What you won't find in our wikis

Our wikis offer a minimalistic yet cohesive view on development knowledge, much of it in the public domain, and the target groups involved in their maintenance and growth. They avoid unnecessary repeating of content and justifications that can be found elsewhere on the web. They provide access points to authentic work and assets (essential facilities in the knowledge economy), but they are not themselves an essential facility.

Stepstones in an engagement journey

Our wikis support the engagement strategy for local content acceleration: that the identified stakeholder categories (target groups) take ownership of the systematization of the public content , the test cases and the subsequent value construction and risk mitigation on their basis, as well as their use in communicating with their constituencies.

Target groups

The users of the #tag2wiki Engagement Platform are at four socio-technical levels in accordance with the multiple levels of agency in the social architecture:

  • pico: the journeys of persons in various roles, for instance as practitioners, engineers, managers, farmers, parents, public servants, researchers.
  • micro: the partner journeys of organizations that own, maintain, and/or operate plants, land or service facilities, and employ multiple persons in their operations.
  • meso: the sector journeys led by industry associations, standards organisations, engineering and science disciplines; these consolidate sectoral commons.
  • macro: the (sustainable) landscape or macro journeys at scales that are global, international, regional, national and local.

Systematized and classified content

We propose a distinction between the systematized content that Wikinetix is advocating via its wikis, and the ''traditional'' WEB-BASED MEDIA. Although these web-based media offer important advantages over traditional media such as print, the ease of producing content goes with fragmentation, information overload, dis-authentication and rewording, lost trace-ability, quality loss, etc.

For the classification of content shared via social media, we propose #tagcoding using structured hashtags.