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In this demo we present IRIS, an open-source framework that provides a set of simple and modular document operators that can be combined in various ways to create more interesting and advanced functionality otherwise unavailable during most information search sessions. Those functionalities include summarization, ranking, filtering and query. The goal is to support users looking for, collecting, and synthesizing information. The system is also easily extendable, allowing for customized functionality for users during information sessions and researchers studying higher levels of abstraction for information retrieval. The demo shows the front end interactions using a browser plug-in that offers new interactions with documents during search sessions, as well as the back-end components driving the system. 

People often have difficulty in expressing their information needs. Many times this results from a lack of clarity about the task at hand, or the way an information or search system works. In addition, people may not know what they do not know. The former is addressed by search systems by providing recommendations, whereas there are no good solutions for the latter problem. Even when a search system makes recommendations, they are limited to suggesting objects such as queries and documents only. They do not consider providing suggestions for strategies, people, or processes. This Perspective Paper addresses it by showing how to investigate the nature of the work a person is doing, predicting the potential problems they may encounter, and providing help to overcome those problems. This help could be an object such as a document or a query, a strategy, or a person. This whole process is referred to as Information Fostering. Beyond crafting a general-purpose recommender system, Information Fostering is the idea of providing proactive suggestions and help to information seekers. This could allow them avoid potential problems and capture promising opportunities from a search process before it is too late. The current paper presents this new perspective by outlining desired characteristics of an Information Fostering system, envisioning application scenarios, and proposing a set of potential methods for moving forward. Beyond these details, the primary purpose of this paper is to offer a new viewpoint that looks at the other side of the information seeking coin, by bringing together ideas from human-computer interaction, information retrieval, recommender systems, and education.