From owner-ieee-metadata@monroe.llnl.gov Wed Feb 26 19:11 EST 1997 X-VM-v5-Data: ([nil nil nil nil nil nil nil nil nil] ["1975" "Wed" "26" "February" "1997" "15:51:54" "-0800" "Charles R. Musick, Jr." "rmusick@k2.llnl.gov" "<199702262351.PAA06380@k2.llnl.gov>" "56" "[olken@mh1.lbl.gov: Metadata Registries Workshop Deadline extension]" "^From:" nil nil "2" "1997022623:51:54" "[olken@mh1.lbl.gov: Metadata Registries Workshop Deadline extension]" nil nil] nil) Received: from cv3.cv.nrao.edu (root@cv3.cv.nrao.edu [192.33.115.2]) by fits.cv.nrao.edu (8.8.5/8.8.0/CV-2.2) with ESMTP id TAA10060 for ; Wed, 26 Feb 1997 19:11:15 -0500 (EST) Received: from monroe.llnl.gov (monroe.llnl.gov [128.115.54.12]) by cv3.cv.nrao.edu (8.8.5/8.8.5/CV-2.4) with ESMTP id TAA19543 for ; Wed, 26 Feb 1997 19:11:12 -0500 (EST) Received: (from daemon@localhost) by monroe.llnl.gov (8.8.5/LLNL-3.0) id PAA08273 for ieee-metadata-list@lists.llnl.gov; Wed, 26 Feb 1997 15:51:58 -0800 (PST) Received: from k2.llnl.gov (rmusick@k2.llnl.gov [134.9.1.1]) by monroe.llnl.gov (8.8.5/LLNL-3.0) with ESMTP id PAA08265 for ; Wed, 26 Feb 1997 15:51:56 -0800 (PST) Received: (from rmusick@localhost) by k2.llnl.gov (8.8.5/8.8.5/LLNL-Jun96) id PAA06380; Wed, 26 Feb 1997 15:51:54 -0800 (PST) Message-Id: <199702262351.PAA06380@k2.llnl.gov> Errors-To: owner-ieee-metadata@monroe.llnl.gov Reply-To: ieee-metadata@llnl.gov Precedence: bulk Content-Type: text Content-Length: 1974 From: Charles R Musick Jr To: ieee-metadata@monroe.llnl.gov Subject: [olken@mh1.lbl.gov: Metadata Registries Workshop Deadline extension] Date: Wed, 26 Feb 1997 15:51:54 -0800 (PST) ------- Start of forwarded message ------- PLEASE CIRCULATE THE CALL TO YOUR COLLEAGUES. ========================================================================== Joint Workshop on Metadata Registries Deadline Extended to March 14, 1997 PLEASE NOTE THAT THE DEADLINE FOR SUBMISSIONS HAS BEEN EXTENDED TO March 14, 1997. The Participation Intent Form is now available at the workshop homepage - - given below. We are asking everyone planning to attend the workshop to fill out the form. This is to announce a workshop of invited participants on how to improve access to and sharing of data by harmonizing metadata standards and developing interoperable metadata registries accessible by the World Wide Web. A central goal of the workshop will be to develop detailed recommendations for registries of data element metadata and higher-level metadata (e.g., for schemas, models, and metamodels). The workshop will bring together researchers in formal methods (from the knowledge representation and database communities), and other researchers and practitioners from the database research, standards, metadata registry, middleware and database vendor, GIS, EDI, and digital library communities. Dates and Location: * July 8-11, 1997, Tuesday through Friday - 9:00 AM to 5:00 PM * Clark Kerr Campus Conference Center, University of California, Berkeley, California WWW Documents: * Preliminary Call for Participation http://www.lbl.gov/~olken/EPA/Workshop/call.html * Workshop Home Page http://www.lbl.gov/~olken/EPA/Workshop/index.html Key Dates: March 14, 1997 Papers/abstracts and Participation Intent Form due April 14, 1997 Program Committee Meeting (Berkeley, Calif.) April 18, 1997 Invitations issued June 8, 1997 Early registration fees due July 8-11, 1997 Workshop convenes =================================================================== ------- End of forwarded message ------- From owner-ieee-metadata@monroe.llnl.gov Tue Mar 4 17:01 EST 1997 X-VM-v5-Data: ([nil nil nil nil nil nil nil nil nil] ["8103" "Tue" "4" "March" "1997" "12:41:42" "-0800" "Charles R. Musick, Jr." "rmusick@k2.llnl.gov" "<199703042041.MAA16247@k2.llnl.gov>" "175" "DMDK special issue" "^From:" nil nil "3" "1997030420:41:42" "DMDK special issue" nil nil] nil) Received: from cv3.cv.nrao.edu (root@cv3.cv.nrao.edu [192.33.115.2]) by fits.cv.nrao.edu (8.8.5/8.8.0/CV-2.2) with ESMTP id RAA14422 for ; Tue, 4 Mar 1997 17:01:43 -0500 (EST) Received: from monroe.llnl.gov (monroe.llnl.gov [128.115.54.12]) by cv3.cv.nrao.edu (8.8.5/8.8.5/CV-2.4) with ESMTP id RAA14822 for ; Tue, 4 Mar 1997 17:01:40 -0500 (EST) Received: (from daemon@localhost) by monroe.llnl.gov (8.8.5/LLNL-3.0) id MAA20283 for ieee-metadata-list@lists.llnl.gov; Tue, 4 Mar 1997 12:41:46 -0800 (PST) Received: from k2.llnl.gov (rmusick@k2.llnl.gov [134.9.1.1]) by monroe.llnl.gov (8.8.5/LLNL-3.0) with ESMTP id MAA20275 for ; Tue, 4 Mar 1997 12:41:43 -0800 (PST) Received: (from rmusick@localhost) by k2.llnl.gov (8.8.5/8.8.5/LLNL-Jun96) id MAA16247; Tue, 4 Mar 1997 12:41:42 -0800 (PST) Message-Id: <199703042041.MAA16247@k2.llnl.gov> Errors-To: owner-ieee-metadata@monroe.llnl.gov Reply-To: ieee-metadata@llnl.gov Precedence: bulk Content-Type: text Content-Length: 8102 From: Charles R Musick Jr To: ieee-metadata@monroe.llnl.gov Subject: DMDK special issue Date: Tue, 4 Mar 1997 12:41:42 -0800 (PST) This may be of interest to the metadata miners out there.. ============================================================================ CALL FOR PAPERS ============================================================================ DATA MINING AND KNOWLEDGE DISCOVERY Special Issue on Scalable High-Performance Computing for KDD Guest editors: Paul Stolorz and Ron Musick ========================================== http://www.research.microsoft.com/research/datamine/dmkdpar Traditional computational techniques and computer architectures are routinely overwhelmed by the sheer volume and complexity of information generated from data-gathering instruments, computational and experimental methodologies, and business operations. The fundamental problem of extracting knowledge and insight from massive databases and datasets is shared across a wide range of fields in business, academia and government. The new field of Data Mining and Knowledge Discovery in Databases (KDD) has arisen as an interdisciplinary response to this situation, merging ideas drawn from disciplines such as statistics, pattern recognition, machine learning, databases, visualization and high performance computing. This special issue of Data Mining and Knowledge Discovery is devoted to the challenge of applying data mining and knowledge discovery methods to large, complex datasets. Implementation of data mining ideas in high-performance computing environments is crucial for coping with large-scale data. In particular, parallel and distributed systems are needed to ensure system scalability as datasets grow inexorably in size and scope. These environments include dedicated massively parallel supercomputers, super-servers built from clusters of commodity workstations and high-speed network interfaces, and heterogeneous networks distributed over regional, national and global scales. High-performance and parallel computing holds the promise of scaling to large data sets, allowing the data mining component to search a much larger set of patterns and models than traditional computational platforms and algorithms would allow. In addition, it promises to render the KDD process much more interactive by allowing fast response times for difficult search and model fitting problems. Data Mining and Knowledge Discovery, published by Kluwer Academic publishers, is the flagship publication in the rapidly growing area of KDD. In this special issue we solicit the most dramatic new developments in high performance large-scale KDD applications, highlighting the promise of the technology and identifying the main challenges for the future. Technically innovative papers that describe new theoretical developments, or tackle the application of practical data mining approaches to real problems and datasets on parallel and distributed architectures, are solicited. Topics of interest include, but are not limited to, the intersection of KDD with the following fields: Parallel implementations of datamining & KDD methods: Classification and regression: e.g. decision trees, neural nets Pattern recognition Belief nets and other Bayesian approaches Genetic programming Association rules Statistical inference