A transactions pattern for structuring unstructured corporate information in enterprise applications

It is known that 80-85% of all corporate information remains unstructured. As such, many enterprises rely on information systems that cause them to risk transactions that are based on lack of information (errors of omission) or misleading information (errors of commission). To address this concern, the fundamental business concept of monetary transactions is extended to include qualitative business concepts. A Transaction Model (TM) is accordingly identified that provides a structure for these unstructured but vital aspects of business transactions. By highlighting how unstructured information can be integrated into transactions, the TM provides businesses with a much more balanced view of the transactions they engage in or to discover novel transactions that they might have otherwise missed. A simple example is provided that illustrates this integration and reveals a key missing element. This discovery points to a transactions pattern that can be used to ensure that all the parties (or agents) in a transaction are identified, as well as capturing unstructured and structured information into a coherent framework. In support of the TM as a pattern, more examples of its use in a variety of domains are given. A number of enterprise applications are suggested such as in multi-agent systems, document text capture, and knowledge management.</p

Proceedings of the First International Workshop on Mashup Personal Learning Environments

Wild, F., Kalz, M., & Palmér, M. (Eds.) (2008). Proceedings of the First International Workshop on Mashup Personal Learning Environments (MUPPLE08). September, 17, 2008, Maastricht, The Netherlands: CEUR Workshop Proceedings, ISSN 1613-0073. Available at http://ceur-ws.org/Vol-388.The work on this publication has been sponsored by the TENCompetence Integrated Project (funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org]) and partly sponsored by the LTfLL project (funded by the European Commission's 7th Framework Programme, priority ISCT. Contract 212578 [http://www.ltfll-project.org

Template Based Semantic Integration: From Legacy Archaeological Datasets to Linked Data

The online dissemination of datasets to accompany site monographs and summary documentation is becoming common practice within the archaeology domain. Since the legacy database schemas involved are often created on a per-site basis, cross searching or reusing this data remains difficult. Employing an integrating ontology, such as the CIDOC CRM, is one step towards resolving these issues. However, this has tended to require computing specialists with detailed knowledge of the ontologies involved. Results are presented from a collaborative project between computer scientists and archaeologists that provided light weight tools to make it easier for non-specialists to publish Linked Data. Applications developed for the STELLAR project were applied by archaeologists to major excavation datasets and the resulting output was published as Linked Data, conforming to the CIDOC CRM ontology. The template-based Extract Transform Load method is described. Reflections on the experience of using the template-based tools are discussed, together with practical issues including the need for terminology alignment and licensing consideration

The EMPRISES pan-European Framework:

There is a need for further integration of information systems globally for tackling Serious Organised Economic Crime (SOEC). Taking Europe as the illustration, and levering existing pan-EU (European Union) systems such as Europol's SIENA and the FIU.NET as well as national systems, further steps can be taken to provide a more coherent and coordinated approach for detecting and deterring SOEC. This aim is achievable through the EMPRISES framework, which adds value to national, SIENA and FIU.NET systems by increasing the effectiveness of communication across Europe. EMPRISES would introduce an agreed common language (taxonomy) of SOEC, including multi-lingual support. Moreover, by enriching the taxonomy with current business tools and analysis techniques through the SOEC Architecture that EMPRISES embodies, the illegitimate businesses of SOEC can be monitored and combatted

Active Algorithms: Sociomaterial Spaces in the E-learning and Digital Cultures MOOC

This paper will explore two examples from the design, structure and implementation of the ‘E-learning and Digital Cultures’ Massive Open Online Course (MOOC) from the University of Edinburgh in partnership with Coursera. This five week long course (known as the EDCMOOC) was delivered twice in 2013, and is considered an atypical MOOC in its utilisation of both the Coursera platform and a range of social media and open access materials. The combination of distributed and aggregated structure will be highlighted, examining the arrangement of course material on the Coursera platform and student responses in social media. This paper will suggest that a dominant instrumentalist view of technology limits considerations of these systems to merely enabling or inhibiting educational aims. The subsequent discussion will suggest that sociomaterial theory offers a valuable framework for considering how educational spaces are produced through relational practices between humans and non-humans. An analysis of You Tube and a bespoke blog aggregator will show how the algorithmic properties of these systems perform functions that cannot be reduced to the intentionality of either the teachers using these systems, or the authors who create the software, thus constituting a complex sociomaterial educational enactment

Implementation of a Training Courses Recommender System based on k-means algorithm

Providing the right professional training courses for employees is a critical issue for organizations as well as employees. Its necessity stemmed out on the fulfillment of the organization and employees need. Thus, building a recommender system that would help in the decision making process and planning of the training course offered by organizations. This can be performed using various techniques and methodologies, where the most important one is data mining. Data mining is a process of looking for specific patterns and knowledge from large databases and carrying out predictions for outputs. Therefore, this project aims to build a web-based application for predicting appropriate training recommenders for Princess Norah University employees based on their education and professional information. This helps the university in suggesting the most optimal training recommender for employees, which in turn can enhance their performance and develop their career and working levels. Employees’ data was gathered from the Human Resource of the university and then clustered using the WEKA program to find the centroids of clusters to be then used in the developed application. The developed web-based application is used to suggest the most suitable training recommender for each employee. Results demonstrate that the developed web-based application effectively suggests the most appropriate training courses for employees based on the previously taken courses, evaluation of courses and probability for promotion. Furthermore, this web-based application can be used for describing the appropriate training courses for new employees based on their levels. The achieved accuracy of the developed system was 73.33%

A Transaction-oriented architecture for enterprise systems

Many enterprises risk business transactions based on information systems that are incomplete or misleading, given that 80-85% of all corporate information remains outside of their processing scope. It highlights that the bulk of information is too unstructured for these systems to process, but must be taken into account if those systems are to provide effective support. Computer technology nonetheless continues to become more and more predominant, illustrated by SAP A.G. recognising that 65-70% of the world's transactions are run using their technology. Using SAP as an illustrative case study, and by bringing in the benefits of technologies such as Service-Oriented Architecture (SOA), Business Process Management (BPM), Enterprise Architecture Frameworks (EA) and Conceptual Structures, a practical roadmap is identified to a Transaction-Oriented Architecture (TOA) that is predicated on the Transaction Concept. This concept builds upon the Resources-Events-Agents (REA) modelling pattern that is close to business reality. Enterprise systems can thus better incorporate that missing 80-85% of hitherto too-unstructured information thereby allowing enterprise systems vendors such as SAP, their competitors, customers, suppliers and partners to do an ever better job with the world's transactions