Legislation of direct-to-consumer genetic testing in Europe: a fragmented regulatory landscape

Despite the increasing availability of direct-to-consumer (DTC) genetic testing, it is currently unclear how such services are regulated in Europe, due to the lack of EU or national legislation specifically addressing this issue. In this article, we provide an overview of laws that could potentially impact the regulation of DTC genetic testing in 26 European countries, namely Austria, Belgium, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, the Netherlands and the United Kingdom. Emphasis is placed on provisions relating to medical supervision, genetic counselling and informed consent. Our results indicate that currently there is a wide spectrum of laws regarding genetic testing in Europe. There are countries (e.g. France and Germany) which essentially ban DTC genetic testing, while in others (e.g. Luxembourg and Poland) DTC genetic testing may only be restricted by general laws, usually regarding health care services and patients’ rights

Semantic input/output matching for waste processing in industrial symbiosis

Industrial symbiosis (IS) is a subdiscipline of Industrial Ecology that aims to bring together companies from different sectors to share resources, namely energy, materials, and water. The main goal of IS is to improve resource (materials, waste, energy) efficiency and lead to mutual environmental, financial and social benefits to participants.In this paper we present a semantic approach for IS input/output matching. This approach is based on knowledge modelling and ontologies.Ontologies are used to model all resources - waste, water, energy - along with details about their composition, characteristics (chemical and physical) and tacit knowledge about their flow.The input/output matching algorithm presented enables the valorisation of resources through industrial symbiosis networks. © 2014 Elsevier Ltd

Semantic approach for pre-assessment of environmental indicators in Industrial Symbiosis

© 2013 Elsevier Ltd. All rights reserved. Abstract Industrial Symbiosis (IS) is a growingly accepted paradigm for processing waste into material, energy and water with benefits to participants measured by economic, environmental and social gains. Despite of some attempts to quantify them no unified metrics or methods for calculating concomitant indicators have been proposed. This paper presents a systemisation of IS relevant environmental metrics and a semantic approach based on knowledge modelling using ontologies to facilitate "a priori" calculation of respective indicators. The approach and metrics are presented and verified with a case study

Towards a Re-Usable Ontology for Waste Processing

The potential of ontologies and knowledge modeling in process systems engineering has been realised and researched, efforts were directed to create semantic models representing the process industry domain. In this paper we present a re-usable ontology that consists of two main classification modules: i) Waste and ii) Processing Technology. The ontology has been developed, validated and used for processing of waste within the framework of Industrial Symbiosis. It supports a web platform that enables Industrial Symbiosis practice. The ontology is used for collecting information, user registration and semantic input output matching. © 2014 Elsevier B.V

