Presented by Karl M. Rich (with contributions from Jared Berends, Greg Cooper, Chisoni Mumba, Magda Rich, Helene Lie, Kanar Dizyee and Sirak Bahta) at a training course on systems thinking, participatory modelling and value chains, April 2020.
The document outlines the typical life cycle stages of a new business:
1) Invention - where opportunities are identified and intellectual property is protected.
2) Start-up - the most difficult stage to survive which requires a sound business plan.
3) Growth - where a business works to become profitable and compete in its market.
4) Maturity - when a stable business looks to expand or develop an exit strategy.
5) Harvest - the final stage where a business aims to profit from prior efforts or risks failure.
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
This document discusses descriptive, predictive, and prescriptive analytics techniques. It states that the goal of analytics is to obtain actionable insights that lead to smarter decisions and better business outcomes. Descriptive analytics examines past performance to understand reasons for success or failure. Predictive analytics uses statistical modeling and data mining to determine probable future outcomes. Prescriptive analytics synthesizes data and machine learning to suggest optimal decision options by anticipating future risks and opportunities along with the implications of various choices.
The document discusses various techniques for measuring attitudes and scaling responses, as presented by Pooja Luniya. It describes the components of attitudes, including the cognitive, affective, and behavioral aspects. Several important scaling techniques are covered, such as paired comparison scales, constant sum scales, rank order scales, Q-sort scales, graphic and itemized rating scales, Likert scales, semantic differential scales, and Stapel scales. These techniques are used to quantify opinions, preferences, and attitudes by assigning numbers or positions to responses.
The document discusses various aspects of research design. It defines research design and notes that it involves decisions about what, where, when, how much and by what means an inquiry will be conducted. It outlines requirements like identifying the type of research, being realistic and precise. Factors affecting research design are also discussed, like availability of data, time and resources. The main parts of research design are described as sampling design, observational design, statistical design and operational design. Different types of research designs are explained, including exploratory, descriptive, diagnostic and experimental designs. Key concepts in research design are also covered.
The document discusses business analytics and the role of a business analyst. It defines key terms like business analytics, data analytics, business intelligence, big data, data science, and data mining. It describes the skills required of a business analyst like understanding the business, basic statistics, Excel, and some analytics tools. The duties of a business analyst are to understand business problems and use data to help decision making. The document also lists some common business analyst job titles and roles.
This document discusses legal and ethical issues related to data sharing. It covers rights and copyright regarding data, how to address ethics when sharing personal data under GDPR, and obtaining consent from participants. Guidelines are provided for discovering and accessing shared data from repositories. Questions about data sharing are welcomed.
The document outlines the typical life cycle stages of a new business:
1) Invention - where opportunities are identified and intellectual property is protected.
2) Start-up - the most difficult stage to survive which requires a sound business plan.
3) Growth - where a business works to become profitable and compete in its market.
4) Maturity - when a stable business looks to expand or develop an exit strategy.
5) Harvest - the final stage where a business aims to profit from prior efforts or risks failure.
Analytics with Descriptive, Predictive and Prescriptive Techniquesleadershipsoil
This document discusses descriptive, predictive, and prescriptive analytics techniques. It states that the goal of analytics is to obtain actionable insights that lead to smarter decisions and better business outcomes. Descriptive analytics examines past performance to understand reasons for success or failure. Predictive analytics uses statistical modeling and data mining to determine probable future outcomes. Prescriptive analytics synthesizes data and machine learning to suggest optimal decision options by anticipating future risks and opportunities along with the implications of various choices.
The document discusses various techniques for measuring attitudes and scaling responses, as presented by Pooja Luniya. It describes the components of attitudes, including the cognitive, affective, and behavioral aspects. Several important scaling techniques are covered, such as paired comparison scales, constant sum scales, rank order scales, Q-sort scales, graphic and itemized rating scales, Likert scales, semantic differential scales, and Stapel scales. These techniques are used to quantify opinions, preferences, and attitudes by assigning numbers or positions to responses.
The document discusses various aspects of research design. It defines research design and notes that it involves decisions about what, where, when, how much and by what means an inquiry will be conducted. It outlines requirements like identifying the type of research, being realistic and precise. Factors affecting research design are also discussed, like availability of data, time and resources. The main parts of research design are described as sampling design, observational design, statistical design and operational design. Different types of research designs are explained, including exploratory, descriptive, diagnostic and experimental designs. Key concepts in research design are also covered.
The document discusses business analytics and the role of a business analyst. It defines key terms like business analytics, data analytics, business intelligence, big data, data science, and data mining. It describes the skills required of a business analyst like understanding the business, basic statistics, Excel, and some analytics tools. The duties of a business analyst are to understand business problems and use data to help decision making. The document also lists some common business analyst job titles and roles.
This document discusses legal and ethical issues related to data sharing. It covers rights and copyright regarding data, how to address ethics when sharing personal data under GDPR, and obtaining consent from participants. Guidelines are provided for discovering and accessing shared data from repositories. Questions about data sharing are welcomed.
- Univariate analysis refers to analyzing one variable at a time using statistical measures like proportions, percentages, means, medians, and modes to describe data.
- These measures provide a "snapshot" of a variable through tools like frequency tables and charts to understand patterns and the distribution of cases.
- Measures of central tendency like the mean, median and mode indicate typical or average values, while measures of dispersion like the standard deviation and range indicate how spread out or varied the data are around central values.
The document introduces Logical Framework Analysis (LFA), a methodology used for participatory project planning, implementation, and evaluation. It describes the key steps in LFA, including situation analysis, stakeholder analysis, problem analysis, objective analysis, strategy analysis, and developing a project planning matrix. The planning matrix outlines objectives, indicators, means of verification, and external assumptions. The document provides definitions for the different components of the LFA process and planning matrix.
The document discusses propositions and hypotheses. It defines a proposition as a statement that predicts a relationship between two or more variables, while a hypothesis describes a proposition that will be tested. Propositions form the basis of scientific research and are used to evaluate a study's internal validity. The document provides examples of propositions and explains that a hypothesis predicts observations in empirical data and must be falsifiable. It must include a null hypothesis of no relationship and state an association but not causation. Supported hypotheses may become accepted theories over time if repeatedly tested and not falsified.
The document discusses the importance of data for evidence-based policymaking, organizational development, detecting security issues, and improving business outcomes. It provides examples of how New Zealand Registry Services (NZRS) uses data for these purposes, including operating a national broadband map and open data portals. The document advocates for making more data openly available to enable reproducible research, more informed policy debates, and increased public trust.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
In many different types of researches we are interested in learning about large groups of people who all have something in common that is called 'target population' Researchers commonly study traits or characteristics (parameters) of populations in their studies. It is more or less impossible to study the whole population therefore researches need to select a sample or sub-group of the population that is likely to be representative of the target population. Therefore, the researcher would select individuals from which to collect the data which is called sample. Sampling is the method of selecting individuals from the population. The method of sampling is a key factor for generalizing the results of sample into a population. There are two main methods of sampling including probable and non-probable sampling techniques. In probable sampling method the sample, should be as representative as possible of the population which leads to more confident to generalize the results to the target population.
Another important question that must be answered in all sample surveys is "How many participants should be chosen for a survey"? An under-sized study can be a waste of resources since it may not produce useful results while an over-sized study uses more resources than necessary. Determining the sample size should be based on type of research and its objectives as well as required statistical methods. There are different methods for determining the sample size applying various formulas to calculate a sample size.
The document outlines a social and behavioral change communication strategy to improve nutrition in Ethiopia. The goal is to improve nutrition for women, children, and adolescent girls. Key objectives include improving dietary and feeding practices, increasing demand for nutrition services, and fostering gender-equitable behaviors. The strategy involves qualitative research, stakeholder input, and focuses on behavior change at the household and community levels through a "whole household" approach and clustering behaviors into pathways. Priority behaviors targeted include maternal nutrition practices like antenatal care and supplementation as well as infant and young child feeding.
