scholarly journals Ein Metadatenlabel für das semantische Sensorweb

2020 ◽  
Author(s):  
Anika Graupner
Keyword(s):  
Cloud Computing ◽  
World Wide Web ◽  
Sensor Network ◽  
Linked Data ◽  
World Wide ◽  
Sensor Data ◽  
Readable Form ◽  
Machine Readable ◽  
Machine Readable Form ◽  
New Machine

Deutsch: Das World Wide Web entwickelt sich zu einem semantischen Web. Daten werden mit Hilfe von Ontologien semantisch annotiert, um sie maschinenlesbar bereitzustellen. Zu diesen Daten zählen auch Sensordaten. Da die Anzahl an online zur Verfügung gestellten Sensordaten steigt, fällt es dem Nutzer immer schwerer, geeignete Daten zu finden. Die neuen Sensorbeschreibungen in Form von Ontologien werden in der folgenden Arbeit dazu eingesetzt, dem Nutzer die Suche wieder zu vereinfachen. Die Erfassung von Informationen aus den neuen maschinenlesbaren Beschreibungen kann für den Menschen schwierig sein. Daher wird das von GeoViQua ursprünglich für GEOSS entwickelte GEO Label dazu eingesetzt, auch visuelle Zusammenfassungen der Verfügbarkeit von Informationen in Sensorbeschreibungen bereitzustellen. Das Label besteht aus Facetten, die Auskunft über das Vorhandensein von Informationen wie Herstellerprofil, Benutzerfeedback und Qualitätsinformationen in Metadatendokumenten geben. In der vorliegenden Arbeit wird die 52 North Implementierung der Java GEO Label API um die Generierung von Labels basierend auf der Semantic Sensor Network Ontology (SSNO) und verbundenen Linked Data Ontologien erweitert. Zuvor werden aus diesen Ontologien Informationsquellen für die Facetten des Labels gesucht. Zudem wird die GEO Label API mit einem Serverless Cloud-Computing Anbieter zur Verfügung gestellt, wobei die Frage beantwortet wird, welche Cloud-Ressourcen für die Labelgenerierung notwendig sind. English: The World Wide Web is developing into a semantic web. Data are semantically annotated using ontologies to make them available in a machine-readable form. These data include also sensor data. As the amount of sensor data made available online increases, it becomes more difficult for users to find suitable data. The new sensor descriptions in form of ontologies will be used in the following work to simplify the search for users again. The acquisition of information from the new machine-readable descriptions may be difficult for humans. Therefore, the GEO Label, originally developed by GeoViQua for GEOSS, is used to provide visual summaries of the availability of information in sensor descriptions. The label consists of facets that provide information about the availability of information in metadata documents such as producer profile, user feedback and quality information. In this thesis the 52 North implementation of the Java GEO label API is extended by the generation of labels based on the Semantic Sensor Network Ontology (SSNO) and related Linked Data Ontologies. Prior to this, information sources for the facets of the label are searched for from these ontologies. In addition, the GEO Label API will be made available with a serverless cloud computing provider, whereby the question will be answered which cloud resources are necessary for label generation.

scholarly journals Subject Access to a Data Base of Library Holdings

1974 ◽  
Vol 7 (4) ◽  
pp. 267
Author(s):  
Alice S. Clark
Keyword(s):  
Public Service ◽  
Public Libraries ◽  
Ohio State University ◽  
State University ◽  
Complete Collection ◽  
Remote Locations ◽  
Readable Form ◽  
The Ohio State University ◽  
Machine Readable ◽  
Machine Readable Form

As more academic and public libraries have some form of bibliographic description of their complete collection available in machine-readable form, public service librarians are devising ways to use the information for better retrieval. Research at the Ohio State University tested user response to paper and COM output from selected areas of the shelflist. Results indicated users at remote locations found such lists helpful, with some indication that paper printout was more popular than microfiche.

scholarly journals Visualization of typed links in Linked Data

2017 ◽  
Vol 70 (2) ◽  
pp. 179-199 ◽  
Author(s):  
Georg Neubauer
Keyword(s):  
World Wide Web ◽  
Semantic Web ◽  
Information Visualization ◽  
Web Application ◽  
Linked Data ◽  
World Wide ◽  
Processing Data ◽  
The World ◽  
Web Of Data ◽  
Practical Guidelines

The main subject of the work is the visualization of typed links in Linked Data. The academic subjects relevant to the paper in general are the Semantic Web, the Web of Data and information visualization. The Semantic Web, invented by Tim Berners-Lee in 2001, was announced as an extension to the World Wide Web (Web 2.0). The actual area of investigation concerns the connectivity of information on the World Wide Web. To be able to explore such interconnections, visualizations are critical requirements as well as a major part of processing data in themselves. In the context of the Semantic Web, representation of information interrelations can be achieved using graphs. The aim of the article is to primarily describe the arrangement of Linked Data visualization concepts by establishing their principles in a theoretical approach. Putting design restrictions into context leads to practical guidelines. By describing the creation of two alternative visualizations of a commonly used web application representing Linked Data as network visualization, their compatibility was tested. The application-oriented part treats the design phase, its results, and future requirements of the project that can be derived from this test.

The relevance of terminologies for automatic abstracting

1982 ◽  
Vol 4 (4) ◽  
pp. 161-165
Author(s):  
Wolfgang Nedobity
Keyword(s):  
Scientific Literature ◽  
Relevant Information ◽  
Automatic Production ◽  
Readable Form ◽  
Automatic Abstracting ◽  
The One ◽  
Machine Readable ◽  
Machine Readable Form

The increased production and publication of professional and scientific literature makes it necessary that abstracts are pro duced in a quick, efficient and economical way. This can be achieved by the mechanization of abstracting. With the aid of computers, extracts can be produced of all kinds of texts which are available in machine-readable form. The main problem of this procedure is how to determine the key sentences of a text, i.e., the passages that contain the most relevant information. Various methods have been developed for this purpose; the one presented here is based on the fact that in order to convey relevant information, subject terminology is used. In many cases subject terminologies are now available in machine-reada ble form too and thus can be easily applied to the automatic production of abstracts.

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