M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....to information management, query processing, decision making, process control and many other applications. Therefore, knowledge discovery in databases (or data mining) has been considered as one of the most important research topics in 1990s by both machine learning and database researchers [17, 20]. There are different philosophical considerations on knowledge discovery in databases (KDD) 5, 23] which may lead to different methodologies in the development of KDD techniques [5, 11, 6, 18, 1, 21, 22, 23] In our previous studies [2, 7, 8] an attribute oriented induction method has been ....

M. Stonebraker, R. Agrawal, U. Dayal, E. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. 19th Int. Conf. Very Large Data Bases, pages 688-692, Dublin, Ireland, Aug. 1993.

....topic for future research. In April 1993, a similar gathering of 5 researchers in Vienna reiterated their interest in interfaces but they lamented that progress in this area 2 continues to be done by industry, and the research community has very little impact on this important topic [Stonebraker 93a] While database systems have been slow to attract the attention of mainstream HCI researchers, the development of database system technology has nevertheless spawned several innovative user interfaces. For example, relational DBMSs provide, through their declarative query languages, a ....

....Seehelm model. We believe that, far from showing that database systems are behind main stream UIMS research in this respect, it merely illustrates that DBMSs conform more closely to the abstract model of an underlying application implicit in the Seeheim model. The Way Forward Stonebraker s [Stonebraker 93a] fears notwithstanding, a brief glance at the reference section of this paper which is not intended as a comprehensive survey of the field but rather an indication of trends shows a substantial amount of work being carried out in this area. The question we attempt to address here is how to ....

Stonebraker, M., Agrawal, R., Dayal, U., Neuhold, E.J., and Reuter, A.: "DBMS Research at a Crossroads: The Vienna Update", Proc VLDB 93, Dublin, August 1993 - 45 -

.... Data Modelling System (CDMS) has been created as a prototype system in which user interaction facilities (UIFs) can be configured [14] CDMS tackles the problem that whereas DBMS are designed for a wide range of user, the user interfaces provided are few in number and often poor in quality [15]. CDMS provides a component which allows novel UIFs to be created without recourse to repetitive low level programming. To this end CDMS allows the configuration of UIFs, where each UIF consists of a conceptual model tied to a concrete user interface. The conceptual model is built as an ....

Stonebraker M, Agrawal R, Dayal U, Neuhold EJ, Reuter A. DBMS Research at a Crossroads: The Vienna Update. In: Proc. 19th International Conference on Very Large Databases, Dublin, 1993, pp 688-692

....were categorical (discrete) and most unordered. The target classes were 19 different disease conditions, very unevenly distributed among the classes. The third data set (IBM) was artificially generated from a synthetic data generation program pred created by IBM s QUEST data mining research group [78]. This program can generate data sets of any size for 55 different classification problems, each with two or four target classes. The nine inputs consist of six bounded real valued features and three categorical features, one of which is ordered. The problem domain of this dataset generator is ....

M. Stonebraker, R. Agrawal, U. Dayaland E.J. Neuhold, and A. Reuter. Dbms research at a crossroads: The vienna update. In 19th International Conference on Very Large Data Bases, 1993.

....Additional support was provided by the IBM Partnership Award, and by the IBM SUR equipment grant. Access to computing facilities was provided by AHPCRC, Minnesota Supercomputer Institute. See http: www.cs.umn.edu #han for other related papers. One of the important problems in data mining [SAD 93] is discovering association rules from databases of transactions, where each transaction contains a set of items. Several algorithms for finding association rules have been proposed. Most of the algorithms work on transaction data where each transaction contains a subset of items from the whole ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993. 3

....work in the Database Human Computer Interaction field. 1 Introduction In 1989, and again in 1993, Michael Stonebraker surveyed panels of database researchers about which research areas they considered promising, and also which areas they considered the least likely to produce significant results [1]. The panels conclusions were somewhat controversial because of their dismissal of several active research areas as unimportant. On the positive side, however, both panels chose user interfaces as the most promising area. This outcome indicates an awareness of the importance of ....

Stonebraker, M., et. al., DBMS Research at a Crossroads: The Vienna Update, Proceedings of the 19th VLDB Conference, Dublin, Ireland, 1993, pp. 688-692.

