Designing CSCW System for Integrated, Web ... - Semantic Scholar

Designing CSCW System for Integrated, Web-Based, Cotton Cultivation Services

C. Pontikakos, G. Zakynthinos, T. Tsiligiridis* Informatics Laboratory Agricultural University of Athens, 75 Iera Odos, 118 55 Athens, Greece * Corresponding author: [email protected]

Abstract Computer Supported Collaborative Work (CSCW) systems have attracted the attention of many software implementers on the area of multimedia applications, however very few of them have been used in agriculture. The necessity for using the CSCW environment in agriculture arises from the utilization and the rapid development of modern strategies of plant cultivation. In this paper we present the design of an agricultural CSCW system, which aims to provide integrated, web-based, services for cotton cultivation. Designing and developing such a system is a complex task that requires dealing with a great number of challenges. We focused on a number of important interrelated issues of user profiles, providing an overview and an insight on the way we address them. The proposed framework is intended to contribute to a unified view of requirements of a knowledge management support system by identifying core components and functionalities. Key words: CSCW, IPM, PA, ICM, web-services, user profile, personalization, cotton cultivation.

1. Introduction Cotton, a perennial plant that is cultivated annually on commercial basis, is an important product of Greece. Its production is high, whereas the quality as well as the economic benefit for the producers remains low. In addition, the conventional production practices have significant environmental impacts, mainly because of the overuse of pesticides and fertilizers. Traditionally, any associated decision on cotton cultivation is been related with the phenological stages of cotton. The main characteristics of the cotton production are as follows:  The calculation of the irrigation timing and quantity is mainly empirical.  The nutrients that must be applied are estimated in relation of the cotton growth stages, without considering meteorological aspects (rainfall, temperature etc), or soil properties.

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The control of the major pests of cotton depends largely on the use of synthetic broad-spectrum pesticides. The weed management is based on chemical applications. The irrigation is applied without any scientific calculation.

As it appears, the irrigation, the nutrient supply, as well as, the pest and weed management does not correspond to the real needs of cotton quality and the market trends. During the last years, new approaches have been developed on cotton production management, such as Precision Agriculture (PA), Integrated Pest Management (IPM) and Integrated Crop Management (ICM). PA is a precise crop production using computers, Global Positioning Systems (GPS), Geographic Information Systems (GIS) and remote sensing. Integrated Pest Management (IPM) is the rational application of a combination of biological, biotechnical, chemical, cultural, or plantbreeding measures, whereby the chemical pest control is limited to the minimum necessary to maintain the pest population at levels below those causing economically unacceptable damage or loss. PA and IPM can be integrated into the broader concept of Integrated Crop Management (ICM). This approach utilizes pest management decisions and touches all issues of cotton cultivation including planning, irrigation, nutrient supply, weed management, variety selection, crop rotation, harvesting and marketing. The cultivation approaches mentioned above ensure the quality of cotton production and offer the greatest financial results with the lowest environmental impacts. However, they require management of large volume of information, well-trained and knowledgeable people (producers, agricultural engineers and scientists) (Kitchen et al., 2002), collaboration between participants (producers, experts, companies and organizations) to develop management strategies for quality cotton production, effective profit, and finally, immediate, valid and scientific decisions concerning the crop management. One way to satisfy the aforementioned requirements is to use webbased technology, by means of the development of an agricultural CSCW system for cotton production, which combines the cotton cultivation needs, and the modern cultivation approaches, with participant’s collaboration and the market trends. CSCW systems integrate the way people work together using computer networking technologies and other complementary information technology tools. They have been used in a large number of multimedia applications in order to improve the collaboration between people who participate towards a common goal (Ehrlich K., 1999). Companies and organizations have been using these multimedia systems to increase the collaboration and productivity of employees. In addition, research institutes have developed CSCW environments for distance learning (Brusilovsky, 2001; Schubert and Koch, 2003). As a result, designing and developing a CSCW system is a complex task that requires the involvement of many different disciplines,

