Technological Spaces: An Initial Appraisal

In this paper, we propose a high level view of technological spaces (TS) and relations among these spaces. A technological space is a working context with a set of associated concepts, body of knowledge, tools, required skills, and possibilities. It is often associated to a given user community with shared know-how, educational support, common literature and even workshop and conference regular meetings. Although it is difficult to give a precise definition, some TSs can be easily identified, e.g. the XML TS, the DBMS TS, the abstract syntax TS, the meta-model (OMG/MDA) TS, etc. The purpose of our work is not to define an abstract theory of technological spaces, but to figure out how to work more efficiently by using the best possibilities of each technology. To do so, we need a basic understanding of the similarities and differences between various TSs, and also of the possible operational bridges that will allow transferring the results obtained in one TS to other TS. We hope that the presented industrial vision may help us putting forward the idea that there could be more cooperation than competition among alternative technologies. Furthermore, as the spectrum of such available technologies is rapidly broadening, the necessity to offer clear guidelines when choosing practical solutions to engineering problems is becoming a must, not only for teachers but for project leaders as well

SPARQL Query Mediation for Data Integration

The Semantic Web provides a set of promising technologies to make sophisticated data integration much easier, because data on the semantic Web is allowed to be connected by links and complex queries can be executed against the dataset of those linked data. Although the Semantic Web techniques offer RDF/OWL to support schematic mappings between diverse data sources, large-scale data integration is still severely hampered by various types of data-level semantic heterogeneity among the data sources. In the paper, we show that SPARQL queries that are intended to execute over multiple heterogeneous data sources can be mediated automatically

Ontology mapping: the state of the art

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mapping has beeb the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping

XML technologies in language documentation workflows

More and more programs use XML formats for internal data storage, not only for interchange. This includes both general-purpose tools like MS Office and OpenOffice/LibreOffice and specialized linguistic software such as ELAN, EXMARaLDA, FLEx, Speech Analyzer, Arbil, WeSay, SayMore and so on. Thus more and more linguistic data are being created in XML, not just convertible to XML. Although not ideal (verbosity, high processing time), XML formats have a number of benefits to boost workflow efficiency. Importantly, XML documents can be processed with XSL transforms to get new data, remaining still in the realm of XML (the XSL transforms themselves are also XML and can be transformed by other XSL...), displayed as HTML or published into PDF. Finally, there are now mature free native-XML databases like eXist-db and BaseX which offer the full cycle of operations in one application with browser-based interface: store existing documents, browse and query data, create and edit data online, apply XSLT to publish. I will illustrate this with examples of transformations we used in language documentation workflow to convert interlinear texts in Archi (East Caucasian) between various formats including OpenOffice and FLEx. A connected issue which will be addressed is the need for an interchange standard format for interlinear texts

Ontology-based data integration between clinical and research systems

Data from the electronic medical record comprise numerous structured but uncoded elements, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of relevant data elements and the creation of database jobs for extraction, transformation and loading (ETL) are challenging: With current methods such as data warehousing, it is not feasible to efficiently maintain and reuse semantically complex data extraction and trans-formation routines. We present an ontology-supported approach to overcome this challenge by making use of abstraction: Instead of defining ETL procedures at the database level, we use ontologies to organize and describe the medical concepts of both the source system and the target system. Instead of using unique, specifically developed SQL statements or ETL jobs, we define declarative transformation rules within ontologies and illustrate how these constructs can then be used to automatically generate SQL code to perform the desired ETL procedures. This demonstrates how a suitable level of abstraction may not only aid the interpretation of clinical data, but can also foster the reutilization of methods for un-locking it