Towards a Re-Usable Ontology for Waste Processing

The number of ontologies available today, more than 10,000 as identified by dedicated search engines , is a good indicator of the progress made so far. Ontologies are developed for and used in several applications ranging from knowledge representation and semantic search up to data integration and web service discovery (Cheung, Cheung & Kwok 2012)(Trokanas, Cecelja & Raafat 2013, Raafat et al. 2013b)(Raafat et al. 2013a). Much of recent ontology development efforts have been reported in the domain of Process Systems Engineering (give references from review). It is the fact that ontologies are by definition conceptualisations that are supposed to be shared and reused (Gruber 1993, Gruber 1995). Ontology reuse is a practical and useful approach for knowledge engineers. It has the potential to reduce the cost of developing ontology from scratch (24), as well as promote interoperability among applications (6). In addition, many of the existing ontologies cover similar or overlapping domains (14). Ontology reuse is also part of many of existing frameworks and established methodologies (Noy, McGuinness 2001, López et al. 1999) for ontology development. However, by reviewing the literature (Bock et al. 2010, Brandt et al. 2008, Fernandes et al. 2011, Giménez et al. 2008), it became apparent that ontology reuse is a seldom occurring task. Researchers have identified a lack in robust (27) and pragmatic (24) methods for evaluating and identifying ontologies for reuse. This paper presents a metric for the evaluation of ontologies for reuse. The metric account for ontology metadata such as the datatypes, external resources, terminology and languages used for modelling. It also accounts for structural characteristics of ontologies such as size, breadth and width of the evaluated ontologies. All the available information is translated into vectors which are consequently compared. The resulting similarity scores for each aspect are aggregated and normalised into a single metric ranging between [0,1]. The metric has been tested and verified using experiments for the development of an ontology for the domain of Industrial Symbiosis. Bock, C., Zha, X., Suh, H. & Lee, J. 2010, "Ontological product modeling for collaborative design", Advanced Engineering Informatics, vol. 24, no. 4, pp. 510-524. Brandt, S.C., Morbach, J., Miatidis, M., Theißen, M., Jarke, M. & Marquardt, W. 2008, "An ontology-based approach to knowledge management in design processes", Computers & Chemical Engineering, vol. 32, no. 1, pp. 320-342. Cheung, C.F., Cheung, C. & Kwok, S. 2012, "A knowledge-based customization system for supply chain integration", Expert Systems with Applications, vol. 39, no. 4, pp. 3906-3924. Fernandes, R.P., Grosse, I.R., Krishnamurty, S., Witherell, P. & Wileden, J.C. 2011, "Semantic methods supporting engineering design innovation", Advanced Engineering Informatics, vol. 25, no. 2, pp. 185-192. Giménez, D.M., Vegetti, M., Leone, H.P. & Henning, G.P. 2008, "PRoduct ONTOlogy: Defining product-related concepts for logistics planning activities", Computers in Industry, vol. 59, no. 2, pp. 231-241. Gruber, T.R. 1995, "Toward principles for the design of ontologies used for knowledge sharing", International journal of human computer studies, vol. 43, no. 5, pp. 907-928. Gruber, T.R. 1993, "A translation approach to portable ontology specifications", Knowledge acquisition, vol. 5, no. 2, pp. 199-220. López, M.F., Gómez-Pérez, A., Sierra, J.P. & Sierra, A.P. 1999, "Building a chemical ontology using methontology and the ontology design environment", Intelligent Systems and their Applications, IEEE, vol. 14, no. 1, pp. 37-46. Noy, N.F. & McGuinness, D.L. 2001, "Ontology development 101: A guide to creating your first ontology", . Raafat, T., Trokanas, N., Cecelja, F. & Bimi, X. 2013a, "An Ontological Approach Towards Enabling Processing Technologies Participation in Industrial Symbiosis", Computers & Chemical Engineering, . Raafat, T., Trokanas, N., Cecelja, F. & Bimi, X. 2013b, "An ontological approach towards enabling processing technologies participation in industrial symbiosis", Computers & Chemical Engineering, vol. 59, no. 0, pp. 33-46. Trokanas, N., Cecelja, F. & Raafat, T. 2013, "Semantic approach for pre-assessment of environmental indicators in Industrial Symbiosis", Journal of Cleaner Production,

Semantic input/output matching for waste processing in industrial symbiosis

Industrial symbiosis (IS) is a subdiscipline of Industrial Ecology that aims to bring together companies from different sectors to share resources, namely energy, materials, and water. The main goal of IS is to improve resource (materials, waste, energy) efficiency and lead to mutual environmental, financial and social benefits to participants.In this paper we present a semantic approach for IS input/output matching. This approach is based on knowledge modelling and ontologies.Ontologies are used to model all resources - waste, water, energy - along with details about their composition, characteristics (chemical and physical) and tacit knowledge about their flow.The input/output matching algorithm presented enables the valorisation of resources through industrial symbiosis networks. © 2014 Elsevier Ltd

Ontology Evaluation for Reuse in the Domain of Process Systems Engineering

Ontologies are a useful tool for knowledge representation, sharing and reuse. Although the number of available ontologies is increasing, the concomitant reuse activities are not following respectively. This is particularly true in the domain of Process Systems Engineering where the ontology development has been proven to be a challenging task and respective reusability is at its infancy. This paper presents a framework for evaluation of ontology for reuse. The proposed framework benefits from information about ontologies, such as terminology and ontology structure, to calculate a compatibility metric of ontology suitability for reuse and hence integration. The framework was demonstrated using a Chemical and Process Engineering case