilissia, Athens 15784, Greece. Tel.:
+30 2107275176.
E-mail address: sokbar@di.uoa.gr (S. Barmpounakis).
Peer review under the responsibility of China Agricultural
University.
http://dx.doi.org/10.1016/j.inpa.2015.04.002
2214-3173  2015 China Agricultural University. Production and hosting by Elsevier B.V. All rights reserved.

however. such as an expert system. while at the other end there is a database. farmers. An app store usually offers a variety of choices among apps. Analyses of potential developments in the precision agriculture domain have taken place taking into account spatial and temporal variations. precision agriculture. farm business apps.) and/or domain business stakeholders the capability to search for and use specific services and applications according to own needs and requirements. The aim of FInest was to define realistic business scenarios illustrating how transport business operations could be conducted and facilitated through the help of a FI-based collaboration platform. involving more and more business actors and stakeholders. a considerable amount of efforts is focusing on wireless sensor networks solutions for monitoring the condition of the crops during production. knowledge inference and finally knowledge transfer back to the farm or greenhouse and execution of the generated actions. Although prior efforts do attempt to address some of the high challenges of the business processes either in the domain of the agriculture or the logistics exclusively. as well as multiple and often complex interactions between them establish completely new needs – previously unseen. adjustable approaches as well as future directions for such developments have been described ([1. The increasing complexity through the agri-food supply chain processes. is a unified underlying infrastructure. although there is a single platform to support the several apps (Android or iOS respectively). However. based on the FI 2 ( 2 0 1 5 ) 5 1 –6 3 technologies as well but focusing on the domains of transport and logistics is FInest ([15]). the apps are developed in a completely independent and separated way from one another.e. The main operations. from a centralized repository of services/apps. an advanced architecture based on the Future Internet developments is presented. in which any stakeholder is able to take advantage of a specific business collaboration model. what is actually missing is a holistic. most of the existing schemes limit their functionality to a very narrow aspect of the overall business process. end-to-end solution. lacking this way in homogeneity. enterprises. In the agriculture domain. In the afore-mentioned work. as well as for the transport of products condition monitoring ([3–5]). a typical solution comprises a wireless sensor network residing inside the farm or greenhouse. as well as a processing component. for product autoidentification. eplanning. real time. AgWeb app store ([18]) offers a considerable number of agrifood chain-related apps specializing in different fields such as agronomy apps. etc. Current trend is gradually heading toward the Internet capabilities in order to address several of the existing limitations. which aims to . previously unexploited. as well as realizing an efficient communication scheme between the involved stakeholders of the business chain still remain some of the most significant obstacles. or results and offer a complete end-to-end solution. data processing. With regard to existing solutions. along with a framework that allows the interconnection among services developed by different service providers. In principle. In [9] the authors describe a novel architecture. isolating the business actors and thus. Modern business processes related to agriculture and greenhouse management and control involve multiple stakeholders. as well as corresponding business actors and events. failing to provide a holistic solution. open and flexible. Future systems cannot rely on existing infrastructure and require more sophisticated and smart frameworks in order to improve the effectiveness of business processes. the proposed schemes attempt to partially enhance a narrow aspect of the overall supply chain picture. Different use case scenarios were used to demonstrate the capabilities of the FInest architecture in real-life: handling late booking cancellations. In [11]. services) to accomplish it. In all cases presented earlier. which introduce the notion of sophisticated processes using advanced information and communication tools and systems into agriculture processes. lacking any business collaboration model behind them to link their requirements. Examples of existing site-specific precise farming approaches. weather. Smart farming.52 Information Processing in Agriculture Several efforts over the last years have attempted to integrate end-to-end ICT solutions into the agriculture business processes. What is actually missing. However. which is processing the available data and generates actions – often in an automated manner – for the farmer. all are terms. etc. Even in the case of Google Play or Apple Store. Another FI-PPP Phase 1 project related with the Smart Agri-Food project presented earlier. greenhouse managers. The complexity of those business processes is nowadays the most crucial challenge that needs to be coped with.. such as the aforementioned ones. which are in general dealt within the context of Precision Agriculture and Greenhouse Management are data monitoring. An operational example is used to demonstrate the interworking of the functional modules of the architecture. Several sophisticated Farm Management Information Systems’ solutions and architectures have been already described in the literature ([6–8]). resource coordination. Another significant perspective.. as well as external back-end systems. namely an ‘‘app store’’.e. machinery. In [13] the implementation of an innovative. as well as automated shipment tracking. not being able to maximize the potential outcomes. usability and user friendliness. in a similar manner the famous Apple Store ([16]) or Google Play ([17]) offer. actual execution. using dynamic. handling vast number of devices (i. which takes advantage of the Future Internet Public–Private Partnership (FI-PPP) ([10]) capabilities in order to facilitate the interoperability among services and stakeholders. In this paper. in parallel to the actual developments and technology choices presented earlier. real-time event handling. it is aimed to demonstrate how the adoption of these general-purpose software modules provided by FI-PPP and their extension into farming specific ones may provide a cloud operating system that can integrate different services and applications. which is capable of bridging the diverse gaps between different – but directly associated – domains. Farm Management Information Systems (FMIS). cloud-based Farm Management System is provided. is ultimately being able to offer to the end-users (i. which supports the execution of the offered apps. a detailed analysis of the FI-PPP software modules exploitation is provided according to the deployments in the context of the Smart Agri-Food (SAF) FI-PPP Phase 1 project ([12]). Internet of Things domain).2]). as well as select and deploy the desired means (apps.

