The Research Intent Ontology is a lightweight, flow-centric framework for open research for the Open Web Platform. The Research Intent Ontology partition research into manageable units, called research cases, that make explicit the chain of questions that goes through the researcher's mind as research progresses.

Research cases are intended to be powerful enough to describe the most complex and intricate of research problems, and simple enough to be useful for informal research that could be thought of more as proactive learning. Research cases make knowledge creation explicit and allow research and knowledge to be built upon and shared openly and in context across platforms and research disciplines.

This draft is very much a work in progress. Please don't critique too harshly while we're working on it. Instead, please join in the effort to improve it!

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One of the most common things we do on the Web is to go to our favorite search engine and look something up. Then we click through the results hoping to find what we are looking for. Yet the queries we so generously feed to the search engines do not become part of the Web. They get sent to the search engine service, and they don't come back. This is probably fine when searching for a specific resource on the Web and we can't remember the URL [[rfc1738]], or trying to learn more about a specific concept that is considered public knowledge, for example, in a Wikipedia article, but it doesn't work as well for things that are on the fringe of our collective knowledge spaces—or beyond. We need some way to keep track of where we are in our search for knowledge. Sometimes we don't remember after a half-an-hour of researching has passed by, what it was exactly that we were looking for in the first place. The journey of the researcher matters, and needs to be part of the Web.

The end goal of research is to create some new bit of knowledge. This knowledge may be an earth-shattering idea that revolutionizes how we, collectively, think of the world around us (such as the general theory of relativity), or it may be already known to others, and only new to the particular researcher that just discovered it for himself or herself. Research is, at its essence, structured learning and often involves asking a series of ever more refined questions as the research progresses. This series of questions frames the research context and delineates the learning trajectory of the researcher, and is of great value for others that are trying to understand or reconstruct the research later on. Theoretically, every piece of knowledge could trace its roots back to some bit of research that discovered it. Research cases organize and preserve this process. They broaden the scope of what has traditionally been thought of as research, modeling it holistically as the process the researcher goes through from an initial research question all the way to the resultant answer. Anyone can then step backwards and forwards through time, as it were, to see how that bit of knowledge came about.

Most knowledge found on the Web today is taken at face value. The social reputation built up by a knowledge provider is the only thing that influences trust. For a news provider this might be adequate, yet for other things it would be helpful, or even necessary, to see how that knowledge was created before placing trust in it. Research cases open up this process, making provenance of knowledge creation more discernible and transparent, allowing each of us to make more informed and accurate trust judgments.


The key words MUST, MUST NOT, REQUIRED, SHALL, SHALL NOT, SHOULD, SHOULD NOT, RECOMMENDED, NOT RECOMMENDED, MAY, and OPTIONAL in this document are to be interpreted as described in [[!rfc2119]].


The examples below can be represented by any of the available syntaxes for RDF [[rdf11-primer]], and we provide Turtle [[turtle]], JSON-LD [[json-ld]], RDF/XML [[rdf-syntax-grammar-20040210]], and HTML/RDFa [[html-rdfa]] representations of the RDF model. You can control which syntaxes are shown throughout the document by using the buttons below.

The buttons below can be used to select between the available syntaxes.

Research Intent Ontology Overview

The Research Intent Ontology can be used across a wide variety of tools to organize the process of learning and the creation of knowledge. Much like a VCS provides a scaffolding of provenance, attribution, and context around the incremental development process of a software codebase, research cases provide a similar scaffolding around the process of knowledge creation. This specification builds upon the efforts of the PROV [[prov-overview]] and Web Annotation [[!annotation-model]] communities.

At a Glance

Design Goals and Rationale

Research cases satisfies the following design goals:

There is an overwhelming deluge of data, information, and knowledge on the Web. Research cases should provide a scaffolding for this knowledge, so researchers can focus and build on top of this knowledge in a sustainable, incremental way.
Pragmatic & lightweight
We're aiming for a good balance between simple and comprehensive. We need to be able to preserve the most important elements of the research process without getting bogged down in pointless formalities. Research cases should be as easy as possible for users and developers to understand and implement, and provide an obvious return on investment.
Domain agnostic
Should work for any domain of knowledge. If domain-specific extensions to the core vocabulary are needed, they should be minimal. Research cases enable interoperability across domains of knowledge, working alongside domain-specific vocabularies which describe the objects of the study.
Client focused
Machines can take the time to connect things that we humans just don't have time for or desire to do on our own. Research cases should make researchers’ lives easier and more productive at the same time, by connecting research to related research and researchers to researchers that are working in similar areas.
Researcher centric
Research cases are about the researcher’s personal journey through the discovery process. This journey is unique to each researcher, since each one of us has a unique world view. Research cases allow researchers of any skill level pursue what they think needs to be pursued next using the knowledge that they have at the time. If you already know something, you don't need to research it. Looking at it a different way, there is more than one road that can lead to a given answer. [Many] roads lead to Rome.
Open & transparent
Enable the learning process—the journey of discovery—to be preserved and shared in context, in an open and transparent way. Everything should be publishable: the good, the bad, and, yes, even the ugly.

The Basic Framework


There SHOULD only be one question per research case.

Research Case

A research case is an intention to find an answer to a question, and embodies one and only one intention. This focus on one discrete intention at a time is a unique characteristic of research cases.

Research Context

The research context keeps track of where the researcher is in the research process. It’s intention is to model real-world research processes, which may be composed of one person researching alone, or of several people working together as is commonplace in research or open-source software development collaborations.

Vocabulary Cross-Reference

Namespace Prefixes

The following namespace prefixes are used throughout this specification:
PrefixNamespace IRIDefinition
rdf The RDF namespace [[!rdf-concepts]]
xsd The XML Schema Namespace [[!xmlschema11-2]]
owl The OWL namespace [[!owl2-overview]]
prov The PROV namespace [[!prov-o]]
oa The OA namespace [[!annotation-model]]
rio The Research Intent Ontology namespace (this specification)
(others) (various) All other namespace prefixes are used in examples only. In particular, IRIs starting with represent some application-dependent IRI [[!rfc3987]].

Extended Examples

Leonardo da Vinci Full Example

Steps to the Future: Researching the Backcountry Birth of George F. Ring

From a real research project by Dr. John Phillip Colletta, published as Building Context around Biographical Facts: A Process Illustrated by the Backcountry Birth of George F. Ring in the National Genealogical Society Quarterly.

Alignment with Similar Ideas and Vocabularies


IBIS is a system and grammar initially designed to support coordination and planning of political decision processes. It is based on three simple elements: Question, Idea, and Argument. Usually IBIS is represented on a graphical issue map. Research cases are distributed in nature, while IBIS was introduced as a centralized model. Multiple datasets of research cases could be combined, however, into a single graph and displayed graphically. Another distinction is that research cases are focused on factual questions only, while IBIS is more abstract.


Micropublications [[mp]] is a model and ontology developed by Tim Clark, Paolo Ciccarese, and Carole Goble for claims, evidence, arguments and annotations in biomedical communications.


And, of course, thanks to Robin Berjon for making our lives so much easier with ReSpec.