The document discusses business analytics and decision making. It defines key concepts like data warehousing, data mining, business intelligence, descriptive analytics, predictive analytics, and prescriptive analytics. It explains how these concepts are used to extract insights from data to support decision making in organizations. Examples of how different types of analytics can be applied in a retail context are provided.
This document provides an overview of sampling methods for research. It defines key terms like universe, sample, and population. It explains that sampling involves studying a subset of a larger population due to limitations of time, resources, and feasibility of studying every member. The document outlines different sampling methods like simple random sampling, stratified sampling, and cluster sampling. It notes that sampling allows for time and cost savings while still providing accurate results. However, limitations include potential inaccuracies if not done scientifically and difficulty ensuring representativeness.
This document presents a strategic management presentation on corporate sustainability. It discusses key topics like corporate sustainability, the triple bottom line of economic, environmental and social impacts, stakeholder management, corporate governance, and corporate social responsibility. The presentation was delivered to a professor by three MBA students at CSJM University Kanpur. It provides an overview of these strategic management concepts as they relate to long-term sustainability.
Grand strategy [ strategic alternatives]Nawal Badu
1. The document discusses different generic strategies for achieving competitive advantage including cost leadership, differentiation, and focus. It outlines the key organizational requirements and skills needed to successfully implement each strategy.
2. Various strategic options for organizations are presented including market penetration, market development, product development, integration, diversification, turnaround, divestiture, and strategic alliances. Risks associated with each generic strategy are also summarized.
3. Guidelines are provided for when a focus strategy may be most appropriate, including when an industry is resistant to change and a firm has stable inputs and competitive advantages in production or distribution.
This document provides an overview of big data and machine learning strategies. It discusses the exponential growth in available data, increases in computing power, and advances in machine learning techniques. It classifies different types of alternative data sources and machine learning methods. The document aims to educate investors on applying big data and machine learning approaches to investing across different asset classes.
This document discusses various methods for collecting primary data, including surveys, interviews, telephone surveys, mail surveys, observation, and experiments. It provides details on each method, such as how surveys involve asking questions of respondents, interviews can be personal or focus groups, telephone surveys are conducted by phone, and mail surveys are done through postal mail. It also discusses challenges with each method like response rates for mail surveys and controlling external factors for experiments.
This document provides an introduction to biostatistics. It defines biostatistics as applying statistics to biology, medicine, and public health. Some key points covered include:
- Francis Galton is considered the father of biostatistics.
- There are two main types of data: primary data collected directly and secondary data collected previously.
- Variables can be qualitative (categorical) or quantitative (numeric).
- Biostatistics is applied in areas like medicine, public health, and research to analyze data and draw conclusions.
- Common sources of health data include censuses, vital records, surveys, and hospital/disease records.
The document discusses the basic postulates and levels of measurement in social research. It outlines 9 postulates for basic measurement, including identities, order, and additivity. It also explains Stevens' 4 levels of measurement - nominal, ordinal, interval, and ratio - and how they determine what statistical analyses can be done on different types of data based on the meaning of the values. Knowing the level of measurement is important for properly interpreting data and selecting appropriate analyses.
Designing Futures to Flourish: ISSS 2015 keynotePeter Jones
We now find ourselves as a systems thinking community inquiring into planetary governance for climate and ecological politics. The Anthropocene demands a planetary response, and yet we often find even our fellow travelers tethered to discourses of technological management, cultural change, and right action. We might now advocate a stronger role for social systems design as a process for continual engagement of citizen stakeholders, and between these citizens and policy makers, as advocated by Christakis, Ulrich and others. As we have seen power (economic and political) separate from its cultural histories, and become globalized, we may find ourselves in trajectories of action but with marginal power to effect societal outcomes.
We are faced with a dual mandate of restorative system design, recovering human needs in our communities, and policy system design, restoring the long historical arc toward democratic governance. And as these are both designable contexts, systemic design can integrate ecological, technological and design thinking to guide policy in more productive ways.
• We find ourselves captured in the politics of solutionism. Most presentations of the “problems” as stated before us reveal a trajectory of preferred solutions and their possible shortcomings.
• Climate change, even the entire Anthropocene aeonic perspective, represents a problematique of multiple effects systems. We are bound up in political discourses of “system change” and do not share a compelling common view of a flourishing world. We seem unable to reregister the most compelling societal choices and drivers save carbon mitigation.
• We have not conducted, to my knowledge, a substantial stakeholder discovery that extends beyond the immediate and obvious primary combatants in the climate change wars.
• As citizens and political actors on the planetary stage, we have been afraid or unable to present a clear view of the risk scenarios, possible governance strategies, or a normative plan for serious global investment. If the planet were a business concern, it would be in receivership by now.
- Univariate analysis refers to analyzing one variable at a time using statistical measures like proportions, percentages, means, medians, and modes to describe data.
- These measures provide a "snapshot" of a variable through tools like frequency tables and charts to understand patterns and the distribution of cases.
- Measures of central tendency like the mean, median and mode indicate typical or average values, while measures of dispersion like the standard deviation and range indicate how spread out or varied the data are around central values.
The document introduces Logical Framework Analysis (LFA), a methodology used for participatory project planning, implementation, and evaluation. It describes the key steps in LFA, including situation analysis, stakeholder analysis, problem analysis, objective analysis, strategy analysis, and developing a project planning matrix. The planning matrix outlines objectives, indicators, means of verification, and external assumptions. The document provides definitions for the different components of the LFA process and planning matrix.
The document discusses propositions and hypotheses. It defines a proposition as a statement that predicts a relationship between two or more variables, while a hypothesis describes a proposition that will be tested. Propositions form the basis of scientific research and are used to evaluate a study's internal validity. The document provides examples of propositions and explains that a hypothesis predicts observations in empirical data and must be falsifiable. It must include a null hypothesis of no relationship and state an association but not causation. Supported hypotheses may become accepted theories over time if repeatedly tested and not falsified.
The document discusses the importance of data for evidence-based policymaking, organizational development, detecting security issues, and improving business outcomes. It provides examples of how New Zealand Registry Services (NZRS) uses data for these purposes, including operating a national broadband map and open data portals. The document advocates for making more data openly available to enable reproducible research, more informed policy debates, and increased public trust.
DI&A Slides: Descriptive, Prescriptive, and Predictive AnalyticsDATAVERSITY
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets.
This webinar will compare and contrast these different data analysis activities and cover:
- Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis
- Descriptive Data Analytics – finding patterns
- Predictive Analytics – creating models of behavior
- Prescriptive Analytics – acting on insight
- How the analytic environment differs for each
In many different types of researches we are interested in learning about large groups of people who all have something in common that is called 'target population' Researchers commonly study traits or characteristics (parameters) of populations in their studies. It is more or less impossible to study the whole population therefore researches need to select a sample or sub-group of the population that is likely to be representative of the target population. Therefore, the researcher would select individuals from which to collect the data which is called sample. Sampling is the method of selecting individuals from the population. The method of sampling is a key factor for generalizing the results of sample into a population. There are two main methods of sampling including probable and non-probable sampling techniques. In probable sampling method the sample, should be as representative as possible of the population which leads to more confident to generalize the results to the target population.
Another important question that must be answered in all sample surveys is "How many participants should be chosen for a survey"? An under-sized study can be a waste of resources since it may not produce useful results while an over-sized study uses more resources than necessary. Determining the sample size should be based on type of research and its objectives as well as required statistical methods. There are different methods for determining the sample size applying various formulas to calculate a sample size.
The document outlines a social and behavioral change communication strategy to improve nutrition in Ethiopia. The goal is to improve nutrition for women, children, and adolescent girls. Key objectives include improving dietary and feeding practices, increasing demand for nutrition services, and fostering gender-equitable behaviors. The strategy involves qualitative research, stakeholder input, and focuses on behavior change at the household and community levels through a "whole household" approach and clustering behaviors into pathways. Priority behaviors targeted include maternal nutrition practices like antenatal care and supplementation as well as infant and young child feeding.
