DevelopersThe Common Approach’s four standards can help software developers, database developers and website builders better support their clients.
Adopt the Common Impact Data Standard. Enable clients to exchange and analyze impact data more easily.
- Provides a standard representation for the core concepts and attributes that underlie impact models (e.g., logic model, impact thesis, theory of change, etc.), inputs, activities, outputs, and outcomes;
- Provides a standard for representing the definition of an organizations’ stakeholders, outcomes, indicators, impact, etc.
- Provides a flexible standard in that any impact model can be mapped onto this data standard;
- Supports interoperability amongst impact models by enabling the transformation of data from one impact model to another;
- Complements other impact standards (such as IRIS+ taxonomy of metrics) and other data standards (such as the common data standard and IATI);
- Simplifies the sharing and analysis of impact data, including data from different sources, organizations, and software;
- Is extensible in that additional concepts and attributes can be added to meet the specific needs of an organization;
- Makes it possible to assess the similarity of indicators from multiple sources; and
- Is a Semantic Representation, that making it easier to use AI and Machine Learning to analyze the data.
Why adopt the Common Impact Data Standard?
Because the Common Impact Data Standard will allow your software, database or website to:
- enable the representation of precise definitions thereby reducing the ambiguity of interpretation;
- foster interoperability, i.e., the ability to understand and merge the information available from datasets spread across social purpose organizations, their networks and their investors and grant makers;
- make the components of impact interpretable by a computer so that open source software and other technologies developed for big data can be applied to analyze and interpret the data collected and generated by social purpose organizations, including automating the detection of inconsistencies in data, as well as the causes of the observed variations.
A common impact data ontology will allows social purpose organizations who want to share their data, and the linked details, to do so at very little cost.
The Common Impact Data Standard is ready
The Common Approach Impact Data Standard is not:
- a taxonomy of metrics or indicators currently in use by organizations, but can represent any indicator;
- a data collection or measurement standard, but can record the standard used to collect or measure data; nor
- an alternative to other impact standards (e.g. SASB, IRIS, IMP, GRI, SVI), but it can be used to represent each of those standards.
Specifically, the Common Impact Data Standard is an impact vocabulary an impact ontology.
A vocabulary is a list of concepts and properties (also referred to as “terms”) used to describe and represent an area of concern. Properties can be either link one concept to another, e.g., “forOutcome” linking an indicator to an Outcome, or link a concept to data, e.g., “dateOfBirth”. The meaning of each term is specified by an external document in a natural language such as English. In this case, the area of concern in impact measurement. Vocabularies can also represent taxonomies of concepts, such as categories of stakeholders, impacts, etc. Vocabularies can aid in data integration when the terms are consistently used by organizations such as SPOs.
The most cited definition is that an Ontology is an “explicit formal specifications of the terms in the domain and relations among them” (Gruber, 1993). In other words, the definitions of concepts and properties are specified using a formal, computation language that software can understand and use. No longer are the definition of terms relegated to an external document. Figure 2 Depicts the mapping of an indicator definition in English into the Common Approach ontology.
The purpose of the Common Approach Data Impact Ontology is twofold:
1. Linking Data. Just as the Web links pages across the world, Linked Data enables the linking of data across the world. Given a set of terms in a vocabulary or ontology, linked data standards can assign a unique identifier to each term, so that when two or more SPOs use that unique identifier, the software knows that they are referring to the same term, thereby reducing ambiguity of what term is being referred to.
2. Semantics. The Ontology defines the semantics of concepts and properties, thereby created a more precise understanding of where and how terms are to be used. Secondly, because it is machine interpretable, we can build algorithms that perform more sophisticated analysis of impact data.
The Common Form
The Common Form is also relevant to software developers.
The Common Form will be ready to use shortly. Once it is ready, you will be able to integrate it to your data management software.
The Common Foundations
Software developers can use the Common Foundations to show that their impact software guide users through the globally-recognized essential practices of impact measurement.
Join the Common Approach Community
Make sure social purpose organizations and others know that you are compliant with the Common Impact Data Standard.
Common Impact Data Standard Leadership
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To illustrate how these two Standards work, we collaborated with Carleton University and Rally Assets on an example using an investment portfolio focused on affordable housing. This case study demonstrates how these Standards can be used to represent impact data, allowing for a nuanced analysis across a portfolio while reducing the burden of reporting.
Common Approach is pleased to announce we have convened our first technical committee for the Common Impact Data Standard! They will help develop the next version of Standard and support the creation of more user-friendly technical resources.
The Common Approach recently completed a crosswalk between its Common Impact Data Standard and the Common Data Model for Nonprofits, stewarded by Microsoft, to analyze compatibility between the two data models.