FI-LAB is a use case example of FI-WARE instance. yet efficient way. Security GEs (e. integrated and extensible ‘‘Platform as a Service’’ (PaaS) for stakeholders and business players belonging to diverse business domains. eHealth. The main idea of FIspace is that any business collaboration is ‘‘built’’ around ‘‘business entities (BEs)’’. etc. via the FI-LAB environment Generic Enablers implementations are available and globally accessible as services. fruit and vegetables quality assurance. Device/Network Interfaces GEs (e. Often. the FI-PPP plays an essential role toward creating the required communication and technological infrastructure for supporting a complex and holistic stakeholder interaction in the context of business collaboration processes.. providing cloud-hosting capabilities for third parties in order to be able to experiment with Future Internet applications. It may be described as a business-to-business software tool. in order to facilitate 2 ( 2 0 1 5 ) 5 1 –6 3 53 the creation of novel applications built on top of the existing infrastructure features... IoT Broker GE.. Cloud Hosting GEs (e. 3. the current work emphasizes on the greenhouse management and control use case trial of the FIspace project. etc. FIspace Platform high-level architecture FIspace is a Business Collaboration Network in agri-food. Identity Management GE. network virtualization. smart cities. Cloud Edge. semantic tools or big data handling.g. communicate and coordinate activities. . accessible. which engages both developers and entrepreneurs and provides the required tools to support it.g. greenhouse management and control. Future Internet refers mainly to an initiative. transport and logistics aiming to provide an innovative business space. Object Storage GE. smart applications deployed inside FIspace. etc. based on the Future Internet technologies. and how all the involved agri-domain business actors may benefit from such a B2B platform via novel. energy etc. focusing on multiple business domains: crop protection information sharing. In the final section. demonstrating how the FIspace platform is exploited in order to facilitate B2B collaboration scenarios related to the agricultural. which collaborate in order to fulfill a complete business case: FIspace ([19]).): Enables the implementation of modern FI applications. Data/Context GEs (e. The vision of FI-PPP is based on FIWARE and FI-LAB ([14]).. Semantic Annotation. Furthermore. apps’ repositories. Gateway Data Handling. compliant with cloud hosting infrastructure.): Establishes an open and standardized network infrastructure. Job Scheduler. and allowing seamless collaboration between multiple business actors. which will be described in the following sections. 1.. which performs research activities to create novel architectures for the Internet. exchange information. searchable. Complex Event Processing. Each one of the GEs is licensed with no costs within the FI-PPP program. In Section 2. These GEs are the building blocks of the core platform and are categorized according to their principal scope to several categories such as: • • • • • • Applications/Services Ecosystems GEs (e.Information Processing in Agriculture provide an end-to-end. we summarize the conclusions. Big Data Analysis. In Section 4. General-purpose software modules – known as ‘‘Generic Enablers’’ (GEs) – support the infrastructure of FIWARE. Application Mash-up. fish distribution and (re-)planning. Section 3 provides an overview of the FIspace platform. we focus on the greenhouse management and control trial. – an ecosystem. manufacturing. safety.g. while diverse domain-specific apps and services are deployed and configured in accordance with these business entities. which are derived and insights on the next steps are provided. incremental steps to complete architecture and principles’ redesigns. ranging from small. the platform supports multiple domains in order to support the complete supply chain ‘‘from farm to fork’’. etc.1.): Helps the ‘‘things’’ connection to the real world by becoming available.g. Research activities that could be seen as components of a future Internet include network management. flowers and plants supply chain monitoring and meat information provenance. while diverse terms and conditions are applied among the various GEs for external use.g. FI-PPP mainly targets toward the digitization of the European economy sectors including agriculture. The rest of the paper is organized as follows. Various use case scenarios are applied in the context of FIspace.): Supports the creation of an innovative ecosystem of applications and services. transport. logistics. tourism. comparable to Facebook or LinkedIn.): Enables the implementation of the required security mechanisms for each app to be developed.g. 