The document discusses business analytics and decision making. It defines key concepts like data warehousing, data mining, business intelligence, descriptive analytics, predictive analytics, and prescriptive analytics. It explains how these concepts are used to extract insights from data to support decision making in organizations. Examples of how different types of analytics can be applied in a retail context are provided.
This document provides an overview of sampling methods for research. It defines key terms like universe, sample, and population. It explains that sampling involves studying a subset of a larger population due to limitations of time, resources, and feasibility of studying every member. The document outlines different sampling methods like simple random sampling, stratified sampling, and cluster sampling. It notes that sampling allows for time and cost savings while still providing accurate results. However, limitations include potential inaccuracies if not done scientifically and difficulty ensuring representativeness.
This document presents a strategic management presentation on corporate sustainability. It discusses key topics like corporate sustainability, the triple bottom line of economic, environmental and social impacts, stakeholder management, corporate governance, and corporate social responsibility. The presentation was delivered to a professor by three MBA students at CSJM University Kanpur. It provides an overview of these strategic management concepts as they relate to long-term sustainability.
Grand strategy [ strategic alternatives]Nawal Badu
1. The document discusses different generic strategies for achieving competitive advantage including cost leadership, differentiation, and focus. It outlines the key organizational requirements and skills needed to successfully implement each strategy.
2. Various strategic options for organizations are presented including market penetration, market development, product development, integration, diversification, turnaround, divestiture, and strategic alliances. Risks associated with each generic strategy are also summarized.
3. Guidelines are provided for when a focus strategy may be most appropriate, including when an industry is resistant to change and a firm has stable inputs and competitive advantages in production or distribution.
This document provides an overview of big data and machine learning strategies. It discusses the exponential growth in available data, increases in computing power, and advances in machine learning techniques. It classifies different types of alternative data sources and machine learning methods. The document aims to educate investors on applying big data and machine learning approaches to investing across different asset classes.
This document discusses various methods for collecting primary data, including surveys, interviews, telephone surveys, mail surveys, observation, and experiments. It provides details on each method, such as how surveys involve asking questions of respondents, interviews can be personal or focus groups, telephone surveys are conducted by phone, and mail surveys are done through postal mail. It also discusses challenges with each method like response rates for mail surveys and controlling external factors for experiments.
This document provides an introduction to biostatistics. It defines biostatistics as applying statistics to biology, medicine, and public health. Some key points covered include:
- Francis Galton is considered the father of biostatistics.
- There are two main types of data: primary data collected directly and secondary data collected previously.
- Variables can be qualitative (categorical) or quantitative (numeric).
- Biostatistics is applied in areas like medicine, public health, and research to analyze data and draw conclusions.
- Common sources of health data include censuses, vital records, surveys, and hospital/disease records.
The document discusses the basic postulates and levels of measurement in social research. It outlines 9 postulates for basic measurement, including identities, order, and additivity. It also explains Stevens' 4 levels of measurement - nominal, ordinal, interval, and ratio - and how they determine what statistical analyses can be done on different types of data based on the meaning of the values. Knowing the level of measurement is important for properly interpreting data and selecting appropriate analyses.
Designing Futures to Flourish: ISSS 2015 keynotePeter Jones
We now find ourselves as a systems thinking community inquiring into planetary governance for climate and ecological politics. The Anthropocene demands a planetary response, and yet we often find even our fellow travelers tethered to discourses of technological management, cultural change, and right action. We might now advocate a stronger role for social systems design as a process for continual engagement of citizen stakeholders, and between these citizens and policy makers, as advocated by Christakis, Ulrich and others. As we have seen power (economic and political) separate from its cultural histories, and become globalized, we may find ourselves in trajectories of action but with marginal power to effect societal outcomes.
We are faced with a dual mandate of restorative system design, recovering human needs in our communities, and policy system design, restoring the long historical arc toward democratic governance. And as these are both designable contexts, systemic design can integrate ecological, technological and design thinking to guide policy in more productive ways.
• We find ourselves captured in the politics of solutionism. Most presentations of the “problems” as stated before us reveal a trajectory of preferred solutions and their possible shortcomings.
• Climate change, even the entire Anthropocene aeonic perspective, represents a problematique of multiple effects systems. We are bound up in political discourses of “system change” and do not share a compelling common view of a flourishing world. We seem unable to reregister the most compelling societal choices and drivers save carbon mitigation.
• We have not conducted, to my knowledge, a substantial stakeholder discovery that extends beyond the immediate and obvious primary combatants in the climate change wars.
• As citizens and political actors on the planetary stage, we have been afraid or unable to present a clear view of the risk scenarios, possible governance strategies, or a normative plan for serious global investment. If the planet were a business concern, it would be in receivership by now.
Generating Business Value with Business Process Management (BPM)Jan vom Brocke
1. The document discusses three stories related to engaging universities to continuously develop BPM capabilities.
2. The first story presents the BPM Billboard, a tool for effectively planning and scoping BPM initiatives.
3. The second story discusses the BPM Context Matrix, which accounts for diversity in processes and how to classify them into four clusters.
4. The third story examines how to turn process mining data into business value using a five-level framework analyzing the technical, individual, group, organizational, and ecosystem levels.
SC6 Workshop 1: Big Data Europe platform requirements and draft architecture:...BigData_Europe
Presentation by Martin Kaltenböck, Semantic Web Company, at the first workshop of Societal Challlenge 6 in the BigDataEurope project, taking place in Luxembourg on 18 November 2015.
http://www.big-data-europe.eu/social-sciences/
This document discusses open social mapping, which combines actor modeling, social network analysis, crowdsourcing, and customer relationship management tools to allow stakeholders to map themselves. This helps designers understand social systems from the perspectives of real stakeholders. Benefits include centering stakeholders, identifying disconnects, increasing understanding of diversity, and facilitating shared understanding between stakeholders. Challenges include maintaining participation, addressing privacy concerns, and ensuring interoperability between maps. Examples of open social mapping projects in Canada are provided.
Implementation of spatial group model building sessionsILRI
for
annotations
Layers: to organize
different data layers
History: to track
changes
Source: https://vecta.io
In the SGMB session, participants can then collaboratively add
data layers, reference modes, and annotations using the
drawing tools.
The facilitator should guide the process and ensure all
contributions are captured.
Time allocation: 90-120 minutes
34
Group exercises (3)
Agendas and planning
Hopes-and-fears
Motivating systems thinking
Layerstack
Problem identification/prioritization
Causes and consequences
Facilitation of a concept module
Source: "Man Working on Laptop Cartoon.svg" by V
2021006 jim spohrer mc gill_precision_convergence_panel v3ISSIP
Jim Spohrer served as a panelist for a webinar on global value chain resilience hosted by Gary Gereffi. Spohrer is on the board of ISSIP.org and contributes to the Linux Foundation AI and Data Foundation. He retired from IBM in 2021 after a career in speech recognition, service science research, and open source AI. Spohrer posed questions on how trust and resilience are related in global value chains and how artificial intelligence and digital services may impact resilience.
Muki Haklay (UCL) Mapping For Sustainable Communities 170608Muki Haklay
- The document discusses a seminar that aims to foster collaboration between academics, practitioners, and communities on participatory mapping and GIS research in the UK.
- It will involve sharing learning from previous mapping projects, discussing concepts of participatory mapping, and showcasing community projects.
- One session will discuss the philosophy of technology as it relates to participatory GIS, and how GIS could be "rewired" to better incorporate local knowledge and public participation.
This document discusses current themes and trends in data-centric architecture. It identifies several inhibitors to widespread data sharing across organizations, including data feudalism and regulatory challenges. Emerging opportunities include using semantic standards and knowledge graphs to enable digital twins and autonomous agents through interoperable data collaboration. Adopting decentralized architectures and federated storage models can further break down data silos. However, widespread adoption faces obstacles including organizations needing to become truly data-centric first.
