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Metamodeling for Method Engineering Metamodeling for Method Engineering Edited by Manfred A. Jeusfeld, Matthias Jarke, John Mylopoulos The MIT Press Cambridge, Massachusetts London, England 6 2009 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. MIT Press books may be purchased at special quantity discounts for business or sales promotional use. For information, please email [email protected] or write to Special Sales Department, The MIT Press, 5 Cambridge Center, Cambridge, MA 02142. This book was set in Times New Roman and Syntax on 3B2 by Asco Typesetters, Hong Kong. Printed and bound in the United States of America. Library of Congress Cataloging-in-Publication Data Metamodeling for method engineering / edited by Manfred A. Jeusfeld, Matthias Jarke, John Mylopoulos. p. cm. — (Cooperative information systems) Includes bibliographical references and index. ISBN 978-0-262-10108-0 (hc : alk. paper) 1. Programming (Mathematics) 2. Engineering models. I. Jeusfeld, Manfred. II. Jarke, Matthias. III. Mylopoulos, John. IV. Series. T57.7.M48 2009 003 0.3—dc22 2008047203 10987654321 Index Note: The letter t following a page number denotes a table, the letter f denotes a figure, and the letter n denotes an endnote. Abiteboul, S., 49 ARIS House and Toolkit, 50, 51, 63–65, 66f Abrial, J.-R., 6, 7, 9 Aristotle, 3 Abstract classes, 300, 301–302, 303, 305, 310, 311, Armenise, P., 58 322 Artifact focus of method engineering, 89–90, 154 Abstractionism, 4 Artificial intelligence, 10, 12, 26, 28, 170–171 Abstraction levels. See Data level; IRDS; Model Artz, J., 3 level; Notation definition level; Notation level Assertions, 17–18 Abstraction mechanisms, xv, 3, 295–296. See also Associations, 1, 4 Aggregation; Classification; Generalization; Atkinson, N., 9 Generic relationships; Instantiation; Attribute propagation, 296, 300–302, 304, 305– Materialization 309, 310 Abstractness, 299, 300, 309, 310, 327n1 Attributes, 7, 15–16 Abstract objects, 296, 305, 307, 316, 324–325 of relationships, 16 Access-oriented metamodeling, 75–80 Authority, modeling, 34 Actions, 11, 20, 24, 25, 26 Awareness metamodels, 46 Activities, 3, 8, 11, 20, 23, 24–25. See also Dynamic aspects Backx, T., 365 Actors, 20, 21–22, 23, 34, 36 Balzer, R., 11 Adaptability Bandinelli, S., 60 goal-based, 60 Basili, V. R., 61, 343 metamodel-based, 43, 50, 51 Bayer, B., 358 of modeling environments, 52–53 Beckett, D., 233 in modeling languages, 44–45 Begeman, M., 27 of ontologies, 55 Bellamy, J., 169, 216 Adaptation, goal-driven method, 61, 62 Bergsten, P., 55, 58 AD/Cycle, 55 Berliner sehen, 79 Agent responsibility, modeling, 11 Berners-Lee, T., 50, 76, 236 Agents, 26 Bernstein, P. A., 43, 51, 65 Agents, modeling, 3, 11, 34, 36, 60 Bertino, E., 296 Aggregation, 9, 17, 33, 295. See also Relationships, Beßling, B., 357 part-whole Blair, R., 365 Alford, M., 50, 283 Bloor, M. S., 358 Al-Jadir, L., 311 Bobrow, D., 11 Alternatives, modeling, 11 Boehm, B. W., 170, 284 Anderson, J., 20, 24, 34 Boloix, G., 54 Andono¤, E. G., 296 Boman, M., 12 AND/OR trees, 28–29, 30 Booch, G., 47, 54, 57, 61, 359 Anto´n, A. I., 261 Borgida, A., 10, 11, 12 Argumentation framework, 27–28 Bosgra, O., 365 388 Index Bouma, L. G., 169 process steps, 367, 372, 373, 374, 377, 378 Boundary objects, 46 systems, 359–361 Bower, G., 3 technical system functions, 361, 362, 363–365, Brachman, R., 10 374–375 Brickley, D., 233, 235 technical system properties, 362–364, 369, 371 Brinkkemper, S., 44, 55 technical systems, 361–365 Brodie, M. L., 12, 47, 53 unit operations, 367–368, 374, 375 Bruns, G., 27 workflow modeling, 368–372 Bubenko, J., 9 Clustering of information, 3 Buneman, P., 49 Coad, P., 311 Bunge, M., 359, 360 Codd, E., 2, 6, 9 Business process engineering, 44, 74 Coleman, D., 61 Collaboration history, 46 Cþþ, metadata in, 44 Collins, A., 3 Calvanese, D., 19, 43, 339 Common Lisp Object System (CLOS), 44 Carnot, 50 Common Object Model (COM), 51, 65 CASE, 54, 58, 261 Commonsense knowledge, 10 Castro, J., 60 Communities of practice, 46, 78, 79 Catarci, T., 43 Complex activities, 24–25 Cauvet, C., 12 Complex models, 374–376, 378–379 CDIF (Case Data Interchange Format), 54 ConceptBase, 51, 55, 58, 72–75, 73f, 89–167. See Ceri, S., 105, 271 also Telos Chawathe, S., 334 active rules, 134–138, 319 Checkland, P. B., 56 CLiP, use in, 372–373, 375–377, 379 Chemical engineering, xvi, 44, 356–357. See also data flow diagrams, modeling, 139, 143–148, 150– CLiP 151, 152, 155, 159 Chemical process modeling, 372–379. See also data warehouse design, use in, 337–338, 340, CLiP 345 Chemical process system modeling, 365–368, 380 DealScribe, use in, 271–283 Chen, M., 57, 260, 261 entity-relationship approach, modeling, 139, 