III Research Topic Examples:

  • Transformation of massive volumes of data from disparate sources into useful information and actionable knowledge;
  • Usable semantics and ontologies to enrich data for new uses;
  • Ontology construction, selective knowledge sharing, and inference with large distributed sources;
  • Persistent, long-term preservation of valuable data and knowledge assets that overcome transitions in technologies and culture;
  • Re-using, re-purposing, and integrating disparate data, information, and knowledge in ways that preserve provenance and appropriate protections;
  • Integrative, generalized approaches to data, knowledge, and information integration and processing with a variety of data types, including spatial, temporal, graph, matrices, text, speech, image and other multimedia types;
  • Individual and group-oriented information management, supporting personalization, contextualization, interaction, and collaboration;
  • Data processing, management, and inference techniques that scale to the quantities, speed of acquisition, dimensionality, and complexity of data and knowledge, using the advancing computing and communication platforms and media including clouds, multicore, flash memory, mobile computing, and sensor and social networks;
  • Exploration of the limits and applicability of approaches in information integration and informatics;
  • Energy-, computing resource- and memory-conserving approaches to storing, querying, indexing, updating, and processing data;
  • Integration of data, hypothesis, predictive modeling and knowledge-based inference, experimentation, and simulation to support decision making and discovery;
  • Support for interactivity collaboration, adaptability, and evolvability with process , workflow, provenance, lifecycle, or inconsistency management;
  • Managing, querying, and analysis of social media for leveraging new forms of interaction (e.g., crowd-sourcing) for acquiring, integrating, managing, or using information;
  • Management of uncertainty, including expressive representation of and reasoning about preferences, uncertainty, noise, inconsistency, changing context, and scalable techniques;
  • Analytics for massive, distributed, dynamic, uncertain, heterogeneously structured and unstructured data, for long-term, real-time or predictive techniques with accuracy, reliability, and risk measures;
  • Challenges presented by informatics-enabled applications of societal importance;
  • New information architectures, e.g., new database designs, new data models, etc.

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.