The document summarizes Jim Spohrer's presentation on service provision and technology in service systems from a service science perspective. Some key points:
- Better models are needed to understand the increasingly complex and interconnected world from various perspectives including physical, social, virtual, organizational, and technological.
- Human-centered design should evolve to humanity-centered design by focusing on entire ecosystems of people, living things, and the environment with a long-term systems view.
- Value co-creation is accelerated when large numbers of skilled people with advanced technology have a safe, ethical, and sustainable environment for interaction and change.
- Upskilling is moving from individual skills to skills extended with AI tools across knowledge areas
Presenting a new, clear approach to defining neogeography and its various elements, understanding the stakeholders in VGI and researching how volunteered information may benefit users over and above traditional cartography.
A Socio-Technical Design Approach to Build Crowdsourced and Volunteered Geogr...José Pablo Gómez Barrón S.
Ph.D. dissertation defence at Technical University of Madrid (UPM).
A Socio-Technical Design Approach to Build Crowdsourced and Volunteered Geographic Information Systems (VGIS) Leveraging the Crowds and Participatory Communities for Geoinformation Management.
Jim Spohrer was invited to be a panelist for John Hagel's presentation at the Fall 2021 Berkeley Innovation Forum. Spohrer recommends the book "Humankind: A Hopeful History" by Rutger Bregman. He notes his experience at IBM of facing fears of product to service and proprietary to open source transformations, which led IBM to acquire Red Hat for $34B and spin off Kyndryl. Spohrer serves on the board of ISSIP.org and is a retired IBM executive focusing his studies on service science and open source AI, where trust is key.
David Coleman: Challenging Traditional Models, Roles and Responsibilities in ...GSDI Association
GSDI President, Dr David Coleman's presentation at the Joint International Conference onGeospatial Theory, Processing Modeling and ApplicationsToronto, 6 October 2014.
Implementing Sustainable Digital Preservationneilgrindley
There has been a lot of investment and activity in digital preservation over the last decade and a lot of it has been supported by grant funded activity and research projects. The ‘learn by doing’ approach and the prodigious number of beta systems and project reports have all played their part in helping to mature the digital preservation field - and judging by the changing tone of conferences over the years, the community has come a long way. So far - in fact - that a lot of organisations are now at the stage when theory is less important than action. They need to work out the best implementation paths and make procurement choices.
So the economic landscape for digital preservation has shifted and the onus is now on many organisations to look closely at their needs and their objectives and to make investment choices that are sustainable as part of the business needs of their organisation rather than as an adjunct activity that is supported by ‘soft’ research money. Work being taken forward by the 4C Project is looking at providing resources to support organisations to make sustainable digital preservation investment choices and this webinar will describe some of that work.
But budgets are hard to secure and digital preservation remains a difficult case to argue so collaboration with like-minded organisations and the establishment of shared services should support the arguments and drive down the cost. This is one of the core messages that underpins the Aligning National Approaches to Digital Preservation (ANADP) initiative and this will also be described and explained during the webinar.
Dr. Katherine Skinner is the Executive Director of the Educopia Institute, a not-for-profit educational organization that builds networks and collaborative communities to help cultural, scientific, and scholarly institutions achieve greater impact. Dr. Skinner, who has a doctorate from Emory University, has co-edited three books and co-authored the landmark “Guidelines for Digital Newspaper Preservation Readiness” with Matt Schultz.
This presentation has a focus on taking a broad perspective on current challenges in digital preservation and on collaborative efforts to address them.
The document discusses the history and future of AI at IBM, from its early work with Nathan Rochester on physical symbol systems to its current focus on open source technologies and cognitive systems through its Center for Open Source Data and AI Technologies (CODAIT). It also covers IBM's view of service science as the study of evolving service system entities, their capabilities, constraints, rights, and responsibilities. The document provides context around IBM's past, present and future work in AI and how it relates to fields like computer science, chemistry, biology and service science.
Similar to Principles of group model building and spatial group model building (20)
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...ILRI
Presentation by Guy Ilboudo, Abel Sènabgè Biguezoton, Cheick Abou Kounta Sidibé, Modou Moustapha Lo, Zoë Campbell and Michel Dione at the 6th Peste des Petits Ruminants Global Research and Expertise Networks (PPR-GREN) annual meeting, Bengaluru, India, 28–30 November 2023.
Small ruminant keepers’ knowledge, attitudes and practices towards peste des ...ILRI
Poster by Guy Ilboudo, Abel Sènabgè Biguezoton, Cheick Abou Kounta Sidibé, Modou Moustapha Lo, Zoë Campbell and Michel Dione presented at the 6th Peste des Petits Ruminants Global Research and Expertise Networks (PPR-GREN) annual meeting, Bengaluru, India, 29 November 2023.
A training, certification and marketing scheme for informal dairy vendors in ...ILRI
Presentation by Silvia Alonso, Jef L. Leroy, Emmanuel Muunda, Moira Donahue Angel, Emily Kilonzi, Giordano Palloni, Gideon Kiarie, Paula Dominguez-Salas and Delia Grace at the Micronutrient Forum 6th Global Conference, The Hague, Netherlands, 16 October 2023.
Milk safety and child nutrition impacts of the MoreMilk training, certificati...ILRI
Poster by Silvia Alonso, Emmanuel Muunda, Moira Donahue Angel, Emily Kilonzi, Giordano Palloni, Gideon Kiarie, Paula Dominguez-Salas, Delia Grace and Jef L. Leroy presented at the Micronutrient Forum 6th Global Conference, The Hague, Netherlands, 16 October 2023.
Preventing the next pandemic: a 12-slide primer on emerging zoonotic diseasesILRI
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help boost feelings of calmness, happiness and focus.
Preventing preventable diseases: a 12-slide primer on foodborne diseaseILRI
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like anxiety and depression.
Preventing a post-antibiotic era: a 12-slide primer on antimicrobial resistanceILRI
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help enhance one's emotional well-being and mental clarity.
Food safety research in low- and middle-income countriesILRI
Presentation by Hung Nguyen-Viet at the first technical meeting to launch the Food Safety Working Group under the One Health Partnership framework, Hanoi, Vietnam, 28 September 2023
The Food Safety Working Group (FSWG) in Vietnam was created in 2015 at the request of the Deputy Prime Minister to address food safety issues in the country. It brings together government agencies, ministries, and development partners to facilitate joint policy dialogue and improve food safety. Over eight years of operations led by different organizations, the FSWG has contributed to various initiatives. However, it faces challenges of diminished government participation over time and dependence on active members. Going forward, it will strengthen its operations by integrating under Vietnam's One Health Partnership framework to better engage stakeholders and achieve policy impacts.
Reservoirs of pathogenic Leptospira species in UgandaILRI
Presentation by Lordrick Alinaitwe, Martin Wainaina, Salome Dürr, Clovice Kankya, Velma Kivali, James Bugeza, Martin Richter, Kristina Roesel, Annie Cook and Anne Mayer-Scholl at the University of Bern Graduate School for Cellular and Biomedical Sciences Symposium, Bern, Switzerland, 29 June 2023.
Assessing meat microbiological safety and associated handling practices in bu...ILRI
Presentation by Patricia Koech, Winnie Ogutu, Linnet Ochieng, Delia Grace, George Gitao, Lily Bebora, Max Korir, Florence Mutua and Arshnee Moodley at the 8th All Africa Conference on Animal Agriculture, Gaborone, Botswana, 26–29 September 2023.
Ecological factors associated with abundance and distribution of mosquito vec...ILRI
Poster by Max Korir, Joel Lutomiah and Bernard Bett presented the 8th All Africa Conference on Animal Agriculture, Gaborone, Botswana, 26–29 September 2023.
Practices and drivers of antibiotic use in Kenyan smallholder dairy farmsILRI
Poster by Lydiah Kisoo, Dishon M. Muloi, Walter Oguta, Daisy Ronoh, Lynn Kirwa, James Akoko, Eric Fèvre, Arshnee Moodley and Lillian Wambua presented at Tropentag 2023, Berlin, Germany, 20–22 September 2023.