140– Chen, P., 6, 7 143, 149–150, 155, 156, 159 Chen, W., 105 event types, modeling, 145–146, 148 Chikofsky, E. J., 259 internotational constraints, modeling, 139, 151– Chilton, C. H., 367 155 Chung, L., 30, 34, 229 intranotational constraints, modeling, 148–151, CIM (Conceptual Information Model), 9 155 Classes, 5–6, 13–15 introduction, 89–91 abstractness/concreteness, 299, 300, 309, 310, materialization in, 296, 311–325, 326–327 327n1 metalevel formulas, 130–134 dynamic and intrinsic properties, 15 multilevel statements, 155–159 reified, 18–19 process models, modeling, 140, 160–165, 166, Class facets, 299, 303–305, 310, 316–322 167 CLASSIC, 10 as prototyping environment for method Classification, 34, 78–79, 348, 373–375. See also application, 90 Instantiation queries, 102, 105, 118–127, 134, 135 in materialization, 295, 296, 303, 310 RATS, use in, 171–172, 178, 187, 189 Classification, multiple, 94 RDF metadata in, 240 Class instances. See Objects stratification, 130 Class-metaclass correspondence, 296 strengths and weaknesses, 326–327, 374–376, Clausing, D., 74 378–379 CLiP Telos, relationship to, 89, 90, 91, 98, 101f, 117 activities, 369, 370–372 ~this, 119, 150, 292n6 chemical process system functions, 365–367, 367– UML, modeling, 158 368 views, 127–130 chemical process systems, 359, 360f, 365–368, Concepts, 1, 4, 13 380 Conceptual model, chemical process system, 359– metalevels, 359, 360f 368 partial model structure, 369 Conceptual model, workflow, 367–372 Index 389 Conceptual modeling, 1, 3, 12, 13, 38n4, 47, 92. See semantic data models, 9 also Information modeling transactions, 136–137 abstraction mechanisms, role of, 295–296 violations, 104 for end-user training, 172 Data dictionaries, 48 history, 4–12 Data flow diagrams, 11–12, 90 for integrating information, 57, 198–199, 247, 357 ConceptBase model of, 139, 143–148, 150–151, in KBS Hyperbook, 245, 247–254 152, 155, 159 in RATS, 172, 174, 178, 181, 185–187 Data integration, 43, 49 in RDF and RDF Schema, 233 Data level, 110, 156–159, 160, 161f. See also IRDS Conceptual models. See also Domain models Datalog, 72, 75, 102–105, 107, 116, 130, 134, 156, consistency and correctness of, 339, 340 167, 253 Conceptual perspective on data warehouses, 334, Data marts, 330, 331f, 335 336–341 Data models, 9, 44 Concrete classes, 300, 301–302, 303, 305, 311, 322 object-oriented, 7, 9–10 Concreteness, 299, 300, 309, 310, 327n1 Data quality, 329–330, 333 Concrete objects, 296, 300, 316, 317–318, 324–325 Data quality factors, 338, 343, 346–348, 354 Congolog, 25, 26 Data quality goals, 343–347, 348–352 Conklin, J., 27 Data quality management, 343–348 Conradi, R., 60 Data quality models, 343, 344, 345, 347–348 Constantopoulos, P., 43 Data Transformation Elements package, 67, 68f, Constraints, 17. See also ConceptBase; Databases; 333 Materialization; RATS; Telos; UML; Yourdan Data warehouse design, xvi method business aspects, 330, 333, 336, 338, 339 on relationships, 15–16 client level, 336, 340, 341, 343 rigid, 190–192 conceptual perspective, 334, 336–341 soft, 187–190 implementation, 339–341 Constructivism, 79 data warehouse level, 336 Context adaptation, 46 enterprise model, 336, 338, 340 Context Interchange Project, 50 logical perspective, 334, 336–338, 341, 348, 349f Context metamodels, 46 metadata framework, 336–338 Context models, 56 physical perspective, 334, 336–338, 341–343, 348, Contextualism, 4 349f Cooperative information systems, distributed, 45 quality data, 344, 345–346 Copeland, G., 9 quality factors, 338, 343, 346–348, 354 Corcho, O., 54 quality goals, 343–347, 348–352 CPCE, 60 quality management, 343–348 Cs3, 260, 284 quality metamodel, 345–348 Curtis, B., 58, 259, 260 quality models, 343, 344, 345, 347–348 CWM (Common Warehouse Metamodel), 331– queries, 335, 341, 343–344, 346, 347, 348, 351, 333 353f Cybulski, J. L., 60 repository model, 336–338 CYC, 50 source level, 336, 341, 343 views, 330, 334, 336, 338, 344, 345 Dahchour, M., 295, 296, 310 Data warehouses, 45, 50 Dahl, O.-J., 5 architecture, 330–342 DAML-OIL, 50, 51 metamodel, 337–338 Dardenne, A., 11, 26, 61 repository, 330, 336–338, 340, 344–345 Darimont, R., 29 data quality, 329–330, 333 Data Abstraction, Databases, and Conceptual metadata-based management of, 330, 334, 335, Modeling, Workshop on, 12 348–352 Databases, 1, 3, 12, 47 metadata standards, 331–333 deductive, 90, 102–105, 275 metamodels, 333, 339 integrity constraints, 103, 104 metrics for quality measurement, 343, 344, 345, introspection in, 44 346, 347, 348 key constraints, 16 strengths and limitations, 329, 353 logical schema, 7 Davis, G.-B., 61 object-oriented, 9, 274–275 Davy, C., 260 relational model, 2 Dayal, U., 43 390 Index DB-Prism, 332f,
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