Defining Your Data Needs

Different types of data and tools will be required depending on the application. Needs may include:

  • Understanding historical conditions/trends

  • Assessing current conditions and assets

  • Identifying appropriate indicators and measures

  • Documenting/evaluating programmatic impacts

Historical Trends

A wide variety of data is available for capturing historical trends. Here are just a few sources directly related to agriculture and food. Others can be found on the Data Sources page of this guide.

  • Social Explorer - (Cornell users only). Online research tool designed to provide quick and easy access to modern and historical census data and demographic information. Create fast, intuitive, and illustrative maps and reports to help visually analyze and understand demography and social change throughout history.
  • USDA Census of Agriculture Historical Archive

Assessing Needs and Assets

Accurately assessing existing conditions and assets is an important step in any agriculture and food system initiative. These efforts may include data gathering in support of asset based community development.

  • Food System Assessments
  • WealthWorks approach is geared toward communities inventorying multiple forms of wealth generating capital, including intellectual, individual, social, natural, built, political, financial and cultural assets.

Metrics, Indicators, and Outcomes

Monitoring programmatic impacts are a common need for agriculture and food systems initiatives, and a growing priority for funders and sponsor organizations focused on outcomes-based programming. As the number of local and regional food systems initiatives has continued to grow, it has become increasingly important that each clearly articulates its intended area of intervention and impact.These efforts can be complicated by a lack of clear understanding about the role of and relationships between “measures”, things that can be measured at a particular point in time (in some cases serving as “proxies” for things that can’t), their function as a valid “metric”, quantifying some particular characteristic, and how these can be used as “indicators” of progress toward desired “outcomes”.

As outlined in the report Charting Growth: Sustainable Food Indicators from the Wallace Center indicators (statements about positive change) should do the following:

  • be measurable

  • be relevant to the attributes of interest

  • address the most important trends and impacts related to these attributes

  • be sensitive/responsive to changes over time in physical conditions

  • be hierarchical (providing a clear overview, but amenable to expansion into detail or at finer scales)

  • promote learning and effective feedback to decision making

Measures (data supporting the indicators) should be:

  • valid and reliable (high quality)
  • timely (indicating problems or progress while there is still time to act to prevent negative consequences)
  • collected and reported regularly and consistently over a broad geographical range of the US
  • publicly available
  • transparent and understandable

The following resources offer models for identifying and collecting potentially useful indicator data:

Logic Models

Further complicating matters is confusion regarding the relationship between measures, indicators, outcomes, and broader changes hoped for, or “goals”. And at each step in this chain of logic, assumptions might be made regarding these connections which are not apparent or valid. “Logic models” are sometimes used to represent how an activity (such as a project, a program, or a policy) is intended to produce particular results, helping reveal these assumptions. They show logical relationships among resources invested, activities, and benefits that result, as a sequence of events, usually presented in a graphic, visual representation.

Theory of Change

A number of programs and methods have been developed to help guide and more clearly articulate this process, and to properly identify the correct indicators needed to measure change resulting from programmatic interventions. Many of these relate to a broad area of work around “Theory of Change”, a methodology designed to help change makers frame and execute successful change strategies, by identifying long-term goals, mapping out requirements for achieving them, identifying areas of intervention, developing indicators associated with those interventions, and developing the ability to “tell stories” that clearly articulate the need and goals of a project, and how the work being done (or proposed) will address those.


As defined by the American Evaluation Association, evaluation involves assessing the strengths and weaknesses of programs, policies, personnel, products, and organizations to improve their effectiveness. Evaluation is the systematic collection and analysis of data needed to make decisions.

The Cornell Office for Research on Evaluation (CORE) offers several useful resources and services related to evaluation, including those specifically geared to the needs of Cooperative Extension. CORE has developed an approach which provides a method for linking multiple logic models together as part of a "network pathway", illustrating lateral, potentially synergistic connections between programs and their outcomes, which may be quite linear in themselves. The Netway is a publicly and freely available tool developed by the CORE supporting collaborative development of program models and evaluation plans.

Other resources include:

Collective Impact

The actual process of indicator development, with/through stakeholder engagement, can be a powerful means of capacity building in itself, helping people and organizations come together to identify common ground and shared goals. This process can be balanced and strengthened by the inclusion of a rigorous approach or knowledgeable experts. “Collective Impact” is one emerging framework for identifying shared indicators, helping guide and link individual projects and communities efforts.


A number of highly innovative food and agriculture related projects are using a network based approach. Various network analyis tools (e.g. Social Network Analysis, or SNA) including surveys are being used to collect, analyze and visualize data about the nature and health of these networks. Network-centric approaches to community and regional development tend to be more focused on capacity building (e.g. building social capital) rather than immediate and discrete outcomes.