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
Anti-Universe And Emergent Gravity and the Dark UniverseSérgio Sacani
Recent theoretical progress indicates that spacetime and gravity emerge together from the entanglement structure of an underlying microscopic theory. These ideas are best understood in Anti-de Sitter space, where they rely on the area law for entanglement entropy. The extension to de Sitter space requires taking into account the entropy and temperature associated with the cosmological horizon. Using insights from string theory, black hole physics and quantum information theory we argue that the positive dark energy leads to a thermal volume law contribution to the entropy that overtakes the area law precisely at the cosmological horizon. Due to the competition between area and volume law entanglement the microscopic de Sitter states do not thermalise at sub-Hubble scales: they exhibit memory effects in the form of an entropy displacement caused by matter. The emergent laws of gravity contain an additional ‘dark’ gravitational force describing the ‘elastic’ response due to the entropy displacement. We derive an estimate of the strength of this extra force in terms of the baryonic mass, Newton’s constant and the Hubble acceleration scale a0 = cH0, and provide evidence for the fact that this additional ‘dark gravity force’ explains the observed phenomena in galaxies and clusters currently attributed to dark matter.
Compositions of iron-meteorite parent bodies constrainthe structure of the pr...Sérgio Sacani
Magmatic iron-meteorite parent bodies are the earliest planetesimals in the Solar System,and they preserve information about conditions and planet-forming processes in thesolar nebula. In this study, we include comprehensive elemental compositions andfractional-crystallization modeling for iron meteorites from the cores of five differenti-ated asteroids from the inner Solar System. Together with previous results of metalliccores from the outer Solar System, we conclude that asteroidal cores from the outerSolar System have smaller sizes, elevated siderophile-element abundances, and simplercrystallization processes than those from the inner Solar System. These differences arerelated to the formation locations of the parent asteroids because the solar protoplane-tary disk varied in redox conditions, elemental distributions, and dynamics at differentheliocentric distances. Using highly siderophile-element data from iron meteorites, wereconstruct the distribution of calcium-aluminum-rich inclusions (CAIs) across theprotoplanetary disk within the first million years of Solar-System history. CAIs, the firstsolids to condense in the Solar System, formed close to the Sun. They were, however,concentrated within the outer disk and depleted within the inner disk. Future modelsof the structure and evolution of the protoplanetary disk should account for this dis-tribution pattern of CAIs.
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆Sérgio Sacani
Context. The early-type galaxy SDSS J133519.91+072807.4 (hereafter SDSS1335+0728), which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). This variability behaviour, coupled with the host-galaxy properties, suggests that SDSS1335+0728 hosts a ∼ 106M⊙ black hole (BH) that is currently in the process of ‘turning on’. Aims. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. Methods. We used archival photometry (from WISE, 2MASS, SDSS, GALEX, eROSITA) and spectroscopic data (from SDSS and LAMOST) to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift, SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We analysed the variability of SDSS1335+0728 in the X-ray/UV/optical/mid-infrared range, modelled its spectral energy distribution prior to and after December 2019, and studied the evolution of its UV/optical spectra. Results. From our multi-wavelength photometric analysis, we find that: (a) since 2021, the UV flux (from Swift/UVOT observations) is four times brighter than the flux reported by GALEX in 2004; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1−W2 WISE colour has become redder; and (c) since February 2024, the source has begun showing X-ray emission. From our spectroscopic follow-up, we see that (i) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (ii) broad emission lines are not detected; and (iii) the [OIII] line increased its flux ∼ 3.6 years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. Conclusions. We conclude that the variations observed in SDSS1335+0728 could be either explained by a ∼ 106M⊙ AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGNobserved in the process of activating. If the latter were found to be the case, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour. Key words. galaxies: active– accretion, accretion discs– galaxies: individual: SDSS J133519.91+072807.4
BIRDS DIVERSITY OF SOOTEA BISWANATH ASSAM.ppt.pptxgoluk9330
Ahota Beel, nestled in Sootea Biswanath Assam , is celebrated for its extraordinary diversity of bird species. This wetland sanctuary supports a myriad of avian residents and migrants alike. Visitors can admire the elegant flights of migratory species such as the Northern Pintail and Eurasian Wigeon, alongside resident birds including the Asian Openbill and Pheasant-tailed Jacana. With its tranquil scenery and varied habitats, Ahota Beel offers a perfect haven for birdwatchers to appreciate and study the vibrant birdlife that thrives in this natural refuge.
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...Sérgio Sacani
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
This presentation offers a general idea of the structure of seed, seed production, management of seeds and its allied technologies. It also offers the concept of gene erosion and the practices used to control it. Nursery and gardening have been widely explored along with their importance in the related domain.
Discovery of Merging Twin Quasars at z=6.05Sérgio Sacani
We report the discovery of two quasars at a redshift of z = 6.05 in the process of merging. They were
serendipitously discovered from the deep multiband imaging data collected by the Hyper Suprime-Cam (HSC)
Subaru Strategic Program survey. The quasars, HSC J121503.42−014858.7 (C1) and HSC J121503.55−014859.3
(C2), both have luminous (>1043 erg s−1
) Lyα emission with a clear broad component (full width at half
maximum >1000 km s−1
). The rest-frame ultraviolet (UV) absolute magnitudes are M1450 = − 23.106 ± 0.017
(C1) and −22.662 ± 0.024 (C2). Our crude estimates of the black hole masses provide log 8.1 0. ( ) M M BH = 3
in both sources. The two quasars are separated by 12 kpc in projected proper distance, bridged by a structure in the
rest-UV light suggesting that they are undergoing a merger. This pair is one of the most distant merging quasars
reported to date, providing crucial insight into galaxy and black hole build-up in the hierarchical structure
formation scenario. A companion paper will present the gas and dust properties captured by Atacama Large
Millimeter/submillimeter Array observations, which provide additional evidence for and detailed measurements of
the merger, and also demonstrate that the two sources are not gravitationally lensed images of a single quasar.
Unified Astronomy Thesaurus concepts: Double quasars (406); Quasars (1319); Reionization (1383); High-redshift
galaxies (734); Active galactic nuclei (16); Galaxy mergers (608); Supermassive black holes (1663)
The Limited Role of the Streaming Instability during Moon and Exomoon FormationSérgio Sacani
It is generally accepted that the Moon accreted from the disk formed by an impact between the proto-Earth and
impactor, but its details are highly debated. Some models suggest that a Mars-sized impactor formed a silicate
melt-rich (vapor-poor) disk around Earth, whereas other models suggest that a highly energetic impact produced a
silicate vapor-rich disk. Such a vapor-rich disk, however, may not be suitable for the Moon formation, because
moonlets, building blocks of the Moon, of 100 m–100 km in radius may experience strong gas drag and fall onto
Earth on a short timescale, failing to grow further. This problem may be avoided if large moonlets (?100 km)
form very quickly by streaming instability, which is a process to concentrate particles enough to cause gravitational
collapse and rapid formation of planetesimals or moonlets. Here, we investigate the effect of the streaming
instability in the Moon-forming disk for the first time and find that this instability can quickly form ∼100 km-sized
moonlets. However, these moonlets are not large enough to avoid strong drag, and they still fall onto Earth quickly.
This suggests that the vapor-rich disks may not form the large Moon, and therefore the models that produce vaporpoor disks are supported. This result is applicable to general impact-induced moon-forming disks, supporting the
previous suggestion that small planets (<1.6 R⊕) are good candidates to host large moons because their impactinduced disks would likely be vapor-poor. We find a limited role of streaming instability in satellite formation in an
impact-induced disk, whereas it plays a key role during planet formation.