2. in order to evaluate specific key performance indicators. and treating any kind of information as objects. Access Control. Internet of Things GEs (e. start and accomplish collaborations. The Future Internet Public–Private Partnership (FI-PPP) and FI-WARE Generic Enablers In the attempts discussed earlier. etc. Business can interact with each other. it aims to create a core platform consisting of various ‘‘sub-platforms’’ and sub-modules. a reference architecture for Business-to-Business (B2B) collaboration in supply chain networks is described including a methodology (i.e. and usable for FI uses and services. Repository GE etc. a description of the Future Internet PPP developments is presented. The high-level architecture of FIspace platform is demonstrated in Fig. independent of their storage or location. Business Calculator. the FIspace operational model) that can be seen as a kind of handbook of how this reference architecture could be implemented. Through cloud solutions. DB Anonymizer. the user can select among more than one implementation of a Generic Enabler is available from different providers. The FIspace platform and the FIspace operational model 3. Although. Network Information and Control GE.): Enables the exchange and publication of massive data in a fast.

integrated user authentication mechanism etc. which facilitates the interoperability among different communication protocols and data models. 1 – FIspace high-level platform architecture. access to FIspace App Store. FI-LAB. and this number may also increase as the developments progresses: • Part of the FIspace Front-End is based on the Wirecloud GE ([20]). .54 Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig. As it is illustrated in the architecture above. several GEs are already used. taking care of the secure access to the FIspace networks. • • • • • • • The System and Data Integration module: the ‘‘gateway’’ of any external or legacy systems (e. It is comprised of o the Business Collaboration Module (BCM): this module serves the principal real-time B2B collaboration concept. the platform is comprised of six fundamental modules: • The Graphical User Interface (Front-End): the main access point for the end-users. The B2B collaboration core The aim of this module is to create. 2) illustrates the relationship between FI-WARE developments. Identity Management and Revenue Sharing GEs ([22–25]). and monitor collaborative processes in the FIspace platform. The Event Processing Module (EPM) core module implements the Complex Event Processing (CEP) GE ([26]). execute. The Security. o the Event Processing Module (EPM): A complex event processing engine that monitors and tracks after events of interest related to the business collaboration. The B2B Collaboration Core module: it is one of the core components of the platform. 2 – FI-WARE FI-LAB’ GEs and FIspace Specific Enabler. its purpose is to create. Privacy & Trust Module is based on the Identity Management GE mentioned earlier. The figure that follows (Fig. Privacy and Trust (SPT) module: it is concerned with all the essential features in order to provide all the required security mechanisms in order to ensure a reliable exchange of business information and transactions. • • The FIspace Store is built upon the WStore GE ([21]). being one of the Specific Enablers example. the FIspace platform is acting as a ‘‘specific enabler’’ of FI-WARE. which provides all the essential features for the business collaboration. on which the business collaborations rely on. The BCM component is responsible to orchestrate the different processes from different stakeholders and assure the According to the previous section. Marketplace. consumption and purchase both for consumers as well as the FIspace app developers. Registry. which respectively connects to Repository. etc. The FIspace Cloud Service Bus (CSB): another essential core module. The Security. handle and manage the FIspace collaboration processes [28]. manage. notifications mechanism. Generic Enablers and FIspace platform. Although the platform development is still ongoing. as several of the core components of the platform is relying up to an extent to a generic enabler. an ‘‘application mash-up’’ platform. The System and Data Integration Module is using the Mediator GE ([27]). two complementary components are implemented: The Business Collaboration Module (BCM) and the Event Processing Module (EPM). which facilitates the connecting between all the main components of the platform. Fig. To this end. The FIspace Store: the access point from which the FIspace apps are available for provisioning. 3. Internet of Things) in order to communicate with the FIspace platform and participate in a business collaboration. reputation and recommendation mechanisms.2.g.

