Consumer-produced videos, images, and text posts are the fastest-growing type of content on the Internet. At the time of the writing of this book, YouTube.com alone claims that seventy-two hours of video are uploaded to its Web site every minute. At this rate, the amount of consumer-produced videos will grow by 37 million hours in one year. Of course, YouTube.com is merely one site among many where videos may be uploaded. Social media posts provide a wealth of information about the world. They consist of entertainment, instructions, personal records, and various aspects of life in general. As a collection, social media posts represent a compendium of information that goes beyond what any individual recording captures. They provide information on trends, evidence of phenomena or events, social context, and societal dynamics. As a result, they are useful for qualitative and quantitative empirical research on a larger scale than has ever been possible. To make this data accessible, we need to automatically analyze the content of the posts and make them findable. Therefore, Multimedia Information Retrieval (MIR) has rapidly emerged as the most important technology needed to answer many questions people face in different aspects of their regular activities. The next chapters will focus on multimedia organization and analysis, mostly from retrieval aspects. We begin by defining multimedia retrieval and the set of challenges and algorithms that dominate the field. In this chapter, we will present basic concepts and techniques related to accessing multimedia data. We will start with the structured data in databases, discuss information retrieval to deal with accessing information in text, and then present techniques developed and being explored in MIR.