....results on these data sets show that CHAMELEON can discover natural clusters that many existing state of the art clustering algorithms fail to find. Keywords: Clustering, data mining, dynamic modeling, graph partitioning, k nearest neighbor graph. 1 Introduction Clustering in data mining [SAD 93, CHY96] is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized [JD88, KR90, PAS96, CHY96] These discovered clusters can be used to explain the characteristics of the underlying data distribution, and thus ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

....used globally [6] Despite these and other advances made in combining and storing heterogeneous and other large data sets, not enough personnel or automated tools are available to take full advantage of these data mines . Recently much work has been focused on developing automated mining tools [17] for databases based on well established theories that have their origin in the field of artificial intelligence such as Learning by Example [11] Knowledge Discovery or Database Mining is defined as the nontrivial extraction of implicit, previously unknown and potentially useful information ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold and A. Reuter, DBMS Research at a Crossroads: The Vienna Update, Invited talks at VLDB 93.

....official endorsement should be inferred. Access to computing facilities was provided by AHPCRC, Minnesota Supercomputer Institute, Cray Research Inc. and NSF grant CDA 9414015. See http: www.cs.umn.edu #han for other related papers. 1 Introduction One of the important problems in data mining [SAD 93] is discovering association rules from databases of transactions, where each transaction contains a set of items. The most time consuming operation in this discovery process is the computation of the frequencies of the occurrence of subsets of items, also called candidates, in the database of ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

....Additional support was provided by the IBM Partnership Award, and by the IBM SUR equipment grant. Access to computing facilities was provided by AHPCRC, Minnesota Supercomputer Institute. See http: www.cs.umn.edu #han for other related papers. 1 Introduction Clustering in data mining [SAD 93, CHY96] is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized [CHY96] These discovered clusters are used to explain the characteristics of the data distribution. For example, in many business applications, ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

....demand for DBMS support. This results in a number of requirements to be fulfilled by next generation database technologies. In particular, next generation database technologies address nonstandard application domains by improvement and integration of new concepts for the major DBMS aspects [6] [20], 14] DBMS architecture: should be designed in such a way that it can easily accommodate various functional extensions. From an economic point of view, it is not practicable to construct several DBMSs with different capabilities from scratch over and over again. Extensible DBMSs try to ....

....mechanisms, or alternative storage structures, depending on the characteristics of different application domains. The construction of a completely new DBMS for different requirements of application domains can be avoided by providing a flexible base DBMS part that can be extended in different ways [20]. The development effort, i.e. the costs for a specially tailored DBMS can thus be drastically reduced. There have been some prototypes implemented for academic use, but there is no commercial system available today. Data modeling: comprises object oriented, deductive, temporal (history and ....

[Article contains additional citation context not shown here]

Stonebraker, M., Agrawal, R., Dayal, U., Neuhold, E., J., Reuter, A., "DBMS Research at a Crossroads: the Vienna Update", Proc. 19th IEEE VLDB Int. Conf., Dublin, Ireland, 1993, pp. 688-692

....PESTO has been to provide a similarly friendly browsing interface, and to augment this interface with an equally natural paradigm for integrating querying and query refinement with browsing. 2. 2 Related Research In general, user interfaces have been neglected as a database research topic [Ston89, Ston93]. Still, a body of work exists in this area; a comprehensive survey and taxonomy of graphical user interfaces for database systems can be found in [Bati91] Aside from the early work on graphical relational interfaces, most research has focused on the design of interfaces for databases based on ....

M. Stonebraker et al, "DBMS Research at a Crossroads: The Vienna Update," Proc. 19th VLDB Conf., Aug. 1993.

....all, a strong user requirement for stable systems in changing environments. Numerous analyses of future database directions has indicated that legacy, change management and high availability are characteristics that are currently, if not poorly, are at least inadequately supported by databases [19 21]. From our perspective, this gives a strong pragmatic emphasis to the development of a temporal, evolving model. In addition, the development of commercial object oriented database management systems have divided (very broadly) into two groups; the unified architectures which are attempting to ....

M. Stonebraker, R. Agrawal, U. Dayal, E.J. Neuhold and A. Reuter, "DBMS research at the crossroads: the Vienna update", in Proc. Nineteenth International Conference on Very Large Databases. Dublin, Ireland, Morgan Kaufmann, Palo Alto, CA, pp. 688-692, 1993.

