title: Note on y-truncation: a simple approach to generating bounded distributions for environmental applications

authors: Bardsley, W. Earl

subjects: bounded distribution

abstract: It may sometimes be desirable to introduce bounds into probability distributions to formalise the presence of upper or lower physical limits to data to which the distribution has been applied. For example, an upper bound in raindrop sizes might be represented by introducing an upper bound to an exponential drop-size distribution. However, the standard method of truncating unbounded probability distributions yields distributions with non-zero probability density at the resulting bounds. In reality it is likely that physical bounding processes in nature increase in intensity as the bound is approached, causing a progressive decline in observation relative frequency to zero at the bound. Truncation below a y-axis point is proposed as a simple alternative means of creating more natural truncated probability distributions for application to data of this type. The resulting “y-truncated” distributions have similarities with the traditional truncated distributions but probability densities have the desirable feature of always declining to zero at the bounds. In addition, the y-truncation approach can also serve in its own right as a means

text: Note on y-truncation: a simple approach to generating bounded distributions for environmental applications It may sometimes be desirable to introduce bounds into probability distributions to formalise the presence of upper or lower physical limits to data to which the distribution has been applied. For example, an upper bound in raindrop sizes might be represented by introducing an upper bound to an exponential drop-size distribution. However, the standard method of truncating unbounded probability distributions yields distributions with non-zero probability density at the resulting bounds. In reality it is likely that physical bounding processes in nature increase in intensity as the bound is approached, causing a progressive decline in observation relative frequency to zero at the bound. Truncation below a y-axis point is proposed as a simple alternative means of creating more natural truncated probability distributions for application to data of this type. The resulting “y-truncated” distributions have similarities with the traditional truncated distributions but probability densities have the desirable feature of always declining to zero at the bounds. In addition, the y-truncation approach can also serve in its own right as a means

year: 2007

title: Visual collaging of music in a digital library

authors: Bainbridge, David

abstract: This article explores the role visual browsing can play within a digital music library. The context to the work is provided through a review of related techniques drawn from the fields of digital libraries and human computer interaction. Implemented within the open source digital library
toolkit Greenstone, a prototype system is described that combines images located through textual metadata with a visualisation technique known as collaging to provide a leisurely, undirected interaction with a music collection. Emphasis in the article is given to the augmentations of the basic technique to work in the musical domain.

text: Visual collaging of music in a digital library This article explores the role visual browsing can play within a digital music library. The context to the work is provided through a review of related techniques drawn from the fields of digital libraries and human computer interaction. Implemented within the open source digital library
toolkit Greenstone, a prototype system is described that combines images located through textual metadata with a visualisation technique known as collaging to provide a leisurely, undirected interaction with a music collection. Emphasis in the article is given to the augmentations of the basic technique to work in the musical domain.

year: 2004-10-01

title: Indigenous data sovereignty

authors: Kukutai, Tahu

abstract: Indigenous Peoples have always been ‘data warriors’. Our ancient traditions recorded and protected information and knowledge through art, carving, song, chants and other practises. Deliberate efforts to expunge these knowledge systems were part and parcel of colonisation, along with state-imposed practices of counting and classifying Indigenous populations. As a result, Indigenous Peoples often encounter severe data deficits when trying to access high quality, culturally relevant data to pursue their goals, but an abundance of data that reflects and serves government interests regarding Indigenous Peoples and their lands. 
The concept of Indigenous data sovereignty (ID-SOV) is a relatively recent one, with the first major publication on the topic only appearing in 2016.1 ID-SOV is defined as the right of Indigenous Peoples to own, control, access and possess data that derive from them, and which pertain to their members, knowledge systems, customs or territories.2,3,4 ID-SOV is supported by Indigenous Peoples’ inherent rights of self-determination and governance over their peoples, territories and resources as affirmed in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), as well as in domestic treaties. ID-SOV recognises that data is a strategic resource and provides a framework for the ethical use of data to advance collective Indigenous wellbeing and self-determination.5,6 In practice ID-Sov means that Indigenous Peoples need to be the decision-makers around how data about them are used.
Given that most Indigenous data is not in the possession of Indigenous Peoples, Indigenous data governance (ID-GOV) is seen as a key lever for addressing ID-SOV. ID-GOV harnesses Indigenous Peoples’ values, rights and interests to guide decision-making about how their data are collected, accessed, stored, and used.7 Enacting ID-GOV results in Indigenous control of Indigenous data through both internal Indigenous community data governance policies and practices and external stewardship of Indigenous data via mechanisms and frameworks that reflect Indigenous values.

text: Indigenous data sovereignty Indigenous Peoples have always been ‘data warriors’. Our ancient traditions recorded and protected information and knowledge through art, carving, song, chants and other practises. Deliberate efforts to expunge these knowledge systems were part and parcel of colonisation, along with state-imposed practices of counting and classifying Indigenous populations. As a result, Indigenous Peoples often encounter severe data deficits when trying to access high quality, culturally relevant data to pursue their goals, but an abundance of data that reflects and serves government interests regarding Indigenous Peoples and their lands. 
The concept of Indigenous data sovereignty (ID-SOV) is a relatively recent one, with the first major publication on the topic only appearing in 2016.1 ID-SOV is defined as the right of Indigenous Peoples to own, control, access and possess data that derive from them, and which pertain to their members, knowledge systems, customs or territories.2,3,4 ID-SOV is supported by Indigenous Peoples’ inherent rights of self-determination and governance over their peoples, territories and resources as affirmed in the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), as well as in domestic treaties. ID-SOV recognises that data is a strategic resource and provides a framework for the ethical use of data to advance collective Indigenous wellbeing and self-determination.5,6 In practice ID-Sov means that Indigenous Peoples need to be the decision-makers around how data about them are used.
Given that most Indigenous data is not in the possession of Indigenous Peoples, Indigenous data governance (ID-GOV) is seen as a key lever for addressing ID-SOV. ID-GOV harnesses Indigenous Peoples’ values, rights and interests to guide decision-making about how their data are collected, accessed, stored, and used.7 Enacting ID-GOV results in Indigenous control of Indigenous data through both internal Indigenous community data governance policies and practices and external stewardship of Indigenous data via mechanisms and frameworks that reflect Indigenous values.

year: 2020