Evolving VirtuE

One of the most attractive aspects of virtual enterprises is their agility: the inherent ability to adapt and evolve in response to changing market conditions. Evolving VirtuE is a formal framework within which such agility can be realized. Through the concepts of enterprise time, activity logging, and log mining, the recent behavior and performance of an enterprise may be studied,and corresponding evolutionary steps can be induced. These steps may be intended to benefit the operation of individual enterprise members, as well the enterprise as a whole. In addition, we examine enterprise creation, a period of rapid evolution that concludes when the enterprise reaches stability and begins transacting its business activities.One of the most attractive aspects of virtual enterprises is their agility: the inherent ability to adapt and evolve in response to changing market conditions. Evolving VirtuE is a formal framework within which such agility can be realized. Through the concepts of enterprise time, activity logging, and log mining, the recent behavior and performance of an enterprise may be studied,and corresponding evolutionary steps can be induced. These steps may be intended to benefit the operation of individual enterprise members, as well the enterprise as a whole. In addition, we examine enterprise creation, a period of rapid evolution that concludes when the enterprise reaches stability and begins transacting its business activities.Monograph's chapter

VirtuE: a Formal Model of Virtual Enterprises for Information Markets

A vital part of a modern economy is an information market. In this market, information products are being traded in countless ways. Information is bought, modified, integrated, incorporated into other products, and then sold again. Often, the manufacturing of an information product requires the collaboration of several participants. A virtual enterprise is a community of business entities that collaborate on the manufacturing of complex products. This collaboration is often ad hoc, for a specific product only, after which the virtual enterprise may dismantle. The virtual enterprise paradigm is particularly appealing for modeling collaborations for manufacturing information products, and in this paper we present a new model, called VirtuE, for modeling such activities. VirtuE has three principal components. First, it defines a distributed infrastructure with concepts such as members, products, inventories, and production plans. Second, it defines transactions among members, to enable collaborative production of complex products. Finally, it provides means for the instrumentation of enterprises, to measure their performance and to govern their behavior.A vital part of a modern economy is an information market. In this market, information products are being traded in countless ways. Information is bought, modified, integrated, incorporated into other products, and then sold again. Often, the manufacturing of an information product requires the collaboration of several participants. A virtual enterprise is a community of business entities that collaborate on the manufacturing of complex products. This collaboration is often ad hoc, for a specific product only, after which the virtual enterprise may dismantle. The virtual enterprise paradigm is particularly appealing for modeling collaborations for manufacturing information products, and in this paper we present a new model, called VirtuE, for modeling such activities. VirtuE has three principal components. First, it defines a distributed infrastructure with concepts such as members, products, inventories, and production plans. Second, it defines transactions among members, to enable collaborative production of complex products. Finally, it provides means for the instrumentation of enterprises, to measure their performance and to govern their behavior.Non-Refereed Working Papers / of national relevance onl

VirtuE: Virtual Enterprises for Information Markets\u27

An essential part of a modern economy is an information market. In this market, information products are being traded in countless ways. Information is bought, modified, integrated, incorporated into other products and then sold again. Usually, the manufacturing of an information product requires the collaboration of several participants. A virtual enterprise is a community of business entities that collaborate on the manufacturing of new products. This collaboration is often ad hoc, for a specific product only, after which the virtual enterprise may dismantle. The virtual enterprise paradigm is particularly appealing for modeling collaborations for manufacturing information products, and in this paper we present a new model, called VirtuE, for modeling such activities

