Design Challenges for Innovation Management on Agro-Food Sector

Current status of research indicates that we assist to location-specific factor supremacy as determinants in regional attractiveness and sustainability being territorial driven, we offer strong arguments for policy makers in order to enable this long term strategy. We also address another issue heavily disputed between academics-that is the return to local and regional offerings as complementary to global assumption. Assisting today to a hybrid innovation process, relying upon territorial marketing-an umbrella for too many issues cvasi- exploited: eco-clusters, local and regional offerings; traditional products/services exploiting, regional clusters competing for funds; we are focusing on complex industrial -rural system reconfiguration relying upon dynamic evolution of territorial branding into competitive identity, as the disruptive behavior we need in sustainable development. Successful development strategies are based on the ability to build an institutional territorial coherence-social and environmental sustainability being inextricably interdependent, such a complex coordination structure relies on territorial knowledge sharing through expertise polls consultation- as key concept of good governance. This model of innovational resource allocation coordination on agro food chains, relying upon clusterisation through patterns of innovational management deficit, offers a relevant solution for synergic orientation of assistance and mentoring efforts on the sector, enable the capitalization of relevant capabilities and increase the addressability from innovation demand side. Based upon auditing 500 SME’s from agro food sector in Europe and 51 in SE region, the paper is fully documented on there years of data analyzing from Agro Food sector on 10 European countries in the framework on FP6 SPAS European Project.territorial knowledge sharing, innovation resource allocation, disruptive territorial solution, community supported agro food chains

Report from MicroResearch 2020 Strategic Planning Meeting, April 24 & 25, 2014, Toronto, Canada

“MicroResearch” (MR, www.microresearch.ca) is a new model to build capacity for community-directed research to overcome longstanding research system gaps at the community level in East Africa. To date, MR has trained over 390 healthcare professionals at five universities in Uganda, Kenya and Tanzania. Training starts with a two-week MR Workshop, where participants learn basic research proposal development, analytic, and knowledge translation skills. This report provides a summary of conference papers and discussions, including participating non-governmental organizations, as well as providing reference links to participants and resources

Developing Online Tutors and Mentors in Sri Lanka through a Community Building Model: Predictors of Satisfaction

This paper discusses the results of a tutor mentor development program that utilized a community building model to train online tutors and mentors in higher education institutions and professional organizations in Sri Lanka. Based on WisCom; an instructional design model for developing online wisdom communities, this tutor mentor development program which utilized a blended format of face-to-face and online activities in MOODLE, attempted to build a learning community between trainees, both academics and professionals who represented diverse disciplines and organizations. A regression model examined predictors of learner satisfaction, using four independent variables: Community Building, Interaction, Course Design, and Learner Support. Interaction emerged as a strong predictor of Learner Satisfaction explaining 50.2% of the variance in Learner Satisfaction. This finding shows the importance of designing interactive learning activities to support learning online, and contradicts the general belief that Sri Lankan participants would be less likely to interact online because they come from a traditional education system that encourages passivity and reception of ideas from a more learned teacher. Qualitative analysis showed evidence of several types of learning online as a result of collaborative group interaction, as well as issues that contributed to non-participation. Factors that motivated participants to stay engaged in learning could be classified into three categories: (1) general enjoyment, interest and motivation; (2) collaborative learning and community building; and (3) knowledge building. These results suggest that the online learning design based on WisCom led to learner satisfaction and supported interaction and collaborative learning in the Sri Lankan socio-cultural context

Modeling usage of an online research community

Although online communities have been thought of as a new way for collaboration across geographic boundaries in the scientific world, they have a problem attracting people to keep visiting. The main purpose of this study is to understand how people behave in such communities, and to build and evaluate tools to stimulate engagement in a research community. These tools were designed based on a research framework of factors that influence online participation and relationship development. There are two main objectives for people to join an online community, information sharing and interpersonal relationship development, such as friends or colleagues. The tools designed in this study are to serve both information sharing and interpersonal relationship development needs. The awareness tool is designed to increase the sense of a community and increase the degree of social presence of members in the community. The recommender system is designed to help provide higher quality and personalized information to community members. It also helps to match community members into subgroups based on their interests. The designed tools were implemented in a field site - the Asynchronous Learning Networks (ALN) Research community. A longitudinal field study was used to evaluate the effectiveness of the designed tools. This research explored people\u27s behavior inside a research community by analyzing web server logs. The results show that although there are not many interactions in the community space, the WebCenter has been visited extensively by its members. There are over 2,000 hits per day on average and over 5,000 article accesses during the observation period. This research also provided a framework to identify factors that affect people\u27s engagement in an online community. The research framework was tested using the PLS modeling method with online survey responses. The results show that perceived usefulness performs a very significant role in members\u27 intention to continue using the system and their perceived preliminary networking. The results also show that the quality of the content of the system is a strong indicator for both perceived usefulness of the community space and perceived ease of use of the community system. Perceived ease of use did not show a strong correlation with intention to continue use which was consistent with other studies of Technology Acceptance Model (TAM). For the ALN research community, this online community helps its members to broaden their contacts, improve the quality and quantity of their research, and increase the dissemination of knowledge among community members