Unified Astronomy Thesaurus concepts: Earth-moon system (436)
Discovery of An Apparent Red, High-Velocity Type Ia Supernova at 𝐳 = 2.9 wi...Sérgio Sacani
We present the JWST discovery of SN 2023adsy, a transient object located in a host galaxy JADES-GS
+
53.13485
−
27.82088
with a host spectroscopic redshift of
2.903
±
0.007
. The transient was identified in deep James Webb Space Telescope (JWST)/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Photometric and spectroscopic followup with NIRCam and NIRSpec, respectively, confirm the redshift and yield UV-NIR light-curve, NIR color, and spectroscopic information all consistent with a Type Ia classification. Despite its classification as a likely SN Ia, SN 2023adsy is both fairly red (
�
(
�
−
�
)
∼
0.9
) despite a host galaxy with low-extinction and has a high Ca II velocity (
19
,
000
±
2
,
000
km/s) compared to the general population of SNe Ia. While these characteristics are consistent with some Ca-rich SNe Ia, particularly SN 2016hnk, SN 2023adsy is intrinsically brighter than the low-
�
Ca-rich population. Although such an object is too red for any low-
�
cosmological sample, we apply a fiducial standardization approach to SN 2023adsy and find that the SN 2023adsy luminosity distance measurement is in excellent agreement (
≲
1
�
) with
Λ
CDM. Therefore unlike low-
�
Ca-rich SNe Ia, SN 2023adsy is standardizable and gives no indication that SN Ia standardized luminosities change significantly with redshift. A larger sample of distant SNe Ia is required to determine if SN Ia population characteristics at high-
�
truly diverge from their low-
�
counterparts, and to confirm that standardized luminosities nevertheless remain constant with redshift.
TOPIC OF DISCUSSION: CENTRIFUGATION SLIDESHARE.pptxshubhijain836
Centrifugation is a powerful technique used in laboratories to separate components of a heterogeneous mixture based on their density. This process utilizes centrifugal force to rapidly spin samples, causing denser particles to migrate outward more quickly than lighter ones. As a result, distinct layers form within the sample tube, allowing for easy isolation and purification of target substances.
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...
Principles of group model building and spatial group model building
1. Principles of group model building and
spatial group model building
Better lives through livestock
O
K
A
PiS
Training course on Systems Thinking, Participatory Modeling, and Value Chains
Materials prepared and presented by Karl M. Rich (with contributions from Jared Berends, Greg Cooper, Chisoni Mumba,
Magda Rich, Helene Lie, Kanar Dizyee, and Sirak Bahta)
Foresight Modeling & Policy Team, Policies, Institutions, and Livelihoods
International Livestock Research Institute (ILRI)
Version April 2020 (draft)
2. 2
Outline
Overview of group model building (and its cousin, mediated
modeling)
Spatial group model building – how it extends GMB and how it’s
different
Examples
• Urban agriculture (NZ)
• East coast fever (Zambia)
• Value chain upgrading - pigs (Myanmar)
• Aggregation systems in horticulture (Bihar)
qualitative
quantitative
3. 3
Session goals
An emerging understanding of (spatial) group model
building and why we use it
An appreciation of the potential of participatory
processes based on previous work
A desire to learn more on implementing SGMB in
practice!
Picture credit: K.M. Rich 2012 (Maroantsetra, Madagascar)
4. 4
Overview
SD models, given their graphical and intuitive nature, can
be developed in collaboration with a variety of groups
Group model building (GMB) is one way to both obtain
information and parameterize relationships that exist in
the system in question.
5. 5
What is group model building?
Group Model Building or GMB
“focuses on building system
dynamics models with teams in
order to enhance team learning, to
foster consensus and to create
commitment with a resulting
decision.”
Source: Vennix (1996)
Picture credit: K.M. Rich 2019 (Myeik, Myanmar)
6. 6
What is group model building?
A participatory process aimed at:
• Identifying and prioritizing the key problems in the system
• The causes of these problems
• The consequences of these problems
• Feedbacks between consequences and causes
• Development of models from these sessions (qualitative or
quantitative)
Use of SD principles and language (stocks/flows/feedbacks)
to facilitate this discussion.
Involvement of stakeholders in the model building process to
increase the effectiveness and ownership of the final
product
Source:
https://commons.wikimedia.org/wiki/File:Kelly%27s_Kin
dergarten_(1898-11-27).jpg, Public Domain
7. 7
GMB and participatory modeling
GMB is not the only type of participatory modeling
technique that uses systems thinking/dynamics tools.
Mediated modeling (van den Belt 2004) is a similar
concept – it involves a wider range of stakeholders in the
process of model building, rather than a smaller client
group (Antunes et al. 2006).
Mediated modeling has been used primarily in
environmental applications.
8. 8
Why GMB?
Messy problems: Problems are usually complex
and not easily defined.
In complex problems, individuals have a limited
(or narrow) view of the problem (silo thinking).
Our mental models are limited by our individual
ability to process information: role of groups
Difficulties in identifying multiple causes of
complex problems their interconnections
Source: Vennix (1996)
Picture credit: S.Bahta 2019 (New Delhi, India)
14. 14
Client
group has
problem
Is SD
appropriate?
Use
preliminary
model?
Yes
No
Use something
else
Questions to consider:
• Is problem dynamic?
• Short vs. long term effects
• Reference mode of behavior
• Qualitative or quantitative
• Who to involve?
Yes: model based on:
No: start from scratch
Informal
interviews
GMB sessions
Conclusions
Interviews
Documents
Questionnaires/
Workbooks
Source: Adapted from Vennix (1996), figure 4.1, p. 103
Note: questionnaires
both inform and
triangulate our GMB
sessions
A way to “short-cut” the process if time or
resources are scarce, but can reduce ownership
of model and power of participatory process
(Vennix 1996)
15. 15
GMB design issues
• Small (5-12) or large (12+) group?
• Type of participants - homogenous vs
heterogeneous groups?
• Level of model complexity needed: problem
conceptualization vs. full model
development with clients/stakeholders?
Picture credit: K.M. Rich 2019 (Jessore, Bangladesh)
16. 16
Limitations of conventional GMB (1)
Lack of use of value chain/natural resource/LDC settings
(an exception: Lie Ph.D., see Lie and Rich 2016)
Issues of comparability/replication (Scott et al. 2016)
Issues of scaling across contexts
17. 17
Limitations of conventional GMB (2)
GMB sessions do not focus on spatial dynamics
However, the processes that generate change within
systems could have important spatial dimensions
(land use, population dynamics, etc.)
The “where” of the system matters as much as the
“what”, “how”, and “why” Picture credit: Ingrid Kallick (http://www.ikallick.com)
/ Public domain; source
https://upload.wikimedia.org/wikipedia/commons/2/
23/SphericalCow2.gif
18. 18
Spatial group model building: GMB with spatial attributes
Key characteristics
• Grounding problems, causes, and
consequences spatially
• Identifying spatial and temporal changes and
their co-evolution
• Using maps and GIS concepts to facilitate
model and system building through physical
platforms such as LayerStack (and eLayerstack
using Vecta) or other related tools
Picture credit: K.M. Rich 2016 (Lincoln, New Zealand)
19. 19
Spatial group model building: toolkits (1)
LayerStack: an offline, participatory GIS-type facilitation platform (funded by KiwiNet)
Use of plastic acetates as data layers (land use, VC actors, climate, disease patterns,
production characteristics) over a map
Use of variety of consumables (stickers, markers) to denote physical location and
temporal/spatial movement
Improves visualization of system and facilitation of model development
Simple, low-tech, hands-on, easy to store information
22. 22
Spatial group model building: toolkits (2)
“Necessity is the mother of all innovation”
COVID-19 has made face-to-face participatory
processes challenging
“eLayerstack” – an online means of conducting
SGMB with groups online using the web-based
Vecta platform (http://vecta.io)
Same principles of layers and consumables to
“draw” on base maps, but in real-time with
stakeholders
Picture credit: K.M. Rich 2020 (online snapshot)
23. 23
Spatial group model building
Process for model development outlined in Rich,
Rich, and Dizyee (2018)
Eight-step process, but flexible depending on use
for qualitative or quantitative modelling.
