Editorial: Agile data-oriented research tools to support smallholder farm system transformation

Smallholder farming systems produce the majority of the food consumed in many lower- and middle-income countries and contribute significantly to national and local economies. However, a transformation is needed to deliver food security and decent incomes for the farmers themselves and to feed the growing populations within those countries. This transformation must be environmentally and socially sustainable to be successful in the long term. One obstacle is the lack of good quality, timely, and targeted information.

In this editorial, we unpack three key terms from the title of this Research Topic and use the articles published to illustrate those terms. The key terms are “data-oriented,” “agile,” and “system transformation.” The term “data-oriented” is used to refer to big data, the compilation of data, replicable analysis methods, and the various other developments facilitated by the digital revolution. Dealing with one of the negative features of the digital revolution is a recurring theme: information overload—or “infobesity”—whereby the flood of non-useful information hampers rational decision-making. The term “agile” is used to refer to an emerging but not yet clearly defined methodological style, which tends to be enabled by the digital revolution, attempts to deal with problems of infobesity, and attempts to deal with the challenge of conducting outcome-oriented science in complex and uncertain situations. The term “system transformation” refers to efforts to stimulate and facilitate sustainability transitions within the smallholder farming sector. These terms are explored further below. The Research Topic focuses on research tools (tools or methods for knowledge creation) and excludes tools which are primarily geared toward the implementation of farming activities.