CISE - IIS - About

The Division of Information and Intelligent Systems (IIS) supports science and engineering research and education projects that 1) develop new knowledge about the integration and co-evolution of social and technical systems, especially those that have the potential to transform learning and discovery and enhance quality of life and economic prosperity for all people; 2) increase the capabilities of human beings and machines to create, discover and reason with knowledge by advancing the ability to represent, collect, store, organize, visualize and communicate about data and information; 3) advance knowledge about how computational systems can perform tasks autonomously, robustly, and flexibly; and 4) advance the state-of-the-art in the application of IIS technologies in specific contexts.

The IIS Division is organized into three clusters, Human-Centered Computing (HCC), Information Integration and Informatics (III), and Robust Intelligence (RI).  Each cluster funds science and engineering research and education projects across a set of related themes. See the details below. IIS is also emphasizing two cross-cutting technical areas, Integrative Intelligence (INT2) and Next-Generation Networked Information (NGNI). 

IIS is involved in many cross-agency and cross-directorate activities.  In particular, NSF (including IIS) and the National Institutes of Health (NIH) support Collaborative Research in Computational Neuroscience (CRCNS).  Both agencies recognize the need for research that focuses on integrating computational models and methods with neuroscience.  IIS is also involved in a NSF cross-directorate activity, Advanced Learning Technologies (ALT), which enables radical improvements in learning and advances research in computer science, information technology, learning, and cognitive science through the unique challenges posed by learning environments and learning technology platforms.

Human-Centered Computing Cluster

Human-Centered Computing (HCC) research encompasses a rich panoply of diverse themes in Computer Science and IT, all of which are united by the common thread that human beings, whether as individuals, teams, organizations or societies, assume participatory and integral roles throughout all stages of IT development and use. People design new technologies; people, in teams and organizations, at school and at home, use them; people anticipate and enjoy their benefits; and they learn about the outcomes of use (whether anticipated or not) and translate that knowledge into the next generation of systems. At the same time, new information technologies and human societies co-evolve, transforming each other in the process. As a consequence, the design of IT must be sensitive to human values and preferences.

Human-Centered Computing topics include, but are not limited to:

·          Problem-solving in distributed environments, ranging across Internet-based information systems, grids, sensor-based information networks, and mobile and wearable information appliances.

·          Multimedia and multi-modal interfaces in which combinations of speech, text, graphics, gesture, movement, touch, sound, etc. are used by people and machines to communicate with one another.

·          Intelligent interfaces and user modeling, information visualization, and adaptation of content to accommodate different display capabilities, modalities, bandwidth and latency.

·          Multi-agent systems that control and coordinate actions and solve complex problems in distributed environments in a wide variety of domains, such as disaster response teams, e-commerce, education, and successful aging.

·          Models for effective computer-mediated human-human interaction under a variety of constraints, (e.g., video conferencing, collaboration across high vs. low bandwidth networks, etc.).

·          Definition of semantic structures for multimedia information to support cross-modal input and output.

·          Specific solutions to address the special needs of particular communities.

·          Collaborative systems that enable knowledge-intensive and dynamic interactions for innovation and knowledge generation across organizational boundaries, national borders, and professional fields.

·          Novel methods to support and enhance social interaction, including innovative ideas like social orthotics, affective computing, and experience capture.

·          Studies of how social organizations, such as government agencies or corporations, respond to and shape the introduction of new information technologies, especially with the goal of improving scientific understanding and technical design.

It is anticipated that Human-Centered Computing will support computer scientists as well as social and behavioral scientists and economists whose work contributes to the design and understanding of novel information technologies. However, HCC research should primarily advance the computer and information sciences rather than the social, behavioral, or economic sciences. Similarly, algorithms, protocols and hardware to build mobile networks would not be appropriate unless there was a very strong focus on individual or group users.

Human-Centered Computing (HCC) subsumes topics covered by these areas previously supported by the IIS Division: Digital Society and Technologies; Human-Computer Interaction; and Universal Access.

Funding Opportunities for the Human-Centered Computing Cluster:

Information and Intelligent Systems:  Advancing Human-Centered Computing, Information Integration and Informatics, and Robust Intelligence. NSF 07-577.

