Sensemaking (bzw. Sinnstiftung) or sense-making is the process by which people give meaning to their collective experiences. It has been defined as "the ongoing retrospective development of plausible images that rationalize what people are doing" (Weick, Sutcliffe, & Obstfeld, 2005, p. 409). The concept was introduced to organizational studies by Karl E. Weick in the late 1960's and has affected both theory and practice. Weick intended to encourage a shift away from the traditional focus of organization theorists on decision-making and towards the processes that constitute the meaning of the decisions that are enacted in behavior. -- Wikipedia

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Introduction and First Steps

In an age flooded with information, the ability to make sense of the world around us is more crucial than ever. We invite you to dive into the realm of analytics, statistics, and open data to explore pressing social issues. The initial step is to form teams that bring diverse skills and perspectives. Begin by brainstorming potential questions that matter to you and your community. Consider issues such as income inequality, environmental justice, or access to education. Collaboratively select a focus area and identify key datasets that can provide insightful answers. Use design thinking approaches to ideate potential solutions that empower users to engage with data meaningfully.

Example Datasets and Resources

To assist your project, several open datasets and resources are available. Here are a few to consider:

1. Census Data: Utilize the U.S. Census Bureau's datasets to analyze demographics, income levels, and education statistics across different communities.
2. Local Government Data Portals: Many cities provide open data platforms—examples include crime statistics, housing data, and public health reports.
3. World Bank Data: Access datasets on global development indicators, poverty, and environmental sustainability.
4. Environmental Data: Explore data from organizations like NASA or the Environmental Protection Agency for insights into climate change and pollution.
5. Social Justice Organizations: Leverage data from groups focused on racial equity, gender rights, and access to resources to identify disparities and advocate for change.

Skills Involved

To successfully navigate this project, diverse skills will be invaluable:

• Data Analysis: Proficiency in tools such as Python, R, or SQL is essential for analyzing datasets and deriving insights.
• Statistical Knowledge: Understanding statistical methodologies will help in interpreting data accurately and responsibly.
• Design Thinking: This approach encourages innovative problem-solving and human-centered design, which are crucial for creating user-friendly solutions.
• Visualization Tools: Skills in tools like Tableau or D3.js will aid in crafting compelling visual narratives that communicate findings effectively.
• Collaboration and Communication: Strong teamwork and the ability to articulate ideas are important for sharing perspectives and refining your solution.

Embrace this opportunity to collaborate, innovate, and make a measurable impact. Together, we can harness the power of data for equity and understanding.