Each Stage can own one or more Guards. which are tightly linked. In general. as business entities. The BCM is based on the entity-centric approach [28]. FIspace operational model The business collaborations within FIspace platform heavily rely on the respective business entities. the business user needs to instantiate (configure) them according to own needs. This is accomplished through the online forecasting of future events. The EPM can support two types of situation detection capabilities: reactive and proactive. and the application of online decision-making processes ([30–33]).e. Proactive rules. Stage. acting internally. Stage can have one or more Milestones. In general. Milestone-model ([28]). or capitalize on predicted opportunities – in advance.e. which were described in the previous sub-section. relate to situations that are likely to happen in the (near) future.e. situations that require appropriate actions. . external systems. They represent the achievement of distinct business objectives and are visually represented as circles. Guards are defined as conditions of the form ‘‘on <event> if <condition>’’ (visually represented as diamonds). Stages represent clusters of activity and are visualized as rectangles with rounded corners.3. that is. The main constructs of the GSM model are illustrated in Fig. This approach relies on the notion of entities (aka. The EPM processes these events and by applying pattern matching derives situations of interest ([29]).Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 55 Fig. a sensor reading outside a permitted range. which control its activation. on the other hand. The Event Processing Module (EPM) component monitors events and detects situations of interest. the tasks flow as a result of triggering events to specific conditions. In order for them to be usable. 3. we refer to proactive event-driven computing as the ability to mitigate or eliminate undesired states. we can distinct between situations that result from the actual execution of the process or collaboration and situations that result from external events (i. An entity type includes both a data schema and a lifecycle schema. they are noted in the form ‘‘on <event> if <condition>’’. as a result the end-users are not supposed to interact with them directly. In FIspace we apply the GSM – Guard. However. i. The apps are built within a generic context and are not supposed to be linked to specific external systems. or sensors. 3 – GSM model for describing the lifecycle of a business entity. a delay in a delivery etc. the analysis of events coming from many sources. Examples of situations of interest can be: missing documentation at a certain point in time. The events sources (aka event producers) can be the actual execution of the collaboration (i. Reactive rules analyze past events and derive situations by applying pattern matching over a single or a set of events over time. these business entities reside within the platform. events coming from external systems or sensors). A business entity is a key concept that evolves as it moves through a business process. correct sequence of the tasks execution. GSM is a declarative model that enables hierarchy and parallelism of the tasks and reactive in nature. The lifecycle schema of an entity type specifies the different ways that an entity instance might evolve as it moves through the overall process. Like Guards. artifacts. 3. or dynamic artifacts). The data schema provides an end-to-end conceptual view of the key data for this entity type. In order to realize the collaboration among business actors and take advantage of the business entities. In the Greenhouse scenario in FIspace we defined Advice as our key business entity related to the Greenhouse Management & Control scenarios to demonstrate in a more specific way how a GSM model may define the greenhouse management workflows processed by the FIspace platform. the BCM). apps are developed and available to the FIspace users via the FIspace Store.

FIspace could support multiple apps linked to this particular collaboration: Firstly. a number of diverse business stakeholders are participating. i. i. there is the possibility for one FIspace app to be linked and consume events from more than one business entity. focusing on the transport and logistics domain ‘‘Smart distribution and consumption’’. mapping specific external systems for a respective specific instance of the business entity. 4 below illustrates the connection between the apps and the FIspace business entities. a third application could be deployed in order to receive from the expert system the advised actions and provide them in a proper way. Finally.: farmers. greenhouse managers. agronomists. several generic as well as domain-specific applications are developed according to the platform’s operational model. similar to this one. A business entity may be linked to multiple FIspace apps. Notably. Farm Management Information . focusing on the agricultural domain ‘‘Intelligent perishable goods logistics’’. in the context of which. assume there is a business collaboration between a greenhouse owner (or farmer). In addition. an app. These scenarios are summarized as follows: • • • • Requesting for greenhouse advice from an expert system Managing consumer complaints Facilitating new collaborations between stakeholders Recalling a product using traceability mechanisms For each one of the above scenarios. using probably notifications mechanism. 