Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

Organizational learning II: Theory, method and practice

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

One of the most influential books ever written on the development of project management-fully revised Handbook of Project-Based Management, Fourth Edition has been thoroughly updated to cover the recent developments in the project management field to help deliver the organization's strategy, regardless of the industry. This new edition focuses on the role of the global Project Manager, and how to embark on a successful project in the digital age. Rodney Turner, editor of the International Journal of Project Management, explains how to employ the proven structured approach that he has popularized over the last four decades.

/pdf/the-handbook-of-project-based-management-355epmx7jq.pdf

The handbook of project-based management

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. 

Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content.

New in this edition: 


Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below

Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more




Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS 
Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more 
Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems

Table of Contents

1?What Is The Semantic Web?
2?Semantic Modeling
3?RDF - The Basis of the Semantic Web
4?SPARQL - The Query Language for RDF
5?Semantic Web Application Architecture
6?RDF And Inferencing
7?RDF Schema Language
8?RDFS-Plus
9?SKOS - the Simple Knowledge Organization System
10?Ontologies in the Wild: Linked Open Data and the Open Graph Project
11?Basic OWL
12?Counting and Sets In OWL 
13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry
14?Good and Bad Modeling Practices 
15?OWL 2.0 Levels and Logic
16?Conclusions
17?Frequently Asked Questions

Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

Understanding IT organization is essential for ensuring a successful transformation phase in IT outsourcing deals We present a model of IT organization, a methodology for deriving it - based both on ethnography and data mining - and a suite of tools for representing and visualizing the model, and to help design changes to bring the organization from its current (AS-IS) state to a desired (TO-BE) state, along with tools for comparing models of organizations based on qualities and characteristics that are expected to have a bearing on the success of the IT transformation step

Understanding IT organizations

The Future of the Internet- Concepts- Ontology in Computer Science- Knowledge Representation in Description Logic- RDF and RDF Schema- OWL- Rule Languages- Semantic Web Services- Technologies- Methods for Ontology Development- Ontology Sources- Semantic Web Software Tools- Applications- Software Agents- Semantic Desktop- Ontology Applications in Art- Geospatial Semantic Web

Semantic Web: Concepts, Technologies and Applications

The "semantic Web" community poses a new nonfunctional requirement for Web applications. In order to secure interoperability and allow autonomous agent interaction, software for the Web will be required to provide machine processable ontologies. We understand that the responsibility, not only for making explicit this requirement, but also to implement the ontology, belongs to requirements engineers. As such, we see the ontology of a Web application as a sub-product of the requirements engineering activity. In this tutorial we survey the basic principles behind ontologies as they are being implemented and used by the semantic Web community today. Those include ontology languages, tools and construction methods. We focus on a process for ontology construction centered on the concept of application languages. This concept is rooted on a representation scheme called the language extended lexicon (LEL). We demonstrate our approach with examples in which we implement machine processable ontologies in the DAML+OIL language. We finalize with a discussion of today's research issues in ontology engineering, including ontology evolution, integration and validation.

Ontology as a requirements engineering product

Video processing applications are notably data intense, time, and resource consuming. Upfront infrastructure investment is usually high, specially when dealing with applications where time-to- market is a crucial requirement, e.g., breaking news and journalism. Such infrastructures are often inefficient, because due to demand variations, resources may end up idle a good portion of the time. In this paper, we propose the Split&Merge architecture for high performance video processing, a generalization of the MapReduce paradigm that rationalizes the use of resources by exploring on demand computing. To illustrate the approach, we discuss an implementation of the Split&Merge architecture, that reduces video encoding times to fixed duration, independently of the input size of the video file, by using dynamic resource provisioning in the Cloud.

/pdf/an-architecture-for-distributed-high-performance-video-585avzymax.pdf

Karin Breitman

Papers

Understanding IT organizations

Semantic Web: Concepts, Technologies and Applications

Ontology as a requirements engineering product

An Architecture for Distributed High Performance Video Processing in the Cloud

Uncertainty quantification through the Monte Carlo method in a cloud computing setting