Similarity detection and measurement Clustering and density estimation Change-detection Text retrieval Content-based indexing Data visualization Trend Analysis Integration of KDD techniques with scalable I/O systems: Data warehouses & federated databases Parallel file systems High-performance network interfaces Intelligent data layout Out-of-core algorithms Parallel relational querying High performance storage systems Hierarchical and distributed storage Methods to control complexity: Random sampling Anytime algorithms applied to datamining techniques New complex data-type algorithms (eg. not based on feature vectors) Domain simplification techniques Inference error/confidence characterization Parallel, clustered and/or distributed applications: Datamining on commodity-based clusters and networks Web-oriented datamining Novel applications and case studies Knowledge discovery systems and tools SCOPE AND REVIEW CRITERIA Articles are solicited that deal with both theoretic and application- oriented approaches to handling the problems inherent in large-scale KDD. All submitted articles should be relevant to KDD, clearly indicating which aspect of large-scale KDD is being addressed. Papers should be clearly written and accessible to readers from several disciplines. A well-written, motivated introduction is especially important. Assumptions and limitations of the methods described must be discussed. Contributions must represent either a fundamental advance in algorithms and methods, or a novel application with clear roots in systematic principals. The scaling properties of algorithms and architectures with respect to problem size and complexity must be discussed, and where appropriate analysis of the throughput and latencies of the systems described. In addition to full-length papers (see below), short application summaries (1-3 pages) are also encouraged. All submissions will be reviewed on the basis of relevance, originality, significance, soundness and clarity. At least three referees will review each submission independently. Results of the review will be sent to the first author via email, unless otherwise requested. SUBMISSION INSTRUCTIONS Electronic submissions are STRONGLY ENCOURAGED. Postscript copies of papers may be emailed to dmkdpar@aig.jpl.nasa.gov. Latex style files and related instructions can be obtained at the web site http://www.research.microsoft.com/research/datamine. Submissions of full papers should be limited to at most 28 pages in 12pt font, 1.5 line-spacing. Electronic submissions will speed the review process significantly, however due to Kluwer requirements, authors must also submit hardcopy papers. All authors must submit (6) hardcopy papers as follows: five (5) hardcopies to: Ms. Karen Cullen, DATA MINING AND KNOWLEDGE DISCOVERY Editorial Office, Kluwer Academic Publishers, 101 Philip Drive, Norwell, MA 02061 phone 617-871-6600 fax 617-871-6528 email: kcullen@wkap.com one (1) hardcopy to: Dr Paul Stolorz Attn: DMKD Special Issue MS 525 3660 Jet Propulsion Laboratory 4800 Oak Grove Drive Pasadena CA 91109 USA In addition, an email message containing title, abstract, and keywords must be sent to dmkdpar@aig.jpl.nasa.gov and cc-ed to kcullen@wkap.com. Please use the electronic template available on the web. For those with no network access, please call Ms. Cullen with a request at 617-871-6600. The journal emphasizes fast dissemination of results and minimal backlogs in publication time. An electronic server will be made available by Kluwer containing accepted articles and will be accessible by subscribers to the journal. Authors are encouraged to make their data available via the journal web site, allowing papers to have an "electronic appendix" containing data and algorithms. =============== IMPORTANT DATES =============== ************************************** SUBMISSION DEADLINE: May 8, 1997 ACCEPTANCE NOTIFICATION: June 20, 1997 ************************************** Enquiries about the submission process and scope of the special issue may be sent to dmkdpar@aig.jpl.nasa.gov.