Trans-Disciplinary Research

Research is only as good as the investigator.  It is the researcher’s creativity, sensitivity, flexibility and skill in using the verification strategies that determines the reliability and validity of the evolving study. ‘Research’ itself is recognised as a constructed concept, in the context of an investigative process. Crossing boundaries between scientific disciplines and between science and society implies, however, compromise on acquired specialization and the research environment and breaking out to new fields of research with considerable uncertainty. Thus, the question is how to move from the present unilateral reductionist system to a more holistic one that favours new inter- and trans-disciplinary approaches? The mutual recognition of different disciplines and the willingness to integrate disciplinary and interdisciplinary knowledge in a trans-disciplinary framework is an important first step. Creation of a mutual learning environment is key to integration of trans-disciplinary processes.

With the rapid increase in the complexity of the technology of farming, there is now a recognized need to improve the skills and education of our farmers – the human capital of agriculture. The Internet is changing the way society accesses and processes information. Farmers now have access to a wide range of information. The managerial tasks for arable farming are currently transforming into a new paradigm, requiring more attention on the interaction with the crops, surroundings ad ecosystem function. The framework’s aim is to support farmers in the design of their production systems at the farm level for crop yield and ecosystem function called OTAIGRO®. It is a web-based Farm Management Information Systems (FMIS) framework fundamental importance for a successful operational farm management, agro-corridor, agribusiness management, co-value creation, collective intelligence and resilience agriculture.
To empower the farmer in achieving to master the planning, organization, monitoring, evaluation controlling of the entire farm’s production and business processes and its engineering of systems from components (data, processes, software, events, and subsystems) powered by metadata. Metadata have been used in information systems engineering for many years, but usually in a specialist, one-off and uncoordinated way. Metadata are required for explaining answers from ever more complex information systems. It assists in distilling knowledge from information and data. It assists in multilingualism and in multimedia representations.

There are different types of  metadata :  System catalogs metadata, Relationship metadata, Content metadata, Data lineage metadata, Technical metadata,  Data usage metadata, System metadata and Process metadata.

A forward loop is characterized by uncertainty, novelty, experimentation, time of greatest potential for the initiation of either destructive or creative change in the system. It is the time when human actions-intentional and thoughtful, or spontaneous and innovation can have the biggest impact of objectives or construct. A back loop –  Laboratories Mechanisms:

  • Construct R&D, Joint R&D
  • Consultancy Service (builds relationships that can lead to contract
  • Collaborations
  • Provision of Facilities eg. incubators (knowledge parks), Agro corridors, universities and institutional laboratories etcs
  • Military infrastructure and centre of gravity (CoG)
  • Products development and service science.

Collaboration – It refers to the capacity of human communities to evolve towards higher order complexity and harmony, through such innovation mechanisms as differentiation and integration, competition and collaboration. The collective activity of individuals and their modifications to the environment are responsible for intelligence using the internet of things (IoTs) on agriculture value chain development called concept of eco-functional intensification for sustainability development.

The scenario (S)  narrative gives voice to the important qualitative and quantitative factors shaping development such as values, behaviours and institutions, providing a broader perspective framework for participants and stakeholders in any area or sectorial application.

A simplified representation of the adaptive cycle above shows two phases in a more recognizable form. The back-loop a slow accumulation of disciplinary knowledge Market –to- laboratory   . The back-loop is the time of greatest potential for the initiation of either destructive or creative change in the system from market to laboratory like internet (internet of things)  i.e machine-to-human interface, farm sensors and  cloud computing. Market (value) to Laboratories Mechanisms:

  • Research objective, construct, investigation;
  • Carry out applied R&D
  • Intellectual Protection (IP)
  • Technology Licensing
  • Spin-off Researchers.
  • Big Data Analytics.

Value drives intelligence – Value of talented people goes beyond predefined tasks, building brands, relationships, reputations, and other intangibles (high value).

                                    © 2019 Ayodele A. Otaiku

 OTAIGRO ® framework web-based Farm Management Information Systems (FMIS) and an innovation ecosystem for natural resource management

All parties roles and responsibilities of  farmers within OTAIGRO ® innovation ecosystem