such as hardware, software, social, personal, privacy and security (Rogers, 1994; Procter et al, 1996; Thimbleby and Pullinger, 1996; Kamel, 1999; Kristoffersen and Ljungberg, 1999; Fink and Kobsa, 2000; Kramer, 2000; Paganelli and Paternò, 2002). So far, a wide variety of CSCW systems have been implemented (Schuckman et al., 1996; Schubert and Koch, 2002; Schubert et al., 2003). Many applications use WWW in order to provide platform-independent interfaces to network-based collaborative services, while others systems use WWW to provide a virtual shared space for group interaction. Gerrit van der Veer and Martijn van Welie (2000) developed a practical method for the design of Groupware, whereas Wang et al. (2000) suggested a graphical hypermedia-based process representation. Although there are many different views on designing and applying CSCW systems (Gerrit van der Veer and Martijn van Welie, 2000) in practice, they are considered as generalpurpose systems with wide applicability that can be adopted and tailored to specific domains. In this paper, we present the design of an agricultural CSCW system in order to provide integrated, web-based services for cotton cultivation. We focused on a number of important interrelated design issues of user profiles, namely, what information is gathered about a user (modeling the user profile), where do we get the user information from (acquiring the user profile), and how to use the user information to deliver personalization (using the user profile), providing an overview and an insight on the way we address these design issues. In addition, and in order to build high quality information services and tailoring them towards personal user needs, personalization in user interface becomes essential (Chi et al., 2001; Koch and Möslein, 2003). The proposed CSCW system can be expanded straightforwardly to other, similar to cotton, cultivations. Computer based community systems may provide powerful support in agricultural knowledge transfer, both in the direct exchange of information and in finding the people to exchange information with. For this goal and for successful collaboration we present the necessary synchronous and asynchronous tools that can enhance our application platform.

2. Integrated, Web-Based Cotton Cultivation Facilities 2.1 Facilities Web-based services are software components that run on a Web server and allow client programs to call its methods over HTTP. Each method on these components appears as a URL and may return data, perhaps as an XML document, and accept parameters (Hugo, 2002). These services designed to support interoperable machineto-machine interaction over a network. To indicate the methods and techniques used by the participants to achieve their goals, the proposed CSCW environment provides

a number of facilities. We categorize these facilities according to their importance in the collaboration process and the implementation of the CSCW system. These facilities are listed below:  Facilities with significant importance in the collaboration process and the implementation of the CSCW system - Multimedia and Text Search, through User-friendly environment. - Remote data entry (field observations on pest populations etc) - Integrated warning-alert and messaging system for critical points of cotton cultivation (disease and insect risk, frost, high temperatures, nutrient issues etc) and prediction systems (management risk) relative to pest control and cultivation management. Water supply timing, sprays, nutrition etc. - Automatic and formal certification of product quality according to the official regulations, IPM methodologies and good practice techniques. - Statistical analysis and data representation followed by charts and graphs.  Facilities with less importance in the collaboration process and the implementation of the CSCW system - Integrated management decisions relating to all the major pests of cotton, and improved collaboration for making the appropriate control tactics (chemical, biological etc) for cotton cultivation and pest management. - Virtual spray applications optimization and training in agricultural issues. - High performance training environment in agronomic issues (Education and Information tools and Digital Libraries (DLs) in which users can improve their agronomic knowledge, computer and information management skills). - User defined cultivation models according to each user needs, cultivation needs, scientific needs etc. Such, models are pest management models, cotton growth models, irrigation models etc. Simulation scenarios for improving the available models. - E-advertisement and web product promotion. The above facilities may also be offered as real-time or non-real time communication services.

2.2 Benefits The major benefits that arise from the use of the proposed CSCW system in cotton cultivation and production are the following:  Communication that helps people (producers, scientists etc) share information about the cotton cultivation. This service can be achieved with the usage of all synchronous and asynchronous CSCW tools.  Collaboration that helps people work together, solve common issues and making the appropriate decisions for cotton cultivation and pest management. The producers can ask for a solution to any problem related to the cultivation. Scientists can analyze the data they get and give the solutions to the producers.

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Weather-forecasting systems support at local level (microclimate level, individual or limited fields) for taking decisions on cotton cultivation protection and management. This can be achieved by relating the meteorological data with the observations for each development stage of the biological units (cotton, insects, diseases, natural enemies of cotton pests etc), the abundance, the time and the space distribution of each stage. Increment of cotton quality and its economical efficiency, and decrement of the environmental impacts. Improvement of the precision of treatment advice recommending applications only where and when necessary. Sharing of knowledge and expertise among participants. There is information access between producers according their need. They may have access to Web-Based Decision Support Systems (DSS) and Meteorological Data. Thus, they manage their cultivation more effectively and improve productivity. Also, producers can use CSCW tools so they are informed for any issue concerns the management of their cultivation, and Bridges geography distances and time.

