• Paper / Report

Mental Health Data Science

  • Source : Columbia Psychiatry
  • 1 January 1970
This program at Columbia University’s Department of Psychiatry offers statistical collaboration, data analytic methodological development, and data management for mental health research. It supports over 50 psychiatric researchers annually with expertise in areas like biomarkers, clinical trials, and causal analysis. The program aims to advance biostatistical methods, develop new data analytics for emerging technologies, and design secure web-based systems for research data. It actively participates in over 60 funded grants, contributing significantly to mental health research innovation and data management.
  • Blog

Data Science, Crisis Counseling, and the Mental Health Industry

  • Source : Discover Data Science
  • 1 January 1970
This article explores the intersection of data science, crisis counseling, and the mental health industry. It highlights how data-driven approaches can enhance the effectiveness of mental health interventions and support services. The discussion covers applications such as identifying individuals at risk, personalizing counseling strategies, and optimizing resource allocation for crisis hotlines. By leveraging insights from large datasets, data science aims to improve accessibility, efficiency, and the overall impact of mental health support systems, ultimately benefiting individuals in need.
  • Case Study

How to mobilize private investment at scale in blended finance

  • Source : Convergence
  • 1 December 2019
This case study from Convergence explores effective strategies for mobilizing private investment at scale through blended finance mechanisms. It highlights the crucial role of development organizations in structuring transactions that attract private sector capital for sustainable development initiatives. The document delves into various governance models and approaches that foster successful partnerships, emphasizing the importance of de-risking and transparent frameworks to unlock significant private funding for impact-driven projects globally.
  • Paper / Report

Data-driven innovation for growth and well-being

  • Source : OECD
  • 1 December 2019
This OECD report explores the transformative potential of data-driven innovation to foster economic growth and enhance societal well-being. It delves into how the increasing availability and analysis of data can lead to new products, services, and business models, driving productivity and improving public services. The report also addresses the policy implications and challenges associated with harnessing data for innovation, including issues of privacy, security, and digital divides, advocating for frameworks that support responsible data use.
  • Case Study

Financing Social Impact

  • Source : European Union
  • 1 September 2019
This case study explores the landscape of social impact financing within the European Union, examining various mechanisms and approaches used to fund social innovation. It delves into the roles of different stakeholders, including foundations and innovators, in driving social change through financial instruments. The publication also highlights the challenges and opportunities in the European context for mobilizing capital towards initiatives that generate measurable social outcomes. The analysis provides insights into successful models and potential areas for improvement in the social finance ecosystem.
  • Media Article

How Data Science Will Help Solve Many Of The World's Most Pressing Challenges

  • Source : Forbes
  • 1 September 2019
This article highlights the transformative potential of data science in addressing complex global challenges beyond traditional business applications. It explains how data for social good initiatives leverage analytics to tackle issues like poverty, hunger, climate change, and public health crises. By analyzing vast and diverse datasets, data science enables more effective resource allocation, informed policy-making, and targeted interventions. The piece emphasizes the importance of interdisciplinary collaboration and ethical data practices to unlock solutions that drive sustainable development and foster a more equitable and resilient society for all.
  • Blog

How Academia Can Fill the Data Science Employability Gap

  • Source : LinkedIn Pulse
  • 1 August 2019
This article addresses the growing demand for data literacy in the workforce and the existing gap in academia’s ability to prepare students with these essential skills. It highlights a disconnect between employer expectations for data analysis and the training universities provide, particularly for entry-level hires. The piece suggests that while not everyone needs to be a professional analyst, basic data literacy is crucial across various sectors. It implicitly calls for academic institutions to prioritize and integrate data skills initiatives into their curricula to better equip graduates for the data-driven job market.
  • Academic / Journal Article

Data Science of the Natural Environment: A Research Roadmap

  • Source : Frontiers in Environmental Science
  • 1 August 2019
This research roadmap explores the critical role of data science in understanding and addressing challenges within the natural environment. It proposes key research directions and methodologies, emphasizing the integration of diverse datasets, advanced analytical techniques, and computational models. The article highlights applications such as climate modeling, biodiversity conservation, ecosystem health monitoring, and natural disaster prediction. The aim is to leverage data science to foster sustainable practices and inform policy decisions for environmental protection and management.
  • Academic / Journal Article

What is responsible and sustainable data science?

  • Source : journals.sagepub.com
  • 1 July 2019
This article explores the ethical and sustainable practices in data science, emphasizing its responsibility in the context of social work and analytics. It examines how data science can be applied to improve social services and the potential implications for social impact. The authors discuss frameworks that guide responsible data science practices and explore challenges such as data access, governance, and accountability.
  • Media Article

How data science can improve society

  • Source : Imperial College London
  • 1 July 2019
This article discusses the profound impact of data science on improving society across various domains. It explores how data analysis and insights can drive progress in public health, urban planning, environmental sustainability, and social justice. The piece highlights data science’s capacity to identify societal challenges, optimize resource allocation, predict future trends, and inform evidence-based policy-making. By transforming vast amounts of data into actionable knowledge, it empowers governments, organizations, and communities to develop more effective solutions that foster social good and enhance overall societal well-being.
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