Dependency Management 2.0 – A Semantic Web Enabled Approach

Software development and evolution are highly distributed processes that involve a multitude of supporting tools and resources. Application programming interfaces are commonly used by software developers to reduce development cost and complexity by reusing code developed by third-parties or published by the open source community. However, these application programming interfaces have also introduced new challenges to the Software Engineering community (e.g., software vulnerabilities, API incompatibilities, and software license violations) that not only extend beyond the traditional boundaries of individual projects but also involve different software artifacts. As a result, there is the need for a technology-independent representation of software dependency semantics and the ability to seamlessly integrate this representation with knowledge from other software artifacts. The Semantic Web and its supporting technology stack have been widely promoted to model, integrate, and support interoperability among heterogeneous data sources. This dissertation takes advantage of the Semantic Web and its enabling technology stack for knowledge modeling and integration. The thesis introduces five major contributions: (1) We present a formal Software Build System Ontology – SBSON, which captures concepts and properties for software build and dependency management systems. This formal knowledge representation allows us to take advantage of Semantic Web inference services forming the basis for a more flexibility API dependency analysis compared to traditional proprietary analysis approaches. (2) We conducted a user survey which involved 53 open source developers to allow us to gain insights on how actual developers manage API breaking changes. (3) We introduced a novel approach which integrates our SBSON model with knowledge about source code usage and changes within the Maven ecosystem to support API consumers and producers in managing (assessing and minimizing) the impacts of breaking changes. (4) A Security Vulnerability Analysis Framework (SV-AF) is introduced, which integrates builds system, source code, versioning system, and vulnerability ontologies to trace and assess the impact of security vulnerabilities across project boundaries. (5) Finally, we introduce an Ontological Trustworthiness Assessment Model (OntTAM). OntTAM is an integration of our build, source code, vulnerability and license ontologies which supports a holistic analysis and assessment of quality attributes related to the trustworthiness of libraries and APIs in open source systems. Several case studies are presented to illustrate the applicability and flexibility of our modelling approach, demonstrating that our knowledge modeling approach can seamlessly integrate and reuse knowledge extracted from existing build and dependency management systems with other existing heterogeneous data sources found in the software engineering domain. As part of our case studies, we also demonstrate how this unified knowledge model can enable new types of project dependency analysis

Considering human capital theory in assessment and training:mapping the gap betweem current skills and the needs of a knowledge-based economy in northeast Iowa

In light of the current economic downturn, thousands of Iowan\u27s are unemployed and this is the ideal time to build the skills of the workforce to compete in the knowledge-based economy so businesses and entrepreneurs can compete in a global economy. A tool for assessing the skills and knowledge of dislocated workers and students as well as identifying skills deficits in order to match individuals\u27 transferrable skills to high-demand jobs is essential in order for dislocated workers and students to increase their human capital. It is essential for individuals to make informed decisions regarding the training they need and for educational institutions to provide appropriate educational programs that are responsive to the needs of the knowledge-based economy. The purposes of this study were to compare the relationships between knowledge levels, transferrable skills, and skill needs of dislocated workers in northeast Iowa to the knowledge and skill needs of area businesses, to outline and develop a model for equipping Iowa\u27s workforce for a knowledge-based economy, and to provide a paradigm for assessment and training. The research questions guiding this study included: (a) What are the demographic characteristics of northeast Iowa\u27s dislocated workers? (b) What are the current skills, knowledge, and competencies of dislocated workers in northeast Iowa? (c) Are there differences in the skills, knowledge, and competencies between male and female dislocated workers? (d) What are the aspirations of dislocated workers in northeast Iowa? (e) What are the skills gaps of dislocated worker regarding the knowledge-based economy? (f) What education and training programs are needed to adapt the current skills set clusters to a knowledge-based economy in northeast Iowa? This quantitative study was conducted using the theoretical frameworks of human capital, new growth, knowledge-based economy, and action research theory concepts. Further, this study analyzes the role the community college system is expected to take in workforce preparation and economic development, along with the Workforce Investment Act (WIA) One Stop Centers and the Iowa Workforce Development Research Bureau. The quantitative techniques of descriptive and inferential statistics were used to describe the data set of 477 individuals--284 males and 193 females--laid off from industries in northeast Iowa. The dislocated worker data was matched with additional demographic and occupational data obtained from the Occupational Information Network (O*NET). The results indicate a high percentage of females and males intend to continue their education. The findings show a significant need for additional training for dislocated workers to be employed in emerging occupations to increase their knowledge and work activity (skills) in order to be prepared for emerging occupations in biotechnology, advanced manufacturing, and information technology. The workforce analysis on regional competitive advantage supports the need for emerging occupations. The study demonstrates the need for further assessment and training for dislocated workers. It also provides a replicable model for other community colleges, One Stop workforce centers, and economic development interests and has the potential to provide an on-line tool for advising, education and recruitment. Finally, the study contributes knowledge and research valuable for One Stop workforce Centers, community colleges and economic development

Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

Supporting the migration towards model-driven robotic systems

Robots are increasingly deployed to perform every-day tasks. It is crucial to implement reliable and reusable systems to reduce development effort. The complexity of robotic systems requires the collaboration of experts from different backgrounds. Therefore, clear and communicatable abstraction of components is essential for successful development process. There has been a demand in the community for increased adoption of software engineering approaches to support better robotic systems. Adopting model-driven approaches has been proved successful in supporting this movement. We aim to support the adaptation of model-driven approaches in robotic domain in three interest areas: behavior models, structural models and guaranteeing confidence in system behavior.The overall goal is to support the creation of reusable, verifiable and easy to communicate robotic missions and systems. To achieve that, we conducted a mix of knowledge-seeking and solution-seeking studies. We started with behavior models. We wanted to build knowledge about used behavior models in practice. We investigated the state-of-practice of an emerging behavior model, behavior trees, in comparison to two standardized UML models and a traditional roboticists choice. Moving to the second interest area, we wanted to support the creation of light-weight tools for building an understanding of system structure using feature models. We conducted a pilot evaluation of an already light-weight tool, called FeatureVista. The final interest area was guaranteeing confidence in system behavior. The usual engineering process of self-adaptive controllers in robotic involves different model-based approaches. We wanted to investigate an approach that reaffirm, at code-level, control properties while keeping the usual engineering process. We investigated an approach for mapping control properties to software ones using an appropriate input format for software model-based checking.Our investigations in the different interest areas have built knowledge and shed light on opportunities. We provided characteristics of behavior models, behavior trees and state machines, in popular robotic implementations and highlighted opportunities for improvements. We also provided usage trend for studied implementations in open-source projects. In addition, we provided corestructural characteristic and code-reuse patterns for studied behavior models in open-source projects. For feature models, our results showed promising results for using an interactive tool that provides an easy and initiative navigation between feature models and software components. Improvement aspects were also highlighted for developing similar tools. Finally, our work for the confidence of system behavior showed promising results in reaffirming the correctness of a control property at code-level using appropriate software notation, specification patterns. Also, our approach allowed keeping the current practices of using model-based approaches in self-adaptive robotic systems

Designing Attention-Centric Notification Systems: Five HCI Challenges

Through an examination of the emerging domain of cognitive systems, with a focus on attention-centric cognitive systems used for notification, this document explores the human-computer interaction challenges that must be addressed for successful interface design. This document asserts that with compatible tools and methods, user notification requirements and interface usability can be abstracted, expressed, and compared with critical parameter ratings; that is, even novice designers can assess attention cost factors to determine target parameter levels for new system development. With a general understanding of the user tasks supported by the notification system, a designer can access the repository of design knowledge for appropriate information and interaction design techniques (e.g., use of color, audio features, animation, screen size, transition of states, etc), which have analytically and empirically derived ratings. Furthermore, usability evaluation methods, provided to designers as part of the integrated system, are adaptable to specific combinations of targeted parameter levels. User testing results can be conveniently added back into the design knowledge repository and compared to target parameter levels to determine design success and build reusable HCI knowledge. This approach is discussed in greater detail as we describe five HCI challenges relating to cognitive system development: (1) convenient access to basic research and guidelines, (2) requirements engineering methods for notification interfaces, (3) better and more usable predictive modeling for pre-attentive and dual-task interfaces, (4) standard empirical evaluation procedures for notification systems, and (5) conceptual frameworks for organizing reusable design and software components. This document also describes our initial work toward building infrastructure to overcome these five challenges, focused on notification system development. We described LINK-UP, a design environment grounded on years of theory and method development within HCI, providing a mechanism to integrate interdisciplinary expertise from the cognitive systems research community. Claims allow convenient access to basic research and guidelines, while modules parallel a lifecycle development iteration and provide a process for requirements engineering guided by this basic research. The activities carried out through LINK-UP provide access to and interaction with reusable design components organized based on our framework. We think that this approach may provide the scientific basis necessary for exciting interdisciplinary advancement through many fields of design, with notification systems serving as an initial model. A version of this document will appear as chapter 3 in the book Cognitive Systems: Human Cognitive Models in Systems Design edited by Chris Forsythe, Michael Bernard, and Timothy Goldsmith resulting from a workshop led by the editors in summer 2003. The authors are grateful for the input of the workshop organizers and conference attendees in the preparation of this document