It identifies the diversity, scale, geography and development trajectory of these initiatives, discusses the implications of these findings for efforts to achieve sustainable development, and identifies future research needs, to help harness the sustainability potential of these initiatives. This paper presents new empirical evidence from the first international study of the scope and character of community currencies. However, this international movement towards community-based ecological economic practices, is under-researched. These parallel systems of exchange (or community currencies) are designed to promote sustainable development by localising economic development, building social capital and substituting for material consumption, valuing work which is marginalised in conventional labour markets, and challenging the growth-based monetary system. Parallel sustainable monetary systems are being developed by civil society groups and non-governmental organisations (NGOs), informed by ecological economics perspectives on development, value, economic scale and growth, and responding to the unsustainability of current global financial systems. Our objective is to contribute to the social movements of co-production of social services and of time banking through designing and developing a socio-technical infrastructure that mutually leverages both to build up the core economy and to enable societal-scale time banking. As part of a requirements analysis for mobile timing banking infrastructures, we identified and analyzed co-production scenarios. Co-production is an important category of time banking interaction it has been identified as a key to strengthening the core economy of home, family, neighborhood and community, and is becoming integrated into government social service schemes. They can also be co-productions, in which the provider and recipient jointly enact a service, such as giving/receiving a guitar lesson. Contributions can be person-to-person services, such as driving another person to an appointment. Time banking facilitates generalized reciprocity among neighbors by rewarding contributions in proportion to the time entailed in contributing. The guiding vision is to develop more intelligent and context-aware systems to support on-the-fly service brokering that will greatly increase the scope and efficiency of acts of reciprocal altruism. It is based on past research and our own ongoing research conducted towards building a mobile app for timebanking. This paper highlights the possibilities for today's researchers and innovators to turbocharge community collaboration by developing the required technologies. This is partly due to a lack of adequate resources devoted towards setting up and running them and also to constraints in the design of the systems that they rely on to coordinate the transactions between community participants. These are known as as timebanks and community exchanges and have been around and increasing in number for quite some time, but they have grown only slowly in relation to the need for their services. Existing organizations, which are already pursuing the goal of leveraging untapped community potential, do exist. I fix your car, you do a neighbor's taxes, she designs my new kitchen, and so on. They hold the promise of breakthroughs in how people can collaborate through dynamically coordinated, efficient and reciprocal service transactions to improve the quality of life for all. These innovations represent a new frontier for transformative innovation on a societal level. In today's world of increasing scarcity of resources and economic stagnation, we still see rapid developments in computer science and user experience towards increasingly mobile, intelligent and context-aware computing systems. This research explores a similar paradigm for scientists and end-users that can be thought of as End-User Data Analytics (EUDA), or Transparent Machine Learning (TML). These EUD platforms enable people to focus on producing content rather than struggling with a development environment and new programming syntax or relying on disciplinary non-experts for essential technical help.
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The goal of this research is to empower a broader range of scientists and end-users to conduct data analytics by adopting the End-User Development (EUD) models commonly found in today's commercial software platforms like Microsoft Excel, Wikipedia and WordPress. However, data analytics requires significant programming knowledge or access to technical experts, while human computation requires in-depth knowledge of crowd management and is error-prone due to lack of scientific domain expertise. Advances in data analytics and human computation are transforming how researchers conduct science in domains like bioinformatics, computational social science, and digital humanities.
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