In the next presentation, we will demonstrate
how we implement in practice (offline and
online).
Picture credit: K.M. Rich 2019 (Dakar, Senegal)
30. 30
Spatial group model building: process (6)
Source: Rich, Rich, and Dizyee (2018)
Note: spatial co-evolution of models remains an important area of
future research; we’re not there yet, but hope to go in that
direction
31. 31
Example #1: urban agriculture (UA) in Christchurch, NZ
UA has a long tradition in Christchurch (WWII,
Vegetable Campaigns)
Since the earthquakes in 2010 and 2011, Christchurch
has experienced a revival in UA
More complex situation:
High prices of fresh produce
Psychological and emotional impact of the
earthquake
UA as a way to reconnect with the city
Divergence between planners and practitioners: role of
SGMB to articulate key spatial issues and leverage
points
Picture credit: M. Rich 2017 (Christchurch, New Zealand)
36. Production
Number of
market outlets
O1 O14
P1 P12
L1 L9
PO1 PO10
Land for urban
agriculture
Population
LEGEND
IN THE MODEL IN THE MAP
Profits
Demand
Distance to market
-
Growth rate of
market outlets
-
Factors to promote
awareness in UA
+
Actual UA
participants
Number of
market outlets
+
Selling to
consumers
+
+
Community &
consumer awareness
of UA
+
+
Production
Land for urban
agriculture
+
+
+
+
+
+
Population
+
+
Production
Number of
market outlets
O11
O11
O12
O1 O14
P4
P5
P6
P7
P8
P1 P12
L4
L5
L6
L7
L1 L9
PO1 PO10
Land for urban
agriculture
Population
LEGEND
IN THE MODEL IN THE MAP
Profits
Demand
Distance to market
-
Growth rate of
market outlets
-
Factors to promote
awareness in UA
+
Actual UA
participants
Number of
market outlets
+
Selling to
consumers
+
+
Community &
consumer awareness
of UA
+
+
Production
Land for urban
agriculture
+
+
+
+
+
+
Population
+
+
Source: Rich, Rich, and Dizyee (2018)
37. 37
Urban agriculture in Christchurch: insights
Spatial dimension of UA in Christchurch
extremely important – land use patterns vs.
population movement patterns.
An opportunity: How to bring UA products from
producers to consumers?
Model remained qualitative – not parameterized
quantitatively
Picture credit: M. Rich 2017 (Christchurch, New Zealand)
38. 38
Example #2: East coast fever in Zambia
ECF – an important livestock disease in East Africa,
including Zambia.
Recent field work (Mumba 2018) highlighted
importance of ECF relative to other government
priorities (e.g. FMD)
Little known about drivers/context of control and how
this differs across space.
How to identify and quantify impact of interventions
that would both improve communal involvement in the
chain and reduce disease?
First “live” test of Layerstack and (qualitative) SGMB in
the field
Picture credit: K.M. Rich 2016 (Monze, Zambia)
43. 43
East coast fever in Zambia: insights
Drivers of ECF have distinct spatial patterns
• Competition between land
• Market differences (external – Lundazi vs. local –
Monze)
• Cultural norms against mixing animals at dip
tanks based on social status/class
• Variations in herding practices
Spatial differences highlight the need for
developing locally relevant, fit-for-purpose control
strategies.
Picture credit: K.M. Rich 2016 (Monze, Zambia)
44. 44
Example #3: upgrading pig value chains in Myanmar
Project at a glance…
Focus: Pro-poor interventions to upgrade pork and rice value chains in Tanintharyi
region, Myanmar
Duration: 5 years, from November 2017 to October 2022
Client: MFAT, Partnership for International Development (PfID) fund
Contract value: NZ$4.1 million.
Partners
World Vision (WV): Contract holder, personnel, resources and logistical support for
project implementation and monitoring
Vision Fund (VF): Micro-finance for households and farmers, new financial products to co-
finance value-adding ventures
Lincoln University & ILRI: Value chain research and design, steer project implementation
and monitoring, impact assessment
Source: Slide courtesy of Berends and Esnard (2020)
45. 45
Process
Three field visits to Myanmar:
• Five pig SGMB workshops (avg. 13
participants and 50% female) with
farmers, brokers, slaughterhouse
owners, and wholesalers
• Five rice SGMB workshops (avg. 14
participants and 40% female) with
paddy farmers, millers, wholesalers
• Six Reference Group workshops (avg. 6
participants) with government officers,
NGO staff, and lead farmers
• Two Project Advisory Committee(PAC)
meetings to review results and decide
on interventions
Source: Slide courtesy of Berends and Esnard (2020)
46. 46
Tools and outputs: Layerstack for VC dynamics
•
•
•HHHH
•
•
•
•
•
•
•HHHH
•
•
•
•
Layer 2: Input, service and product
flows in the pig value chain
Layer 1: Livelihood zones
Source: Slide courtesy of Berends and Esnard (2020); picture credit J. Berends (2019)
47. 47
Tools and outputs: causes and consequences
• Value chain problems prioritised and then explored by developing reference nodes, and cause and consequence maps
• Goal of identifying causal relationships that determine dynamic behaviours in the chain
Source: Slide courtesy of Berends and Esnard (2020); picture credit J. Berends (2019)
48. 48
Tools and outputs: concept model
• Based on common themes and critical feedback loops from cause and consequence mapping, develop concept model
that contains feedback loops and structure which determine dynamic behaviour in the chain
Source: slide courtesy of Berends and Esnard (2020); picture credit J. Berends (2019)
49. 49
Tools and outputs: modules for scenario analysis
• Concept model then divided into
modules
• Each module structure is further
developed in Stella Architect (SD
software package) and
parametrised
• Modules are then connected
through material flows and
information flows to form a
functioning baseline model
Source: Slide courtesy of Berends and Esnard (2020)
50. 50
Tools and outputs: scenarios
Model scenarios
• Baseline: No project interventions
• Scenario 1: Project interventions cover all
pig producers in target villages
• Scenario 2: Project establishes Producer
Groups (PGs) and targets PG members for
interventions
• Scenario 3: PGs are upgraded to Producer
Organizations (POs) with the institutional
arrangements to support ongoing capacity
investments
Interventions (within scenarios)
• Microfinance loans
• Good Animal Husbandry Practices (Animal
Health Workers and biosecurity)
• Training on hybrid pig production and
commercial pig feed
• Artificial insemination
• Combination of interventions
Source: Slide courtesy of Berends and Esnard (2020)
51. 51
Key findings
Source: Slide courtesy of Berends and Esnard (2020); photo credit J. Berends (2019)
• Establish PGs with a mix of hybrid Farrow-to-Finish (high profits) and Wean-to-Finish (moderate profits) farming systems that can
collectively supply slaughterhouses with a consistent high-quality fattener
• To sustain investments in hybrid breeds a rank order for project interventions is
recommended:
1. Improved credit facilities (high priority)
2. Good Animal Husbandry Practices (high priority)
3. Training and the introduction of commercial pig feed (medium priority)
4. Artificial insemination (low priority)
• Interaction effects: individual activities are negative or barely positive but 1+2+3 = 47% increase in profits
• Focus on functional PGs: Institutional arrangements that reward small-scale farmers in proportion to their patronage and investment
delivered higher reinvestment in PGs and larger profits for members
• Co-investment between PG/PO members and a strategic partner in a hygienic slaughterhouse facility is a high-impact intervention that
widens and deepens the medium and long-term results of the project.
• Potential negative impacts for smaller farmers if disease outbreak occurs during upgrading. Improved loan product, subsidize introduction of
GAHPs, keep funds in reserve to cover loan defaults.
52. 52
Example #4: Aggregation systems for horticulture in Bihar
People in Bihar consume less than half of the global
recommendation of 400 grams/capita/day (FAO and
WHO, 2014)
Consumers dependent upon nutritionally vulnerable
markets (i.e. traditional, small and often rural) likely to
face the greatest challenges to F&V access and
affordability.