....on line or concurrently with usage. When reorganization is performed without taking the database off line or quiescing the transactions, it is called concurrent reorganization or on line reorganization. On line reorganization has been identified as a challenging problem by the database community [14, 17, 2, 15, 16]. The single most compelling reason to do on line reorganization is the availability of the database during the reorganization. The conventional approach to reorganization is to take the database offline. Any business enterprise that relies on 24 hour availability such as reservation systems, ....

M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at crossroads: The vienna update. In Proc. 19th Intl. Conf. VLDB, pages 688--692. Morgan Kaufmann Publishers, August 1993.

.... 1 Introduction With rapid growth in the amount of information stored in databases, the development of effective and efficient tools for knowledge discovery in databases (KDD, or data knowledge mining) has become an increasingly important task in both database and machine learning researches [21, 7, 22]. In the past several years, fruitful research has been conducted on knowledge discovery in relational databases, with some experimental systems constructed and tested in large databases [7, 11, 19, 10] With the emerging trend in the development of new database systems, such as object oriented ....

....etc. The availability of generalization operators and knowledge discovery tools will substantially enhance the power and increase the flexibility of data and knowledge base systems. As an emerging field, knowledge discovery in database has not only attracted wide attention in research communities [21, 7, 22] but also shown its high promise in industrial applications. A number of knowledge discovery systems prototypes have been constructed and experimented on medium to large databases, such as DBLEARN [10] INLEN [11] KDW [19] EXPLORA [13] FortyNiner [24] Opportunity Explorer [1] Datalogic R ....

M. Stonebraker, R. Agrawal, U. Dayal, E. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. 19th Int. Conf. Very Large Data Bases, pages 688--692, Dublin, Ireland, Aug. 1993.

....database model has to mean. Proposals such as ODMG 93 are informal and cause semantic and conceptual doubts (not only in 1 DD and DOOD can be considered as a third tendency in addition to the mentioned ones; however, there are doubts if it will result in a realistic technology, see [Ston93]. 2 An aggressive theory does not accept the current reality and forces a revolutionary change; e.g. deductive databases. A nonaggressive theory is an abstraction over many phenomena observed in the reality; e.g. theory of automata. A moderately aggressive theory accepts practical solutions ....

M. Stonebraker et al. DBMS Research at a Crossroad: the Vienna Update. Proc. 19th VLDB Conf. Dublin, Ireland, 1993.

....the expanding capabilities of database systems can be exploited fully only by expert programmers. Making databases easier to use and program, and thereby more accessible, is an important issue today and will become more important as database technology becomes faster, cheaper, and more powerful [1]. We will demonstrate DataSplash, a database visualization environment developed by the Tioga project. DataSplash is an integrated environment for creating, navigating, and querying multiple visual representations of data. Most actions can be performed incrementally via direct manipulation mouse ....

Stonebraker, M., Agrawal, R., Dayal, U., Neuhold, E., Reuter, A., "DBMS Research Crossroads: The Vienna Update," VLDB 1993, Dublin, Ireland, August 1993, pp. 688-692.

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M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

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M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

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M. Stonebraker, R. Agrawal, U. Dayal, E. Neuhold, and A. Reuter. DBMS Research at a Crossroads: The Vienna Upda te. In proceedings of the International Conference on Very Large Databases, 1993.

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M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. DBMS research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993. 8

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M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. Dbms research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

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M. Stonebraker, R. Agrawal, U. Dayal, E. J. Neuhold, and A. Reuter. Dbms research at a crossroads: The vienna update. In Proc. of the 19th VLDB Conference, pages 688--692, Dublin, Ireland, 1993.

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M. Stonebraker, et al.: DBMS Research at a Crossroads: The Vienna Update. - Proc. 19th Int. Conf. on VLDB, Dublin 1993, Morgan Kaufmann Publ., pp. 688-692

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M. Stonebraker, R. Agrawal, U. Dayal, E. Neuhold, and A. Reuter. DBMS Research at a Crossroads: The Vienna Update. In Proceedings of the International Conference on Very Large Databases, 1993.

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