Value drives intelligence. Intelligence exists within the individual, within knowledge working groups, and within society as a whole. What is collective intelligence? it refers to the capacity of human communities to evolve towards higher order complexity and harmony, through such innovation mechanisms as differentiation , integration, competition and collaboration. Collective intelligence does not necessarily mean the sharing of a cognitive state by, for example, mirror neurons. Intelligence can be exhibited by a network of individuals where each individual is specialized in a particular task so that no two individuals share the same cognitive state (skills, activity, and so on) per se, but that the successful action depends on the activities of the entire network like climate forecasts, surveys/surveillance and example is agriculture value chain development encapsulated as a framework called OTAIGRO®.
Agribusiness New logic of value creation
- The ultimate value of any production is its contribution to the wellbeing and happiness of the consumers;
- Intellectual capital (creativity, imagination, and conceptualization) is becoming the main source of value creation. Physical capital (”factories”) provides the “matter”, whereas human capital is creating the “spirit” (conceptual product, meaning, content);
- The value is created in voluntary value networks, “flocks”, which are partly local and partly global like crowdsourcing innoaf.com;
- A firm is becoming a network of connections and production is conducted by orchestrating partners in the network.
HUETZ Agro® – Analytics
Productivity gains in the agricultural industries have historically been driven by the adoption of new technical products and processes. Farming systems are demanding innovative design to increase production, and given the complexity of intervention and modelling is required for the following:
- The representation of the biophysical, technical, and decision processes involved; and the evaluation ex-ante of the impacts of technical or organizational innovations that are difficult to measure experimentally.
- Farming systems are demanding innovative design to increase production cum ecosystem sustainability, and given the complexity of intervention, their modelling is requiring:
Biophysical, technical, and decision processes involved;
b. The evaluation ex-ante of the impacts of technical or organizational innovations that are difficult to measure experimentally.
- Metadata management categorizing of information about data objects. Metadata management provides the tools, processes, and environment to enable an organization or service providers to answer the question, “How do we know, what we know about our data?” The capability to easily and conveniently locate and retrieve information about data objects, their meaning, physical location, characteristics, and usage is powerful and beneficial to the enterprise. This capability enhances the ability of the organization to deal with risk, meet regulatory requirements, and improve IT productivity.
- Good metadata management gives organizations confidence in their information. Confidence flows from the trustworthiness of the information received. Information confidence helps organizations make better decisions because they know they can trust what they see. Trustworthiness comes about by knowing the information received is governed, approved, and therefore true.
There are different sections of the portal dedicated to the following scenarios:
- Strengthen and extend the network of geospatial information management;
- Implement standardized geospatial data‐sharing practices and provide a common software;
- Platform based on open standards ;
- Provide the hosting foundation for a visualization facility as well as a centrally accessible ;
- Data repository for agency‐produced or procured geospatial content such as maps, geographical information system data; and
- Remote sensing imagery, Global Navigation Satellite System logs, crowd‐sourced data and other geo‐referenced information.