Do aggregation systems like LOOP (a program of Digital
Green) improve availability/accessibility for poorer, more
remote HHs? Can they be made more nutritionally-
sensitive? Are there trade-offs in doing so?
Picture credit: K.M. Rich 2019 (Muzzafapour, India)
Source: Slide courtesy of Cooper et al. (2020)
53. 53
The LOOP aggregation scheme
1. F&V aggregation
from farmers
2. Aggregator
sells F&V at
market
3. Aggregator
collects money
and receipts
4. Returns revenues
and receipts to farmers
LOOP
LOOP: a mobile app-based aggregation service that has collected
and sold the F&V supplies of over 28,000 farmers in Bihar, India
Key farmer-facing
benefits:
Cut transport costs
(1.5 Rs/kg 0.5-1
Rs/kg)
Market access
Increased bargaining
power
Time-savings
BUT …
The combination of
lower transport costs
and access to higher
capacity vehicles has
contributed to
aggregation pathways
clustering around
large urban markets
(occasionally
bypassing smaller
rural markets)
Source: Slide courtesy of Cooper et al. (2020)
54. 54
Approach
Example: the total number of farmers
registered to LOOP in Koilwar block, Bihar
Spatial group model building (SGMB): involving
stakeholders in model conceptualisation,
formulation, analysis, evaluation and decision-
making (Mumba et al. 2017); using the participatory
GIS tool ‘LayerStack’ (Rich et al. 2018)
LOOP dashboard data: real-time market transaction
data covering LOOP supply quantities, F&V types,
prices and associated meta-data
Household survey data: 360 farming household
surveys on production and marketing habits
Source: Slide courtesy of Cooper et al. (2020)
55. 55
Output timeseries
Reference Extension Quota
Cold storage Consumer demand
LOOP farmers LOOP profits
LOOP sales Small market
F&V retail
purchases per
customer
Source: Slide courtesy of Cooper et al. (2020)
57. 57
Wider trade-offs
-1
0
1
2
3
4
LOOP extension
-1
0
1
2
3
4
Small market
quota
-1
0
1
2
3
4
Cold storage
-1
0
1
2
3
4
Retail demand growth
Reference
baseline
Outcome
relative
to
reference
Outcome
relative
to
reference
Source: Slide courtesy of Cooper et al. (2020)
58. 58
Implications
Aggregation systems: real potential to improve the availability
and affordability of F&V in small, rural markets.
However, nutrition-facing benefits may come at the expense of
producer-facing financial outcomes.
Likewise, changes in the wider enabling environment may
compound these trade-offs (e.g. cold storage stabilising prices
in smaller markets)
Picture credit: K.M. Rich 2019 (Muzzafapour, India)
Source: Slide courtesy of Cooper et al. (2020)
59. 59
References
Antunes, P., Santos, R., & Videira, N. (2006). Participatory decision making for sustainable development—the use of mediated modelling techniques. Land Use
Policy, 23(1), 44-52.
Berends, J., Rich, K.M., & Lyne, M.C. (2020). A pro-poor approach to upgrade value chains in Tanintharyi region of Myanmar. Oral presentation for the 3rd Asia-Pacific
System Dynamics Society Conference, Brisbane, Australia, 4 February 2020.
Cooper, G.S., Rich, K.M., Shankar, B., Rana, V., Ratna, N., Kadiyala, S., Alam, D. & Nadagouda, S.B. (in review).Identifying ‘win-win-win’ futures from inequitable value
chain trade-offs: a system dynamics approach. Submitted to Agricultural Systems.
Lie, H., Rich, K.M., & Burkart, S. (2017). Participatory system dynamics modelling for dairy value chain development in Nicaragua. Development in Practice 27 (6), 785-
800.
Lie, H., Rich, K.M., van der Hoek, R., & Dizyee, K. (2018). Quantifying and evaluating policy options for inclusive dairy value chain development in Nicaragua: A system
dynamics approach. Agricultural Systems 164, 193-222.
Mumba, C., Skjerve, E., Rich, M., & Rich, K.M. (2017). Application of System Dynamics and Participatory Spatial Group Model Building in Animal Health – A Case Study of
East Coast Fever Interventions in Lundazi and Monze Districts of Zambia. PLOS One, http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189878.
Rich, K.M., Rich, M., & Dizyee, K. (2018). Participatory system approaches for urban and peri-urban agriculture planning: the role of system dynamics and spatial group
model building. Agricultural Systems 160, 110-123.
Scott, R. J., Cavana, R. Y., & Cameron, D. (2016). Recent evidence on the effectiveness of group model building. European Journal of Operational Research, 249(3), 908-
918.
Vennix, J. A. M. (1996). Group Model Building. Facilitating Team Learning Using System Dynamics. New York: Wiley & Sons
moving it to the heart of livestock agendas and investments and driving technical and transformational interventions so women can achieve better lives through livestock
Maputo declaration- 10% of public resources to agriculture
moving it to the heart of livestock agendas and investments and driving technical and transformational interventions so women can achieve better lives through livestock
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
LMP, GLAD, TASSL and ADGG in particular
moving it to the heart of livestock agendas and investments and driving technical and transformational interventions so women can achieve better lives through livestock
LMP, GLAD, TASSL and ADGG in particular
Maputo declaration- 10% of public resources to agriculture
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
LMP, GLAD, TASSL and ADGG in particular
Maputo declaration- 10% of public resources to agriculture
Maputo declaration- 10% of public resources to agriculture
First introduce LOOP farmer membership and total LOOP sales trends. Note how extension leads to ~4 times more farmers than the baseline, whilst having to send 20% of produce to Market B (smaller market) limits the attractiveness of LOOP membership relative to non-loop.
The system is less sensitive to the external scenarios (i.e. cold storage and demand); not the same feedback magnitudes/effect on LOOP membership and production
Market B Quota scenario leads to LOOP profits falling by 1/3 relative to the reference run by October 2021 (lower prices and higher wastage rates in Market B). However, positive implications for the availability and affordability of F&V in Market B, with a ~12% increase in cumulative purchases over the reference scenario.
Interesting, LOOP extension on its own may have negative implications for the avail and affordability of F&V in smaller markets (i.e. this scenario may not actually be nutritionally sensitive); non-LOOP farmers that previously supplied the smaller market are now able to access the larger market through LOOP (essentially diverting supplies away from the smaller market, making supplies less available and more expensive).
How do these runs plot on to the trade-off axes? (next slide)
NOTE: the jagged cumulative profit lines are caused by farmers investing in F&V land and higher yields.
First set up the idea of the trade-off space: where does each scenario land on the trade-off space between LOOP farmer profits (x-axis) and F&V purchases (proxy for availability and affordability) in Market B (small market)? The reference mode sits in the middle…
And the four scenarios fall within the four quadrants
Most noticeably, sending 20% of all LOOP supplies to Market B leads a significant improvement in availability and affordability, but also the steepest decline in LOOP profits. Likewise cold storage, where the reduction in waste and dampening of prices helps to improve avail and affordability, but reduce revenues and profits
Where can we go from here?
How do we arrive at the win-win space for consumer nutrition and producer livelihoods? Is it a combination of the one-at-a-time runs here? Can we run Monte Carlo like simulations to understand the interactions between the scenarios and internal drivers (not plotted here due to time/space limits).
Compare trade-offs from internal and external interventions.
We’re also able to visualise some of the other trade-offs across the wider value chain. e.g. forcibly increasing LOOP supplies to smaller markets may reduce LOOP return on investments (i.e. only able to sell smaller quantities in smaller market, losing out on recouping LOOP transport costs which are Rs/kg sold) and reduce the attractiveness of LOOP to farmers.
- And, whilst cold storage in the small market may help to reduce retail prices below the reference (and increase F&V avail and affordability), the attractiveness of LOOP supply