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�ݺ�ߣshows by User: svanlaere / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: svanlaere / Tue, 22 Sep 2015 10:45:21 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: svanlaere Mapping of Terminology Standards, a Way for Interoperability (Position Paper) /slideshow/mapping-of-terminology-standards-a-way-for-interoperability-position-paper/53056993 ehst15presentation-150922104521-lva1-app6892
Standards in medicine are essential to enable communication between healthcare providers. These standards can be used either for exchanging information, or for coding and documenting the health status of a patient. In this position paper we focus on the latter, namely terminology standards. However, the multidisciplinary field of medicine makes use of many different standards. We propose to invest in an interoperable electronic health record (EHR) that can be understood by all different levels of health care providers independent of the kind of terminology standard they use. To make this record interoperable, we suggest mapping standards in order to make uniform communication possible. We suggest using mappings between a reference terminology (RT) and other terminology standards. By using this approach we limit the number of mappings that have to be provided. The Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) can be used as a RT, because of its extensive character and the preserved semantics towards other terminology standards. Moreover, a lot of mappings from SNOMED CT to other standards are already defined previously.]]>
Standards in medicine are essential to enable communication between healthcare providers. These standards can be used either for exchanging information, or for coding and documenting the health status of a patient. In this position paper we focus on the latter, namely terminology standards. However, the multidisciplinary field of medicine makes use of many different standards. We propose to invest in an interoperable electronic health record (EHR) that can be understood by all different levels of health care providers independent of the kind of terminology standard they use. To make this record interoperable, we suggest mapping standards in order to make uniform communication possible. We suggest using mappings between a reference terminology (RT) and other terminology standards. By using this approach we limit the number of mappings that have to be provided. The Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) can be used as a RT, because of its extensive character and the preserved semantics towards other terminology standards. Moreover, a lot of mappings from SNOMED CT to other standards are already defined previously.]]> Tue, 22 Sep 2015 10:45:21 GMT /slideshow/mapping-of-terminology-standards-a-way-for-interoperability-position-paper/53056993 svanlaere@slideshare.net(svanlaere) Mapping of Terminology Standards, a Way for Interoperability (Position Paper) svanlaere Standards in medicine are essential to enable communication between healthcare providers. These standards can be used either for exchanging information, or for coding and documenting the health status of a patient. In this position paper we focus on the latter, namely terminology standards. However, the multidisciplinary field of medicine makes use of many different standards. We propose to invest in an interoperable electronic health record (EHR) that can be understood by all different levels of health care providers independent of the kind of terminology standard they use. To make this record interoperable, we suggest mapping standards in order to make uniform communication possible. We suggest using mappings between a reference terminology (RT) and other terminology standards. By using this approach we limit the number of mappings that have to be provided. The Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) can be used as a RT, because of its extensive character and the preserved semantics towards other terminology standards. Moreover, a lot of mappings from SNOMED CT to other standards are already defined previously. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ehst15presentation-150922104521-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Standards in medicine are essential to enable communication between healthcare providers. These standards can be used either for exchanging information, or for coding and documenting the health status of a patient. In this position paper we focus on the latter, namely terminology standards. However, the multidisciplinary field of medicine makes use of many different standards. We propose to invest in an interoperable electronic health record (EHR) that can be understood by all different levels of health care providers independent of the kind of terminology standard they use. To make this record interoperable, we suggest mapping standards in order to make uniform communication possible. We suggest using mappings between a reference terminology (RT) and other terminology standards. By using this approach we limit the number of mappings that have to be provided. The Systematized Nomenclature of Medicine, Clinical Terms (SNOMED CT) can be used as a RT, because of its extensive character and the preserved semantics towards other terminology standards. Moreover, a lot of mappings from SNOMED CT to other standards are already defined previously.