4 – The FIspace Operation Model between the business entities and the FIspace apps. increases the agricultural productivity and revenues as well overall facilitates the several processes. The scope of the experiment is the management and control enhancement of greenhouse operations. Respectively. in order to demonstrate numerous aspects of the domain that may be enhanced using the FIspace infrastructure. a weather service provider. and in particular on the greenhouse management and control use case trial. In the context of the Greenhouse Trial. The purpose of these implementations is to test whether the underlying infrastructure is able to deliver the required functionality. they are categorized along three ‘‘themes’’: • • • ‘‘Farming in the cloud’’. privacy and reliability for the business stakeholders of the agricultural domain (in the case of the Greenhouse trial scenarios) to rely on and expand their activities using the FIspace technologies. The above process describes the fundamental operational model of FIspace. also focusing on the transport and logistics domain This paper focuses on the ‘‘Farming in the cloud’’ theme.56 Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig. advisory services enterprises. end-product producers. The use case trials primarily originate from two business domains. For instance.. different scenarios take place. which provides actions to be taken inside the greenhouse to the farmer according to the environmental conditions (provided by sensors inside the greenhouse). as well as an expert (advisory) system.e. 4. which will consume events produced within this business collaboration. aiming at demonstrating how the Business-toBusiness collaboration among the domain stakeholders via the FIspace features.e. performance. a second app could illustrate the weather information provided by the weather service. security. which shows the conditions inside the greenhouse could be developed. The Greenhouse Management & Control scenarios Real-world business scenarios are established in order to evaluate the FIspace platform. Fig. A scenario. agricultural domain and transport and logistics. to the farmer. will be presented in detail in the next section.

which will be presented below. State Agencies etc. revenues Developers will be able to upload via the FIspace Store their apps. In the archimate model above.1. What is going to be tested. health hazards must be identified and relevant stakeholders must be notified in a timely manner. as well as a product traceability platform. Inside the FIspace platform an ‘‘Advice Request’’ app resides. and afterward they are forwarded to FIspace. which will be used by the various business collaborations Various business actors who will be involved in the different scenarios like Consulting Firms. will also gain profit from participating in such collaborative chains • 2 ( 2 0 1 5 ) 5 1 –6 3 57 Appropriate information that is related to farmers’ profiles could be exchanged automatically with states’ and information policies enabling to simplify daily routines. advisory systems. 5): the farmer/greenhouse manager and an advisory/expert system enterprise. For example. In case of events inside the greenhouse (i. The message sequence chart (MSC) that follows. a weather service. which is illustrated later in the paper. is whether and to which extent. as well as the technology/infrastructure layers (gray layer at the bottom). weather services.) and create new Service Level Agreements in a much more efficient as well as sophisticated way.Information Processing in Agriculture System (FMIS) owners. certain Business KPIs are improved. and the Advisory Service. via the use cases. although being a simple business case by involving only two stakeholders. which will potentially enable him to maximize his revenues End-Product producers will be able to discover potential partners that interest them in a much more efficient way. a direct link between a farmer and the state agency would eliminate bureaucracy. Such a business process. an agricultural state agency. The end-user receives the actions from the expert system via the respective FIspace app. Overall. the interconnected advisory services must inform via the FIspace Domain Specific Apps the farm managers of forthcoming alerts and actions to be taken. the business layer of the collaboration is illustrated (yellow color). The main blocks in the technology layer are FIspace. handle their tasks more efficiently retrieving information from multiple back-end systems. The farmers must be able to organize the task planning of their greenhouses in an automated and more sophisticated way. This specific business collaboration is handled by the advice business entity. the Greenhouse FMIS. 6). all of which will collaborate in order to produce the best possible feedback to the stakeholder. targets to illustrate a radical enhancement. 5 – Collaboration (business and technology layers) for Advice Request from expert system for actions to be taken inside the greenhouse. Greenhouse domain stakeholders must be able to discover new potentials for collaborations (with farmers. Requesting for greenhouse advice from an expert system Two main business actors are involved in the first scenario (Fig. sensor values detected out of predefined boundaries) a request for actions is sent to the advisory system. . in principle with regard to the time required accomplishing it. retrieve updated information about products and be notified for any emergency situations concerning their products Legacy/Back-end systems’ owners will deploy their systems in multiple collaboration chains. The idea is that the sensors’ values of the Greenhouse are forwarded to the Greenhouse Farm Management System (FMIS). it is expected that: • • • • • Farm managers/Farmers will be able to manage their greenhouses in a more efficient way. end-product producers etc. as well as the quality and the Fig. which provides advisory services to the greenhouse based on the conditions inside the greenhouse. 4. describes the particular process (Fig.e. where they are contextualized. which corresponds to respective business collaboration and provides the information via the UI to the farmer. maximizing their products’ usage and thus.