3. System architecture CSCW architectures are unique and may be difficult to design. The first step towards an effective design is to understand current requirements and anticipate as many future requirements as possible. The general characteristics of the proposed architecture are the following:  Customizability and personalization.  Efficient and effective search and messaging, according to the user needs.  Different levels of collaboration activities, tools and functionalities.  Controlled authorization, depending on the experience and capabilities of each user.  Privacy and security. The proposed web-based CSCW system is object and goal oriented. The data are gathered through the Internet and the collaboration takes place in the web. The objectives are to serve the goals of PA, IPM and ICM on cotton cultivation in local level (for a specific microclimate production area), and support collaboration among participants of cotton management, which in most cases constitute small and heterogeneous distributed groups of participants. To achieve the prescribed objectives we include a number of services, which may also take the form of collaboration activities. Depending on the information exchange dynamism these activities may be classified into two main categories, namely collaboration activities with high and low level of interactivity. The first collaboration activities are characterized by a high level of interaction within the group. In the latter collaboration activities, the

information is transferred only on demand, thus lowering the degree of active interaction in the group. The activities can take place at the same location (collocated) or at different places (non-collocated). The system also includes multi-user customizable workspace, real-time data updates, live group video, voice conference, integrated messaging and alert system. Users may choose from the workspace environment various objects and features and make their own profile. Because of the heterogeneous groups involved (different knowledge, experience, capabilities, variety of equipment, etc.). The use of personalization techniques for tailoring information services to personal user needs is an essential design issue. In order the participants to take advantage of the integrated web-based services for cotton cultivation, we have defined three levels of services, with different level of interactivity, multimedia equipment and required bandwidth. These levels are presented in Figure 1 and described in the sequel: Hypermedia level: This level supports the basic hypermedia activities for web access of individual users. It requires low bandwidth and equipment standards. The Hypermedia level includes the following activities:  E-mail. The email can be enhanced with functionalities and user actions in order to support personalization and better performance.  Agenda. The agenda can be used from the user to save the contact information of others participants.  News. News can be enhanced with functionalities in order to be more suitable in user’s needs. Main collaborative level: This level supports the basic collaborative activities among the participants in a more formal way. It includes the following activities:  Notes.  Group writing and shared document editing tools (mainly for scientists).  File Exchange tools.  Digital Libraries.  Discussion Forums, Electronic Meeting Systems, Group Decision Support Systems, in which the participants can discuss various issues and take decision about the cultivation.  Chat. Interactive Multimedia level: This level includes interactive activities and advanced services such as:  Voice, Video and Desktop Conference.  Virtual Reality collaboration tools for spray applications optimisation, more safety spray applications, and training in agricultural issues.

Interactive Multimedia Level

Main collaborative level

Hypermedia level

Figure 1. The levels of collaboration tools and activities that CSCW platform supports To support appropriate decisions for cotton cultivation as well as to facilitate the collaboration process the CSCW system uses an enhanced database, which consists of data and objects as shown in Figure 2. USER

USER INTERFACE CSCW tools

Meteorological (Soil and Air Temperatures, Humidity, air velocity, solar radiation, rainfall) Biological (phenological growth stages, nutrition, disorders, pest and beneficial insects, cultivation practices)

DSSs

Biological observations  Growth stage  Nutrition status  Disorders  Pest and beneficial insects populations  Cultivation practices Cultivation techniques

Cotton Cultivation Knowledge Management

CSCW Knowledge Bank

Scientific Investigations Biological models  Crop Nutrition  Cotton Protection  Pest Prediction

PA, IPM, ICM (Regulations, Methodologies) GIS, GPS, Remote Sensing User profile

Collaboration activities Files, Documents, Multimedia elements, Schedules, Forums, DL, e-courses etc.

Figure 2. System enhanced database architecture

4. CSCW System Design Before the development and implementation of the CSCW system, it is important to outline the requirements and designing issues that we must address in order to ensure the particular needs and expectations of the users. Designing and developing such a system is a task that requires dealing with the following major challenges and issues: a) Variety of Different Standards and Requirements (Rogers 1994; Vertegaal and Guest, 1995). Many aspects should be considered in a personalized design, such as multiple users, the indirect linkage between the user’s activity and the application, layouts, objects design, text fonts, internationalisation, performance, high-level and low-level details, external factor, and legal, privacy and security issues etc. b) Building a CSCW environment. There are many methodologies, theories and guidelines on how to build a CSCW environment. Some of them are very specific, while some others are quite inexplicit. However, not all of them are suitable for operation. c) Complexity of the Tools. A large number of tools and applications have already been developed and are in use today. However, in most cases there is a difficulty for the end-users to use them effectively, requiring enormous training. d) Difficulty of implementation. In most cases it is very difficult to determine whether the user interface has been tested completely. e) Real-Time Programming and Personalization. The user interface must be attractive, friendly, easy to use and effective. As a result, more complicated programming and algorithms is needed, and f) Knowledge and Experience. Social issues and difference user knowledge and experience. The basic features need to be considered in the design of the proposed CSCW system are the spatial visual workspace, the support of the distributed activities within the workspace, the common and visually similar environment in all the participants, allowing at the same time different functionalities to take place and in accordance with the role of each user, the provision of timely feedback of all actions within the workspace, and finally, the support of workspace awareness.