Information Integration and Informatics Cluster

Information Integration and Informatics (III) adopts the view that digital content has various stages of refinement and maturity, which can meet diverse sets of needs and serve many purposes. In this view, the hierarchy of refinement and structure proceeds from data to information to knowledge to understanding and, finally, to decision or action as well as to new applications supported by appropriate and necessary digital technologies. The progression is one from bits to data structures and organization to contextualized information objects and resources that support the creation and use of knowledge and understanding through human reasoning and artificial intelligence. The research focus is on digital content and the relevant processes, technologies, and human involvement in creation, storage, querying, representation, presentation, organization, integration, updating, management, analysis, security, privacy, interaction and preservation at each stage of the hierarchy of technology environments from personal computers to globally-distributed dynamic networked repository systems.

Supported activities include:

·          III core research (III-COR), which expands and strengthens the foundations of III research and education, and broadens its impact in all domains; and

·          III contextual research (III-CXT), which explores and extends the potential of III research in specific contexts.

III topics include, but are not limited to:

·          Transformation of raw data into information and knowledge.

·          Creation of new forms of digital content, representations of digital content, access frameworks, delivery services and presentation and analysis tools.

·          Long-term preservation and archiving of valuable data assets.

·          Models of information structures in application areas relying on incomplete data, such as is required to reconstruct past events, cultures, objects and places in the fields of archeology, history, paleontology, geology, and ecology.

·          Storage, organization, retrieval, updating and mining of data, text, speech, multimedia, multidimensional structures, and streams.

·          Extraction of structured information from unstructured sources.

·          Information/knowledge discovery, fusion, summarization, and visualization.

·          Algorithms for personalizing, organizing, navigating, searching, interpreting, and presenting information of different types, using various modalities.

·          Design, management, and governance for information infrastructures, including information flow, adaptive evolution and interoperability.

·          Knowledge environments for science and engineering.

·          Information integration research that leads to a uniform interface to a multitude of heterogeneous independently developed data sources.

·          Information visualization and visual analytics.

·          Information integration research in issues arising in natural disaster recovery, such as telecommunications, message passing, and data loss.

Information Integration and Informatics (III) subsumes topics covered by these areas previously supported by the IIS Division: Digital Government; Digital Libraries and Archives; Information, Data, and Knowledge Management; and Science and Engineering Information Integration and Informatics.

Funding Opportunities for the Information Integration and Informatics Cluster:

Information and Intelligent Systems:  Advancing Human-Centered Computing, Information Integration and Informatics, and Robust Intelligence. NSF 07-577.

Robust Intelligence Cluster

Robust Intelligence (RI) encompasses computational understanding and modeling of the many human and animal capabilities that demonstrate intelligence and adaptability in unstructured and uncertain environments. The general goals of this technical area include the study, theory, design, and implementation of general, integrated, intelligent perception, communication, and reasoning capabilities that are not constrained to address only a single problem in isolation or in one particular context. Systems exhibiting Robust Intelligence are able to use a variety of modeling and reasoning approaches, such as analogical, statistical, and logical inference, to deal with open-ended and changing concepts and environments and to integrate possibly heterogeneous knowledge and reasoning methodologies in complementary and supplementary ways. Such systems are able to respond intelligently in novel situations, and to gaps, conflicts, and ambiguities in their data, knowledge, and capabilities with a level of flexibility and generality comparable to that of humans and animals. Robust intelligent systems are able to assess their environment autonomously, construct plans to achieve general goals, learn transferable lessons from their experiences, and communicate their knowledge, conclusions and reasoning to others so that they can evolve and grow in capability and robustness.

RI topics include, but are not limited to:

·          Problem solving architectures that integrate reasoning, motor, perceptual, and language capabilities and that can learn from experience.

·          Hybrid architectures that integrate or combine different methods, such as deductive, probabilistic, analogical, case-based, symbolic, or sub-symbolic reasoning.

·          Computational models of human cognition, perception, and communication for commonsense or specialized domains and tasks, including acquisition and representation of ingredient knowledge.

·          Novel approaches to long-standing problems in computer vision, for example concerning the recognition and modeling of contours, shapes, regions, objects, people, scenes, events, activities, in 2D images, 3D images or video.

·          Vision systems that capture biological components and capabilities.

·          Synergistic and collaborative research of innovative and emerging technologies to improve the intelligence, mobility, autonomy, manipulability, adaptability, and interactivity of robotic systems operating in unstructured and uncertain environments.