2. Similarly. on the one hand the farmer. the advisory system owner as well. a logistics service could connect to the existing business entity in order to get updates with regard to the conditions inside the greenhouse. The Message Sequence Chart. The Managing Complaints collaboration is managed inside the platform by the complaint business entity. but on the other. and – based on the respective business entity configured inside the platform – forwards the appropriate requests accordingly to the required systems. so that ultimately the information forwarded back to the farmer is enhanced. to higher profits for all involved stakeholders. which follows (Fig. Indicatively. 6 – MSC for the Greenhouse Advice Request scenario. the concept of the platform architecture and operational model provides the opportunity for further enhancing the outcome of the particular business collaboration by deploying more business players and external systems to participate in the same business entity. consequently. . 4. This will result. 7). further elaborates on the particular scenario and the interaction of the diverse systems and the FIspace platform: Fig. accuracy of the actual advice actions.58 Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig. a weather service could be linked to the platform – using the respective adapter – and provide information to the advisory service. 7 – Collaboration for Complaint Management from an end-product producer. a back-end system provider as well as a Consulting Firm. Notably. Instead of having to send separately the complaint report to each one of the aforementioned business actors. The end-product producer uses the Managing Complaints FIspace app to submit the complaint and receive a respective analysis on it from a traceability service (TS) provider. who based on the quality of the services will have the possibility to increase the collaborations with interested parties. an end-product producer receives a complaint from a consumer. 8). Managing consumer complaints In the Managing Complaints scenario (Fig. the specialized FIspace app receives the complaint. when trying to trace food quality issues created during the supply chain.

an automated match-making mechanism between available offers and demands is available. 12). Recalling a product using traceability mechanisms In this scenario (Fig. which are used for storing the service information in the RDF semantic web standard [34]. the process is initiated by a State Agency request . which may possibly satisfy their requirements. by the time an end-product producer enterprise begins to search for new farmers-suppliers for example until an SLA is established) may take very long time. Using the Marketplace Operations service within the FIspace platform. as well as forwards the query to external systems. a health threat is discovered by a State Agency for agricultural policies due to a hazardous pesticide. The implementation of the Marketplace Operations back-end is heavily relying on two GEs from FI-WARE: the Repository GE and the Marketplace GE. which have been integrated and connected to FIspace. the platform’s ‘‘gateway’’) to the respective external systems: the information regarding the raw product part of the request will be forwarded to the Farm Management Information System of the greenhouse. The traceability service (TS). 10 below: An example of an initial creation of a service offer by user A and a service demand by user B sometime later is illustrated. More specifically. which has been linked to the business entity. which need to be notified for the threat. The Business Collaboration core module receives the request from the Complaint Management app’s back-end and dispatches the request via the System and Data Integration (SDI) module (i.e. Similarly with the previous scenarios presented above.Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 59 Fig. as well as FMIS from several greenhouses are also connected to the business process. the MSC of the specific use case is demonstrated in Fig. 11) it is assumed that an emergency event breaks out and needs to be dealt with in a timely manner. in the particular scenario (Fig. which via the app’s respective front-end provides the required info to the user. 4. which the developed FIspace app will use to extract the list of all the involved parties.g. Often.3. specialized services etc. 4. agriculture – greenhouse products). The platform – via the Marketplace Operations – is querying the already created service offers or demands.. any business stakeholder is able to select among the domain of preference (e. via the SDI module the information is aggregated inside the Business Collaboration module and transferred back to the back-end of the Complaint Management app. 9). Facilitating new collaborations between stakeholders Discovering the ideal business players to collaborate with for accomplishing diverse business processes is not a simple task. In the message sequence chart that is presented below (Fig. while the processed product’s part to the traceability platform. in order to provide back information. The match-making mechanism within FIspace provides an instant notification to both users for informing them so that they possibly proceed to the creation of a new collaboration. which is submitted by user B.) and the whole process (i. The State Agency is using the FIspace Product Recall App and sends a request after submitting the relevant information to discover the users of the hazardous pesticide. Many e-marketplaces and/or databases can ultimately integrate with the Marketplace Operations service of the platform. The existing offer created by user A satisfies the demand. the farmers’ database of a State Agency of Agriculture is used. the location. Similarly. in order to notify the interested parties for existing services.e. multiple parameters need to be taken into account (location. availability.4. the period of the collaboration in which one is interested and directly make a request to FIspace. 8 – MSC for the Complaint Management scenario. In addition to the above. providing the highest-quality possible services to the interested business partner.