4.1 Modeling the user profile CSCW systems are generally interactive, and therefore the design of the user profile is critical. We focus on the main features of user’s profile, and particularly on what information is gathered about the user. It is important that users can access, choose and change these features according to their needs and interests. In addition, different types of user profile information must be gathered in order to establish collaboration among the participants, as well as to provide the required services in a personalized way. In the personalized user interface, different users have different roles (Guzdial et al, 2000). In the proposed platform, users are divided in two predefined groups,

according to their specific access rights (authorization). In the first group users categorized according their knowledge, profession, and specialty. In the second group, users are defined according their role and goal in the system. The categories of participants and their activities on the proposed CSCW system, is shown in Table 1. Note that a user belongs to a particular group according with his profession and his goals. Thus, a cotton producer may belongs to the group of observers if he gathers and provides in the system observations about the cultivation, or in the group of Scientists and Expert, and similarly in the group of Collaborative Authors, if he has the appropriate qualifications. Table 1. Categories of participants and their activities in the CSCW system Categories of participants Activities According their knowledge, profession, and specialty Scientists and Experts Provide scientific knowledge. Associations and Organizations Provide scientific knowledge and technical support. Companies Provide products needed for the cultivation (seeds, pesticides etc). Mainly users having scientific or/and commercial interests. They may offer advices, recommendations, share their knowledge and experience, promote products, buy cotton, etc. Cotton Producers Manage the cotton cultivation. According their role and goal in the CSCW system System Administrator Administrate the CSCW system Community Administrator Administrate the functionalities of CSCW tools. They are responsibly for the proper collaboration of the participants. Collaborative Authors Scientists responsible for adding content to existing web pages, or creating new pages. They schedule the forums and the conference, create the content of the digital library, identify the content, define the search keywords for each content and make sure that content is properly accessible. Data collectors Provide appropriate observations about the cultivation (pest population, nutrient disorders, etc.)

4.2 Acquiring the user profile The user profile is acquired through direct request of information from the users (fillin-forms or dialogs boxes) or by watching the user’s activities. However, the acquisition itself does not solve the “cold-start-problem” (Koch, 2002). Participants want to have predictions and recommendations from the beginning. To solve this problem the system must determine the user’s needs by creating the profiles from other sources, such as meteorological, epidemiological and historical data relative with cotton cultivation in a specific cotton farm. The different sources of user profile and the relative data that must be gathered is shown in Table 2. Table 2. Sources of user profile and the relative data that must be gathered. Source of user profile Information (Data that must be gathered) User identification profile User name, contact and location information, user interest, preferences and goals, user knowledge and skills. Cotton farm information Location, properties (size, soil properties, irrigation potential), historical information about the cotton farm, such as the kind of plant cultivated the last years, the pest problems that have came up, the size of production etc., relationships among the participants Producer Calendar Information about the cultivation, about the user’s agenda, appointments, and cultivation applications (sprays, fertilizations, irrigations etc.) Data Collector Calendar Information about the biological observations such as, the type and the number of observations, the date, time of each observation and the location of each observation. Interaction profile Communication events (a user can send messages to other users via the CSCW platform), browsing actions, annotation, actions, etc. Dynamic profile The system can automatically measure information about the needs from each user, depends on cultivation conditions and participants behaviors or actions.

