Serverless GEO Labels for the Semantic Sensor Web

As the amount of sensor data made available online increases, it becomes more difficult for users to identify useful datasets. Semantic web technologies improve discovery with meaningful ontologies, but the decision of suitability remains with the users. The GEO label provides a visual summary of the standardised metadata to aid users in this process. This work presents novel rules for deriving the information for the GEO label's multiple facets, such as user feedback or quality information, based on the Semantic Sensor Network Ontology and related ontologies. It enhances an existing implementation of the GEO label API to generate labels for resources of the Semantic Sensor Web. The prototype is deployed to serverless cloud infrastructures. We find that serverless GEO label generation is capable of handling two evaluation scenarios for concurrent users and burst generation. More real-world semantic sensor descriptions and an integration into large scale discovery platforms are needed to develop the presented solutions further.

Pemantauan Kualitas Udara Terintegrasi dengan Semantic Web Of Thing

Abstrak: Udara merupakan salah satu sumber daya alam yang paling penting bagi keberadaan makhluk hidup di bumi ini. Semua organisme hidup membutuhkan kualitas udara yang baik bebas dari gas berbahaya untuk melanjutkan hidup mereka. Beberapa organisasi telah membuat sistem monitoring dengan struktur data yang berbeda tanpa adanya standar penyamaan. Di sisi lain, manusia masih membutuhkan waktu untuk menafsirkan data-data sensor untuk mendapatkan informasi. Linked Data merupakan metode untuk merepresentasikan dan menghubungkan data terstruktur pada web. Data terstruktur tersebut diintegrasikan dengan Semantic Sensor Web (SSW) yang dipublikasikan pada beberapa format sehingga mudah dibaca mesin dan dapat dihubungkan ke data terstruktur lainnya. Kemudian, untuk menyajikan data yang aktual, sistem monitoring didesain untuk menerima data secara terus-menerus, diquery secara real-time dan dibagikan melalui sosial media. Kata kunci: Linked Data, Pemantauan Kualitas Udara, Semantic Web, Sosial Media. Abstract: Air is one of the most essential natural resources for the existence and survival of the entire life on this planet. all living organisms need good quality of air which is free of harmful gases to continue their life. Some organizations have set up monitoring systems with different data structures without an equalization standard. On the other hand, humans still need time to interpret sensor data to get information. Linked Data is a method for representing and connecting structured data on the web. The structured data is integrated with the Semantic Sensor Web (SSW) which is published in several formats so that it is easy to read and can be connected to other structured data. Then, to present the actual data, the monitoring system is designed to receive data continuously, queried in real time and shared through social media Keywords: Air Quality Monitoring, Linked Data, Semantic Web, Social Media

Serverless GEO Labels for the Semantic Sensor Web

As the amount of sensor data made available online increases, it becomes more difficult for users to identify useful datasets. Semantic web technologies improve discovery with meaningful ontologies, but the decision of suitability remains with the users. The GEO label provides a visual summary of the standardised metadata to aid users in this process. This work presents novel rules for deriving the information for the GEO label's multiple facets, such as user feedback or quality information, based on the Semantic Sensor Network Ontology and related ontologies. It enhances an existing implementation of the GEO label API to generate labels for resources of the Semantic Sensor Web. The prototype is deployed to serverless cloud infrastructures. We find that serverless GEO label generation is capable of handling two evaluation scenarios for concurrent users and burst generation. More real-world semantic sensor descriptions and an integration into large scale discovery platforms are needed to develop the presented solutions further.

A Semantic Sensor Web Architecture in the Internet of Things

The Internet of Things (IoT) vision is connecting uniquely identifiable devices to the internet, best described through ontologies. Furthermore, new emerging technologies such as wireless sensor networks (WSN) are recognized as essential enabling component of the IoT today. Hence, the interest is to provide linked sensor data through the web either following the semantic web enablement (SWE) standard or the linked data approach. Likewise, a need exists to explore those data for potential hidden knowledge through data mining techniques utilized by a domain ontology. Following that rationale, a new lightweight IoT architecture has been developed. It supports linking sensors, other devices and people via a single web by mean of a device-person-activity (DPA) ontology. The architecture is validated by mean of three rich-in-semantic services: contextual data mining over WSN, semantic WSN web enablement, and linked WSN data. The architecture could be easily extensible to capture semantics of input sensor data from other domains as well.