Responsible Quantification Sample Clauses

Responsible Quantification. SUPER MoRRI developed some simple tools to assist users in interpreting the quantifications presented, including indicators. Support for the capacity to make well-informed interpretations of data and information reflects a commitment to responsible quantification. A variety of quantification and visualisation techniques provide users with monitoring outputs within the framework. Primary data underpinning tools and resources provided at PROMISE are available to prospective users under FAIR (findable, accessible, interoperable, reusable) principles. SUPER MoRRI developed the concept of credible contextualisation as part of a general approach to responsible quantification. The main ▇▇▇▇▇ of credible contextualisation is to support users of indicators and other data-driven elements, by providing specific tools to support the appropriate and credible interpretation of the information provided. Credible contextualisation extends from a recognition that there are no universal context-free metrics, indicators, or other quantifications. Rather, data used in indicators are gathered in a specific context. The degree to which any quantification can be credibly utilised as a comparator or as a benchmark, for example, depends on the degree of de-contextualisation appropriate for this quantification. Generally, the further you move away in time and space from a specific action or intervention of interest that you wish to monitor, the more likely it becomes that the complex dynamics of broader societal factors will influence or ‘over-determine’ the outcomes or impacts that you might be seeking to attribute to that action or intervention. Second, credible contextualisation recognises that indicators should be developed in ways that are relevant and meaningful in specific use contexts.