4.3 Personalization A major problem in the design and implementation of any CSCW system is to evaluate the user needs. Current methods of software system design do not sufficiently capture the needs of the users (Kramer, 2000). In order to develop high quality information services and tailor them to personal user needs, user interface personalization becomes essential (Schuckman et al., 1996; Kramer, 2000; Koch and

Möslein, 2003). Personalization is a collection of technologies and applications used in the design of users profile in order to provide to the user tailored products, services, and information (Rossi, 2001; Schubert and Koch, 2002; Koch and Möslein, 2003; Schubert and Koch, 2003). A wide variety of technologies and systems have been developed for personalization purposes and are available on commercial basis, however little attention has been spent for modeling and designing personalized web platforms. Note that a critical factor towards the success of design-personalized applications is to put computer technology after the needs of end users (Kramer, 2000). From the collected data, user profiles are created and used to personalized contents. Then, new data are collected, while the profiles are updated. The features of personalization are wide-ranged, from simple display of the user’s name, to complex items in which we can measure user’s needs and activities. The main goal of personalization systems is to provide the users what they want or need without asking them for it specifically. Personalization has become important in web-based communication and collaboration services like the community systems (Koch and Wörndl, 2001). In these systems user profiles are also needed for exchange of information among users and for finding people to exchange information and data. Thus, community systems and personalization features can provide powerful support to agricultural knowledge dissemination.

4.4 Personalization techniques The main personalization techniques and mechanisms that the CSCW system uses to achieve personalization, and specify the user profile and interests are shown in Figure 3. These techniques are the following: User Recognition: The system recognizes the users when they enter the system using their user name and password. This is the simplest of all methods. Static User Preference: In each section or activity we have introduced predefined or user defined questionnaires to simplify the procedure of gathering information. Each questionnaire includes a number of wizard steps depending on the given answers. The answers can be acquired by clicking a check-box or an option-box or filling a textbox. The users are able to review, modify, and delete personal information from their profile by using the appropriate wizard steps. Dynamic User Preference: The user personalization changes dynamically, according to his/hers preferences for certain services, items, or user behaviors and activities, considering the behavior and activities of the users who participate with this user. Complex statistical algorithms and machine learning techniques are needed in order to achieve this type of personalization (Pazzani and Billsus, 1997).

Automatic determination of User Needs: In the previous cases, the user provides the information for personalization directly or indirectly. Here we consider data from other sources, in which the user has less, or none contribution. As we mentioned in a previous section of this paper the system supports an enhanced database for the purposes of cotton cultivation management. This database can provide to the system with useful information about the user needs. For example, if we acquire through specific observations that a cotton field is infected with a pest, the owner of this field must be informed about this pest population, biology, ways of treatment etc. For this purpose, some synchronous or asynchronous tools may be used. For the success of this kind of personalization, intelligent machine learning techniques must be used. USER

User Interests

USER INTERFACE CSCW tools

Personalization techniques

User Profile

User Recognition Static User Preference Dynamic User Preference

Automatic determination of User Needs

Cotton Cultivation Knowledge Management

Filtering

Figure 3. The main personalization techniques for building the User Profile

5. Privacy and Security User Data collection is the most privacy-critical process to the personalization procedure. Users want to be in control of their personal information. It is important to give users control over how much information about themselves is made available to other participants. In many situations, users can choose to be anonymous or use a pseudonym. Although, anonymity can be crucial in encouraging participation and is useful for providing protection, there is continuing pressure to share more information for valuable and useful reasons. Sharing more information about users, enable our CSCW system to provide more useful personalization and matching to users interests. To assess a multimedia computing and communication environment users require adequate feedback and control mechanisms (Bellotti, 1997). Our CSCW platform supports mechanisms that give users control over what information gets shared and what remains private. Encryption techniques are also included to secure private information.

6. Conclusion and future work In this paper, we presented the architecture and the design of an agricultural CSCW system in order to provide integrated, web-based services for cotton cultivation. We mentioned the major facilities and benefits that arise from the use of the above system in cotton cultivation. CSCW architectures, particularly those for synchronous or interactive systems are unique and can be difficult to design. We focused on a number of important interrelated design issues of user profiles, namely, what information is gathered about a user (modeling the user profile), where do we get the user information from (acquiring the user profile), and how to use the user information to deliver personalization (using the user profile). We presented the main personalization techniques that are essential in order to build high quality information services and tailoring them towards cotton-participants needs and interests. We have introduced the automatic determination of user needs, a personalization technique that integrates user profile and cotton cultivation knowledge. User data collection is the most privacy-critical process to the personalization procedure. Thus, the proposed CSCW platform supports privacy and encryption techniques and mechanisms that ensure the user privacy and the secure of the private information. The framework is intended to contribute to a unified view of requirements of a knowledge management support system by identifying core components and functionalities. Thus, the essential features needed for successful collaboration and the ability to take the appropriate decisions for cotton cultivation and pest management can be enhanced. To this aid, a formative empirical study is currently under way to inform the design of CSCW system to support cotton cultivation services.

7. Acknowledgements We gratefully acknowledge the helpful suggestions of Dr. Costas Yalouris and Stavros G. Papageorgiou.

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