The Dataset Attribute Family of Classes (original) (raw)

Multivariate data analysis: quo vadis? I. Object-oriented data modelling (OODM)

Journal of Chemometrics, 2003

Industry and academe are characterized by steadily increasing huge amounts of data with very different data structures. Both static and dynamic data contexts need to be addressed. A new generic, flexible and comprehensive general data-modelling concept is needed to cope with these demands. During the past 20 years, object-oriented programming (OOP) has become a de facto industry standard of how programming tasks should be defined and carried out in the context of deterministic data modelling. We present here a first framework of analogous ideas for multivariate data analysis. A new strategy, object-oriented data modelling (OODM), is proposed which is invariant with respect to the specific data structures and the practical data context. We present a first delineation of metaprinciples, ideas and stimulants for tomorrow's possible development paths of modelling, in which the fundamental data analysis unit is the generalized`PLS object' in the OOP sense. The key novel aspect concerns inter-object information transfer, facilitated by`root-sum-of-squares averaging' (RSSA), which uses w loading weights as between-object transfer agents. These features allow a powerful generalization beyond multiblock as well as hierarchical bilinear modelling to be laid out. The present part I outlines a first framework for the new data-modelling approach, while part II forms a complementing catalogue of specific options and possibilities when implementing the new principles.

A "Relational Green Card" Supporting Data Modeling in IS 2002

2009

No individual subject area in IS 2002 impacts more aspects of computing theory or profes- sional preparation than data modeling. For more than four decades the bedrock of data model- ing has been the relational data model. There are numerous extensions, variations and imple- mentations of this theory but its core remains the central anchor in the practice of data-driven analysis and design. Like most theoretical foundations that have spawned application devel- opment tools and methodologies much of the pure theory of the relational model is obscured by necessary choices of syntax and implementation features that in many cases complicate if not defy a student's grasp of the theory. This is compounded by the progression from one tool or syntax to another as students traverse their computing curricula. This is a distillation of the relational data model compact enough to be easily committed to memory and robust enough to serve as the consistent reference to the relational paradigm...

Manipulating Data : Elements of the DATA Step Language

2001

In the SAS DATA step, you can manipulate data by instructing SAS what to do. However, SAS understands only instructions given in its own tongue. The DATA step language (SAS DSL) is simple and powerful, its syntax is crisp and highly readable, and it is easy to learn. In this presentation, we will try to introduce the basics of speaking SAS. Just like in any language, a valid SAS phrase contains meaningful expressions that follow an intelligible sequence. These two principal parts will be considered one at a time: 1. Expressions basic blocks from which statements are built: Constants VariablesArraysAssignment and SumOperatorsFunctions. 2. Control Flow the order of execution of instructions: Conditional execution-Branching-Repetition. The presentation should provide an idea about the overall structure and main building blocks of the language used in the SAS DATA step. Some aspects (functions, specific statements) will be touched just briefly as part of the big picture and covered in d...

Data model issues for object-oriented applications

ACM Transactions on Information Systems, 1987

Presented in this paper is the data model for ORION, a prototype database system that adds persistence and sharability to objects created and manipulated in object-oriented applications. The ORION data model consolidates and modifies a number of major concepts found in many object-oriented systems, such as objects, classes, class lattice, methods, and inheritance. These concepts are reviewed and three major enhancements to the conventional object-oriented data model, namely, schema evolution, composite objects, and versions, are elaborated upon. Schema evolution is the ability to dynamically make changes to the class definitions and the structure of the class lattice. Composite objects are recursive collections of exclusive components that are treated as units of storage, retrieval, and integrity enforcement. Versions are variations of the same object that are related by the history of their derivation. These enhancements are strongly motivated by the data management requirements of...

Better Metadata Through SAS® II: %SYSFUNC, PROC DATASETS, and Dictionary Tables

2015

SAS® provides a wealth of resources for users to create useful, attractive metadata tables, including PROC CONTENTS listing output (to ODS destinations), the PROC CONTENTS OUT= SAS data set, and PROC CONTENTS ODS Output Objects. This paper and presentation explore some less well-known resources to create metadata such as %SYSFUNC, PROC DATASETS, and Dictionary Tables. All these options in conjunction with the use of the EXCELXP (and new in 9.4 M2, the EXCEL) tagsets enable the creation of multi-tab metadata workbooks at the click of a mouse.