60 Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig.. 10 – MSC for the New Collaborations scenario.5. Greenhouse trial business process modeling via the notion of business entities In order to provide further insights to the operational model of the FIspace platform regarding the business entities (BEs) of the greenhouse trial. A tight collaboration between two core modules of the platform. the GSM model of the BEs for two of Fig. 9 – Facilitating the search for new collaborations using the FIspace platform. The following messages involve the information acquisition from the external parties (Traceability platform and Greenhouse FMIS) and the final feedback that is provided back to the State Agency: As it is illustrated in the above figure.e. Event Processing and Business Collaboration modules is in charge afterward of the overall coordination of the flow of the messages and the final notification to the user via FIspace’s front-end. . 4. the request is initially submitted via the SDI module into the FIspace platform. i. toward the FIspace platform.

Respectively. Fig. requested by the FIspace platform.Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig. 13 and 14). 11 – Collaboration for recalling a product from Agricultural State Agency. The first figure (Fig. 61 . in order to demonstrate the role of the business entity in the lifecycle of the collaboration process. 13). 12 – MSC for recalling a Product scenario. the second one (Fig. The BEs are: Advice BE (represented by the Advice GSM) and ComplaintAnalysis BE (represented by the Complaint Analysis GSM) respectively. 13 – Advice GSM. and generated by the expert system. which were presented in the technology layer of the respective scenario. the afore-presented scenarios (namely ‘‘Requesting for Greenhouse Advice from an Expert System’’ and ‘‘Managing Consumer Complaints’’) is illustrated below (Figs. Fig. 13) illustrates the advice business entity lifecycle (GSM model) for the greenhouse. These BEs are linked to the apps residing inside the platform. We highlight in Table 1 below the main steps of one of the two GSM models (Advice BE – Fig. 14) shows the BE lifecycle (GSM model) of the Managing Complaints use case.

Advisory Systems. The architecture. This harmonization is achieved via another crucial module of the B2B scheme. as well as the operational model of the platform that were also presented in detail.g. making FIspace one of the cornerstones of the forthcoming Business-to-Business technological solutions in the near future. A B2B collaboration core module is used for the orchestration of such business processes. are detected and as a result the EPM emits the OutOfBoundariesNotification event to the BCM Expert system responds back with required advices/ actions after receiving the values The expert system notifies the FIspace platform that the advice is given to the greenhouse FMIS A notification is created inside FIspace platform for the farmer. will reshape modern business collaborations with the help of the afore-presented notion of the business entities. Respective progress of the Advice BE GSM model • • • • • An OutOfBoundariesNotification. 14 – Complaint Analysis GSM. a critical perspective that needs to be highlighted is the facilitation of integrating existing legacy systems (e. FMISs. visible upon entering FIspace and opening the Advice app Of course. Discussion and conclusions In this conceptual paper we presented how FIspace. multiple data types and standards being used for the accomplishment of a single collaboration. From the agri-food domain’s perspective in particular.). 5.62 Information Processing in Agriculture 2 ( 2 0 1 5 ) 5 1 –6 3 Fig. At some point in time one or more sensor values that exceed pre-defined thresholds. . Scenario steps • • • • Greenhouse sensor values are being constantly monitored by the EPM. set the foundations to establish Future Internet-enabled software tools. via the greenhouse management and control trial’s developments that were provided. onEvent() is received and the process enters the HandlingAdvice stage. the System and Data Integration module of the platform. etc. as the complexity of future collaborations will require diverse parties participating. more complex collaborations can be accomplished by combining BEs along with their respective GSM models. This is realized by minimizing the required effort to harmonize the communication schemes between the platform and these systems. and more specifically the RequestingAdvice sub-stage SendRequestForGreenhouseAdvice action is activated AdviceGiven milestone is reached upon successful receiving the requested Advice The AdviceGiven. as well as huge number of events that need to be handled appropriately. an innovative B2B collaboration platform. Table 1 – Request for Advice from Expert System scenario. a completely novel way of linking diverse business stakeholders and external systems – previously completely disconnected – is presented.onAchieve() guard is passed and NotifyFarmer is activated FarmerNotified is reached – AdviceHandled is reached – HandlingAdvice stage ends Furthermore.

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