Mapping of Terminology Standards, a Way for Interoperability (Position Paper) from Sven Van Laere

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0 A Method for Detecting Behavior-Based User Profiles in Collaborative Ontology Engineering /slideshow/odba2014/41073608 odbase2014-141103160925-conversion-gate02
Ontology engineering is far from trivial and most collaborative methods and tools start from a predefined set of rules, stakeholders can have in the ontology engineering process. We, however, believe that the different types of user behavior are not known a priori and depend on the ontology engineering project. The detection of such user profiles based on unsupervised learning allows finding roles and responsibilities along peers in a collaborative setting. In this paper, we present a method for automatic detection of user profiles in a collaborative ontology engineering environment by means of the K-means clustering algorithm only by looking at the type of interactions a user makes. In this paper we use the GOSPL ontology engineering tool and method to demonstrate this method. The data used to demonstrate the method stems from two ontology engineering projects involving respectively 42 and 36 users.]]>
Ontology engineering is far from trivial and most collaborative methods and tools start from a predefined set of rules, stakeholders can have in the ontology engineering process. We, however, believe that the different types of user behavior are not known a priori and depend on the ontology engineering project. The detection of such user profiles based on unsupervised learning allows finding roles and responsibilities along peers in a collaborative setting. In this paper, we present a method for automatic detection of user profiles in a collaborative ontology engineering environment by means of the K-means clustering algorithm only by looking at the type of interactions a user makes. In this paper we use the GOSPL ontology engineering tool and method to demonstrate this method. The data used to demonstrate the method stems from two ontology engineering projects involving respectively 42 and 36 users.]]> Mon, 03 Nov 2014 16:09:25 GMT /slideshow/odba2014/41073608 svanlaere@slideshare.net(svanlaere) A Method for Detecting Behavior-Based User Profiles in Collaborative Ontology Engineering svanlaere Ontology engineering is far from trivial and most collaborative methods and tools start from a predefined set of rules, stakeholders can have in the ontology engineering process. We, however, believe that the different types of user behavior are not known a priori and depend on the ontology engineering project. The detection of such user profiles based on unsupervised learning allows finding roles and responsibilities along peers in a collaborative setting. In this paper, we present a method for automatic detection of user profiles in a collaborative ontology engineering environment by means of the K-means clustering algorithm only by looking at the type of interactions a user makes. In this paper we use the GOSPL ontology engineering tool and method to demonstrate this method. The data used to demonstrate the method stems from two ontology engineering projects involving respectively 42 and 36 users. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/odbase2014-141103160925-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Ontology engineering is far from trivial and most collaborative methods and tools start from a predefined set of rules, stakeholders can have in the ontology engineering process. We, however, believe that the different types of user behavior are not known a priori and depend on the ontology engineering project. The detection of such user profiles based on unsupervised learning allows finding roles and responsibilities along peers in a collaborative setting. In this paper, we present a method for automatic detection of user profiles in a collaborative ontology engineering environment by means of the K-means clustering algorithm only by looking at the type of interactions a user makes. In this paper we use the GOSPL ontology engineering tool and method to demonstrate this method. The data used to demonstrate the method stems from two ontology engineering projects involving respectively 42 and 36 users.

A Method for Detecting Behavior-Based User Profiles in Collaborative Ontology Engineering from Sven Van Laere

]]> 667 1 https://cdn.slidesharecdn.com/ss_thumbnails/odbase2014-141103160925-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post

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0 https://cdn.slidesharecdn.com/profile-photo-svanlaere-48x48.jpg?cb=1523422773 At present, I work as a teaching assistant at the VUB (campus Jette). Previously I studied a master in Web & Information Systems Engineering/Computer Science at the Vrije Universiteit Brussel, Belgium. Before doing this master, I successfully fulfilled my bachelor in applied informatics. My master thesis was on finding user profiles during the process of ontology engineering. This research was done at STARLab at the VUB and considers to generate a profile for users participating in the semantic process of ontology engineering. As a bachelor I also did an internship at Centrum voor Ondernemen (CvO). There I had to design a workflow encouraging tool to better support their customers. The https://cdn.slidesharecdn.com/ss_thumbnails/ehst15presentation-150922104521-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/mapping-of-terminology-standards-a-way-for-interoperability-position-paper/53056993 Mapping of Terminology... https://cdn.slidesharecdn.com/ss_thumbnails/odbase2014-141103160925-conversion-gate02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/odba2014/41073608 A Method for Detecting...