1,617 research outputs found
Toward Semantics-aware Representation of Digital Business Processes
An extended enterprise (EE) can be described by a set of models each representing a specific aspect of the EE.
Aspects can for example be the process flow or the value description. However, different models are done by different
people, which may use different terminology, which prevents relating the models. Therefore, we propose a framework
consisting of process flow and value aspects and in addition a static domain model with structural and relational
components. Further, we outline the usage of the static domain model to enable relating the different aspects
Approximate Computation and Implicit Regularization for Very Large-scale Data Analysis
Database theory and database practice are typically the domain of computer
scientists who adopt what may be termed an algorithmic perspective on their
data. This perspective is very different than the more statistical perspective
adopted by statisticians, scientific computers, machine learners, and other who
work on what may be broadly termed statistical data analysis. In this article,
I will address fundamental aspects of this algorithmic-statistical disconnect,
with an eye to bridging the gap between these two very different approaches. A
concept that lies at the heart of this disconnect is that of statistical
regularization, a notion that has to do with how robust is the output of an
algorithm to the noise properties of the input data. Although it is nearly
completely absent from computer science, which historically has taken the input
data as given and modeled algorithms discretely, regularization in one form or
another is central to nearly every application domain that applies algorithms
to noisy data. By using several case studies, I will illustrate, both
theoretically and empirically, the nonobvious fact that approximate
computation, in and of itself, can implicitly lead to statistical
regularization. This and other recent work suggests that, by exploiting in a
more principled way the statistical properties implicit in worst-case
algorithms, one can in many cases satisfy the bicriteria of having algorithms
that are scalable to very large-scale databases and that also have good
inferential or predictive properties.Comment: To appear in the Proceedings of the 2012 ACM Symposium on Principles
of Database Systems (PODS 2012
BSML: A Binding Schema Markup Language for Data Interchange in Problem Solving Environments (PSEs)
We describe a binding schema markup language (BSML) for describing data
interchange between scientific codes. Such a facility is an important
constituent of scientific problem solving environments (PSEs). BSML is designed
to integrate with a PSE or application composition system that views model
specification and execution as a problem of managing semistructured data. The
data interchange problem is addressed by three techniques for processing
semistructured data: validation, binding, and conversion. We present BSML and
describe its application to a PSE for wireless communications system design
Object-oriented data modeling
The object-oriented paradigm models local behavior, and to a lesser extent, the structure of a problem. Semantic data models describe structure and semantics. This thesis unifies the behavioral focus of the object-oriented paradigm with the structural and semantic focus of semantic data models. The approach contains expressive abstractions to model static and derived data, semantics, and behavior. The abstractions keep the data model closer to the problem domain, and can be translated into a relational (or other) implementation. The paper makes six contributions. First, a comprehensive set of data structuring abstractions are described. Second, the abstractions are compared to the entity-relationship and relational models. Third, semantic information inherent in the functional representation of the abstractions is identified. Fourth, a set of behavioral abstractions are described. Fifth, an algorithm that describes the dynamics between mathematically derived attributes of cooperating objects is presented. Sixth, weaknesses of object-oriented programming languages are identified
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