Welcome to understanding research impact. Nowadays, it is not uncommon for employers, academic institutions, and funding agencies to ask for evidence of your research impact before making important decisions, such as tenure promotions, academic honors, or grant awards. Therefore, as a researcher, it is important for you to understand what research impact is, what you can do to document, enhance, measure, and present your research impact to those decision makers. The idea of research impact is not new. The traditional model of impact is based on the simple concept of citation. If your work is cited by someone, that's considered impact. From this simple assumption, some very important metrics of impact were established. For example, the times cited measure for an article, the impact factor of a journal, and the h-index of a researcher. Traditionally, authors have been reporting the number of times their articles have been cited to demonstrate the impact of the articles. Tools that are commonly used to do that include the Web of Science, Scopus, and Google Scholar. Notice that because these tools can only base their calculation on the publications they index, the times cited measure reported by these tools can be very different. The impact factor of a journal is a measure designed to compare the impact of journals. To illustrate with an example: if a journal has an impact of 31 in 2013, it means that articles published in that journal in 2011 and 2012 are, on average, cited 31 times in 2013. The impact factor is calculated by journal citation reports from Thompson Reuters. Notice that the impact factor was originally targeted at providing evaluators of journals with information on the journal's performance, not as an indicator of an individual researcher's impact. The h-index, on the other hand, was originally designed to measure the impact of individual researchers. For example, if a researcher has an h-index of 10, it means that the researcher has published at least 10 articles, each of which has been cited at least 10 times. You can get your h_index from a variety of sources, such as the Web of Science, or Scopus. Again, because different sources base their calculations only on the publications they index, the h-index reported by these tools can be very different. You'll notice here that Scopus' h-index only considered articles indexed in Scopus published after 1995, so the number here is very different from the one reported by the Web of Science. Both the impact factor and the h-index have a series of related measures, which address the some of the perceived weaknesses of the metrics. For example, the Eigenfactor also measures the impact of a journal, but it not only considers the number of citations but the source of the citations as well, giving more weight to those from "highly ranked journals". Another example the m-quotient is h-index divided by the number of years since the first published paper of the researcher. Therefore, it is a fairer comparison between researchers at different stages of their careers. Citation-based metrics, as a measure of research impact, have some inherent limitations. As we have seen, these metrics can vary greatly depending on who does the calculation. Other limitations include some types of publications, such as reviews, are natually more likely to be cited than others. Researchers from some fields are more likely to cite each other than those from other fields. A citation itself is also not necessarily equal to a positive evaluation of the quality of the research. Most importantly research impact can mean a lot more than publications and their citations. How many times a research article is cited is not necessarily indicative or predictive of how much real world impact the research makes or will make. To understand the big picture of research impact, consider this tree analogy. The roots system here represents the research output and activities which include, but are not limited to, publications and their citations. For example, it may also include collaboration activities, which is a great way to measure research impact. It may also include activities in the social media world, which is the primary focus of a number of numetrics known as altmetrics. The stem of the tree represents the translational process from research output and activites, to real world impact. And the branches and leaves systems obviously represent the real world impacts themselves, such as a more effective medical procedure, a change in practice guideline, a change in educational curriculum, et cetera. As you can see, citation-based metrics only measure a small part of the big picture here. Even though they are important, researchers should take a more holistic approach to research impact, so that the impact stories they tell are more rounded and better supported. To help you navigate the big picture of research impact, the Becker Medical Library of Washington University, in St. Louis created a checklist of over 300 real world biomedical research impact indicators, which derive from research output and activities through these five important pathways of diffusion. The Becker Model has a lot of important indicators of impact, but you will certainly have some unique indicators of impact that are not included here for your specific area of research. The Becker Model is an open framework, so you can easily add the indicators that matter to you. In this series of short videos, we're going to first take a closer look at the traditional metrics, and how to appropriately use them in telling your impact stories. Then we're going to look in more detail at the Becker Model, and how it can help you tell better research impact stories. We're also going to show you the general steps in visualizing your research impact data to help you tell more compelling research impact stories. Your research impact depends greatly on the discoverability of your work, therefore to achieve maximum impact, you should make sure to write, publish, and disseminate your work in ways that facilitate discovery by your audience. These videos will also include tips and tricks to help you enhance the discoverability of your work and your research impact. So, let's get started with understanding research impact.