Marin Dimitrov

SENTINEL: a semantic business process monitoring tool

Business Activity Monitoring (BAM) aims to support the real-time analysis of business processes in order to improve the speed and effectiveness of business operations. Providing a timely, integrated high-level view on the evolution and well-being of business activities within enterprises constitutes a highly valuable analytical tool for monitoring, managing and hopefully enhancing businesses. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. We argue that the fundamental problem is that moving between the business level and the IT level is insufficiently automated and suggest an extensive use of semantic technologies as a solution. In particular, we present SENTINEL a Semantic Business Process Monitoring tool that advances the state of the art in BAM by making extensive use of semantic technologies in order to support the integration and derivation of business level knowledge out of low-level audit trails generated by IT systems.

WSMO Studio --- A Semantic Web Services Modelling Environment for WSMO

The Web Service Modelling Ontology (WSMO) provides a unique, highly innovative perspective onto the Semantic Web Services domain. Robust and easy-to-use tools play crucial role for the adoption of any technological innovation and indeed the overall value of the innovation can be severely undermined by the lack of proper tools supporting it. In this paper we present a prototype of an integrated modelling environment that supports and elaborates the innovative WSMO perspective.

OntoMap: portal for upper-level ontologies

Currently the evaluation of the feasibility of general-purposeontologies and upper-level models is expensive mostly because oftechnical problems such as different representation formalisms andterminologies used. Additionally, there are no formal mappingsbetween the upper-level ontologies that could ease any kind ofstudies and comparisons. We present the OntoMap Project(http://www.OntoMap.org), a project with the pragmatic goal tofacilitate the access, understanding, and reuse of such resources.A semantic framework on the conceptual level is implemented that issmall and easy enough to be learned on-the-fly. We tried to designthe framework so that it captures most of the semantics usuallyencoded in upper-level models. Technically, OntoMap is a web-siteproviding access to several upper-level ontologies and manualmapping between them.

DataGraft: One-stop-shop for open data management

This paper introduces DataGraft (https://datagraft.net/) – a cloud-based platform for data transformation and publishing. DataGraft was developed to provide better and easier to use tools for data workers and developers (e.g. open data publishers, linked data developers, data scientists) who consider existing approaches to data transformation, hosting, and access too costly and technically complex. DataGraft offers an integrated, flexible, and reliable cloud-based solution for hosted open data management. Key features include flexible management of data transformations (e.g. interactive creation, execution, sharing, reuse) and reliable data hosting services. This paper provides an overview of DataGraft focusing on the rationale, key features and components, and evaluation.

DataGraft: Simplifying Open Data Publishing

In this demonstrator we introduce DataGraft – a platform for Open Data management. DataGraft provides data transformation, publishing and hosting capabilities that aim to simplify the data publishing lifecycle for data workers (i.e., Open Data publishers, Linked Data developers, data scientists). This demonstrator highlights the key features of DataGraft by exemplifying a data transformation and publishing use case with property-related data.

Adapting a Robust Multi-genre NE System for Automatic Content Extraction

Many current information extraction systems tend to be designed with particular applications and domains in mind. With the increasing need for robust language engineering tools which can handle a variety of language processing demands, we have used the GATE architecture to design MUSE - a system for named entity recognition and related tasks. In this paper, we address the issue of how this general-purpose system can be adapted for particular applications with minimal time and effort, and how the set of resources used can be adapted dynamically and automatically. We focus specifically on the challenges of the ACE (Automatic Content Extraction) entity detection and tracking task, and preliminary results show promising figures.

An Execution Engine for Semantic Business Processes

In this paper we present the architecture and design of an extended BPEL engine that implements the operational semantics of BPEL4SWS. BPEL4SWS is an extension of the BPEL language with support for Semantic Web Service concepts like mediation and semantic descriptions of activity implementations. We describe the basic communication scenarios of processes with services and the interaction between the engine components involved in the execution of BPEL4SWS processes. The presented prototype is based on the open source BPEL engine Apache ODE, features improved configurability and facilitates the definition of additional BPEL extensions with minimal development effort.

Semantic Technologies and Triplestores for Business Intelligence

The Semantic Web is the next generation Web of data, which extends the current Web with means to provide well-defined meaning of information and easily find, integrate and analyze relevant information from different sources. Semantic Databases, or triplestores, play a very important role in the realization of the Semantic Web vision, since they provide the means to integrate, store and query the vast amounts of metadata generated on the Semantic Web every day. This paper presents a brief overview of the Semantic Web goals and related standards, with a special focus on the advantages, design and performance factors for triplestores. Finally, the paper provides an overview of Business Intelligence related scenarios where Semantic Technologies and triplestores in particular provide valuable advantage and differentiation.

On-demand Text Analytics and Metadata Management with S4

Semantic technologies provide a new, promising approach for smart data management and analytics. At the same time, the adoption of an emerging technology is usually limited by factors such as its perceived complexity, cost and performance. Startups and mid-size businesses often have very limited resources to evaluate and prototype with emerging technologies, even if their potential for more efficient data management and analytics is significant. The Self-Service Semantic Suite (S4) provides an integrated platform for cloud-based text analytics and Linked Data management as-a-service, so that companies in the early stage of evaluating and adopting semantic technologies can easily access a full suite of semantic data management and text analytics capabilities for smart data analytics in various domains.

AnnoMarket – Multilingual Text Analytics at Scale on the Cloud

AnnoMarket is an open platform for cloud-based text analytics services and language resources acquisition. Providers of text analytics services and language resources can deploy and monetize their components via the platform, while users can utilize such available resources in multiple languages and in various domains in an on-demand, pay-as-you-go manner. The AnnoMarket platform is deployed on the Amazon Web Services cloud and it provides free text analytics and language acquisition services to the general public.