Grid-VirtuE: a layered architecture for grid virtual enterprises

A grid virtual enterprise is a community of independent enterprises concerned with a particular sector of the economy. Its members (nodes) are small or medium size enterprises (SME) engaged in bilateral transactions. An important principle of a grid virtual enterprise is the lack of any global "guiding force", with each member of the community making its own independent decisions. In this paper we describe Grid-VirtuE, a three-layer architecture for grid virtual enterprises. The top layer of the architecture, representing its ultimate purpose, is an environment in which grid virtual enterprises can be modeled and implemented. This layer is supported by middleware infrastructure for grids, providing a host of grid services, such as node-to-node communication, bilateral transactions, and data collection. The bottom layer is essentially a distributed data warehouse for storing, sharing and analyzing the large amounts of data generated by the grid. Among other functionalities, the warehouse handles the dissemination of data among the members of the grid; it confronts issues of data magnitude with an aging mechanism that aggregates old data at a lower level of detail; and it incorporates privacy-preserving features that retain the confidentiality of individual members. Warehouse information is also used for data and process mining, aimed at analyzing the behavior of the enterprise, and subsequently inducing evolutionary changes that will improve its performance.A grid virtual enterprise is a community of independent enterprises concerned with a particular sector of the economy. Its members (nodes) are small or medium size enterprises (SME) engaged in bilateral transactions. An important principle of a grid virtual enterprise is the lack of any global "guiding force", with each member of the community making its own independent decisions. In this paper we describe Grid-VirtuE, a three-layer architecture for grid virtual enterprises. The top layer of the architecture, representing its ultimate purpose, is an environment in which grid virtual enterprises can be modeled and implemented. This layer is supported by middleware infrastructure for grids, providing a host of grid services, such as node-to-node communication, bilateral transactions, and data collection. The bottom layer is essentially a distributed data warehouse for storing, sharing and analyzing the large amounts of data generated by the grid. Among other functionalities, the warehouse handles the dissemination of data among the members of the grid; it confronts issues of data magnitude with an aging mechanism that aggregates old data at a lower level of detail; and it incorporates privacy-preserving features that retain the confidentiality of individual members. Warehouse information is also used for data and process mining, aimed at analyzing the behavior of the enterprise, and subsequently inducing evolutionary changes that will improve its performance.Monograph's chapter

Vague: a user interface to relational databases that permits vague queries

A specific query establishes a rigid qualification and is concerned only with data that match it precisely. A vague query establishes a target qualification and is concerned also with data that are close to this target. Most conventional database systems cannot handle vague queries directly, forcing their users to retry specific queries repeatedly with minor modifications until they match data that are satisfactory. This article describes a system called VAGUE that can handle vague queries directly. The principal concept behind VAGUE is its extension to the relational data model with data metrics, which are definitions of distances between values of the same domain. A problem with implementing data distances is that different users may have different interpretations for the notion of distance. VAGUE incorporates several features that enable it to adapt itself to the individual views and priorities of its users

Intensional answers to database queries

Abstract-In addition to data, database systems store various on keys, integrity constraints, class hierarchies), are often kinds of information about their data. Examples are class hierarchies, to define the various data classes and their relationships; integrity constraints, to state required relationships among the data; and inference rules, to define new classes in terms of known classes. This information is often referred to as intensional assumed as well, but little else is assumed. Notable examples of this approach are the various attempts to provide user interfaces to relational databases that achieve logical data independence; i.e., interpret queries that specify information (the data are referred to as extensional information). only a list of attributes and a condition, without naming the Recently, there have been several independent research works that suggested ways by which intensional information may be used to improve the conventional (extensional) database answers. Although each of these efforts developed its own specific methods, specific relations to which the attributes belong and how the relations should be joined (e.g., [12], [24]). Another example is interfaces that avoid returning empty answers they all share a common belief: Database answers would be by automatically broadening all queries whose answers are improved if accompanied by intensional statements that describe them more abstractly. In this paper, we study and compare the various approaches to intensional answers by using various classifications; we examine their relative merits with regard to key aspects; we discuss remaining issues; and we offer new research empty [7], [ 161. A system based in part on these ideas is FLEX [ 151, a formal language interface to relational databases designed to service satisfactorily users with different levels of expertise. Using only the definition of the database and directions. various data indices, FLEX interprets each and every input Index Terms- Database, database extension, database intension, query, cooperative answer, extensional answer, intensional that is presented to it, regardless of its formal correctness. FLEX is also cooperative: It never delivers empty answers answer without explanation or assistance. Recently, there have been several independent efforts aime