·          Research on intelligent and assistive robotics, neuro-robotics, multi-robot coordination and cooperation, and micro- and nano-robotics with novel approaches to sensing, perception, cognition, actuation, autonomous manipulation, learning and adaptation, haptics, and multi-modal human-robot interaction.

·          Multi-agent systems that control and coordinate actions and solve complex problems.

·          Computational approaches and architectures for analyzing, understanding, generating and summarizing speech, text and other communicative forms (e.g., gesture, haptic); interaction of communicative forms; and dialogue, conversation and other less formal genres (e.g., meeting minutes).

·          Computational models of meaning, intent, and realization at various levels of language representation with a particular attention to semantics and pragmatics; cognitively and neuro-linguistically informed approaches for model evaluation.

·          Novel approaches to longstanding language processing problems such as speaker and language recognition, machine translation, evaluation metrics, and multilingual man-machine communication, including intelligent information delivery.

·          Computational approaches to language processing for underrepresented groups such as minority language groups and aging and disabled population groups.

·          Functional modeling, theory, and analysis of the computational, representational, and coding strategies of neural systems.

Neurally-grounded computational approaches to computer vision, robotics, communication, and reasoning, and systems that combine them and embody empirically derived neural strategies.

RI supports projects that will advance the frontiers of disciplines such as computational neuroscience, language, vision, robotics, and artificial intelligence as well as those that integrate different aspects of these disciplines. While it is not necessary for every project to develop complete integrated solutions, projects that focus on advancing a single aspect must lead towards the more general RI goals mentioned above.

Robust Intelligence (RI) subsumes topics covered by these areas previously supported by the IIS Division: Artificial Intelligence and Cognitive Systems; Computational Neuroscience; Computer Vision; Human Language and Communication; and Robotics.

Funding Opportunities for the Robust Intelligence Cluster:

Information and Intelligent Systems:  Advancing Human-Centered Computing, Information Integration and Informatics, and Robust Intelligence. NSF 07-577.

CROSS-CUTTING TECHNICAL AREAS

Integrative Intelligence (INT2)

Integrative Intelligence (INT2). Many decades of work on building software artifacts that exhibit intelligent behavior have focused on circumscribed computational capabilities, such as in machine learning and knowledge discovery, planning and reasoning under uncertainty, robotics, spoken and written language, and computer vision. We now have significant bodies of results in each of these areas, together with a collection of core methods that reappear across them. However, the development of more broadly competent systems requires facing the challenges that arise in tackling and synthesizing multiple capabilities synergistically. The Integrative Intelligence (INT2) cross-cutting technical area seeks novel approaches that tackle the challenges of creating more broadly capable intelligent systems that master and integrate multiple capabilities at various levels and with various approaches and methods. Efforts that combine researchers with expertise in different areas are especially welcome.

Next-Generation Networked Information (NGNI)

  Next-Generation Networked Information (NGNI). Advances in information systems must occur hand-in-hand with advances in the networking technologies that underlie them. The Next-Generation Networked Information (NGNI) cross-cutting technical area seeks innovative research on information systems that anticipate future distributed networking environments. Examples of questions that NGNI projects might address include: What new information systems are possible in networks with massive numbers of nodes of extreme heterogeneity with respect to capability, mobility, and use? How can vast, heterogeneous, distributed, and uncoordinated sources of data and information be made comprehensible, manageable, and useful for the unforeseen and diverse tasks to which they may be relevant? What new metaphors and models will make it possible to impart coherence to the diverse ways users might access information in the future? How can information be accessed and disseminated based on both content and context (e.g., both as a function of the nature of the information itself and as a function of the current state of the user, device, and network)? How can next-generation networked information systems inform and be informed by the social structures that rely on them? How can we provide timely and coherent access to information when the magnitude of the information flow dwarfs our ability to transport, process, or comprehend the data directly? These questions are meant to be exemplary, not prescriptive. NGNI projects should be clear about the researchers' anticipated future networking environment, as well as the means for evaluating the project's results. Projects that focus primarily on traditional Networking and Distributed Systems research are not appropriate for this solicitation. However, projects that involve partnerships between researchers in Information and Intelligent Systems and Networking and Distributed Systems are especially welcome.

Funding Opportunities for the Cross-Cutting Technical Areas:

Information and Intelligent Systems:  Advancing Human-Centered Computing, Information Integration and Informatics, and Robust Intelligence. NSF 07-577.