Journal of Computing and Information Technology - CIT 20, 2012, 3, 167–173 167 doi:10.2498/cit.1002093 A Framework for Semantic Enrichment of Sensor Data Alexandra Moraru and Dunja Mladenic´ Artificial Intelligence Laboratory, J. Stefan Institute, Ljubljana, Slovenia The increased interest in sensing the environment in networks, which can improve knowledge ex- which we live has led to the deployment of thousands traction from sensor data streams and facilitate of sensors which can measure and report its status. In order to raise the impact that sensor networks can reasoning capabilities. have, improving the usability and accessibility of the Some of the directions adopted for achieving the measurements they provide is an important step. integration of semantic technologies and Sensor The problem addressed in this paper is that of enrichment Web are related to linked data (i.e. linked sen- of sensor descriptions and measurements in order to [ ][ ][ ]) provide richer data, i.e., data containing more meaning. sor data 2 3 4 , or to semantic annotation and We propose a framework for automatizing the process of composition of web services [5]. More general semantically enriching sensor descriptions and measure- directions that can be identified in building the ments with the purpose of improving the usability and Semantic Sensor Web are: accessibility of sensor data. • Automatically annotate and enrich sensor Keywords: semantic web, linked data, sensor web data, by providing semantic metadata about spatiotemporal and thematic properties. • Publish annotated sensor data using shared 1. Introduction vocabularies and standard schemas, in order to facilitate accessibility and enable sensor discovery. Sensors are materials or devices which change • their (conductive) properties according to a phys- Apply reasoning mechanisms on semanti- ical stimulus. These sensors can be attached cally enriched sensor data for solving prob- to more complex devices, called sensor nodes, lems, such as sensor composition, event de- which can have computing and communication tection and network management. capabilities. More and more sensor nodes are The enrichment of data generally refers to adding embedded into physical objects used in every- information, annotation or additional features day life, ranging from pacemakers, transporta- to the data by means of computation or by tion cargos to electrical appliances. Further- pulling information from external sources (e.g., more, communication links can be established the web, databases, etc.). Semantic enrichment between these objects, organized into wired and of sensor data denotes the process of associating wireless networks called sensor networks or semantic tags to initial sensor descriptions and sensor webs in the case when web accessibil- measurements. These tags represent concepts, ity is provided [1]. properties and relationships from an ontology and are used to describe the metadata associ- Using semantic technologies for enriching sen- ( sor descriptions and measurements in scalable ated to sensor data i.e., measurement capabil- ities, observed phenomena, spatial properties, and heterogeneous sensor networks are intended )[ ] as a solution for better interoperability and eas- etc. 6 . ier maintenance. Through semantic descrip- Making sensor data publicly available enables tions it is possible to provide context for sensor the development of new and useful applications. 168 A Framework for Semantic Enrichment of Sensor Data The methods for publishing sensor data can ing thereby advanced query and reasoning. Re- vary from standardized web services, such as source Description Framework attributes (RDFa) OGC’s Sensor Observation Service (SOS) to format is adopted as an annotation language for application specific methods, as the ones used two demonstrative applications that are using by web platforms, such as Pachube1 or Sensor- also several Sensor Web Enablement standards. pedia2. However, such methods require prior Moreover, rule-based reasoning is applied for knowledge of the infrastructures used, while determining specific weather conditions, such publishing semantically annotated sensor data, as freezing or blizzard. The idea of semantic following the linked data principles, would en- annotation is taken further by Wei and Barnaghi able better accessibility. Moreover, when sup- [9] by using Linked Open Data (LOD) resources ported for integration with existing knowledge, for annotation that brings access to knowledge it would increase also the usability of published already represented and eliminates the risks of data. creating redundant data. Reasoning, in general, is the process of produc- A recent trend for making sensor descriptions ing new beliefs from a collection of believed and measurements available on the Web is to propositions. It is strongly related to the field publish them on LOD cloud. The advantages of logic and in the context of ontologies the and challenges of Linked Sensor Data are dis- logical formalisms are provided by a family of cussed by Keler and Janowicz [4] as a solution representation languages known as Description for better sensor data accessibility without intro- Logic (DL)[7]. Describing sensors data using ducing very high complexity. The paper stresses ontology terms enables reasoning mechanisms out the importance of finding the appropriate that can be used to infer new knowledge for links between different datasets from LOD and further enrichment of data or to solve complex proposes a semiautomatic way for generating problems. them. We propose a framework for semantic enrich- Other research in the direction of publishing ment of sensor descriptions and measurements, sensor data as linked data include [2] and [3]. with the purposes of automatizing the process Patni et al. [2] were the first to publish a large of translating existing sensor descriptions into dataset of sensor descriptions and measurements, semantic descriptions and enabling semantic by first representing it in Observations and Mea- querying over sensor measurements. The pri- surements (O&M) standard and then converting mary focus of this work is on the first general it to Resource Description Framework (RDF) direction that we mentioned above, that of anno- format. The linked sensor data is using a sensor tating and enriching sensor data using semantic ontology schema based on the concepts from technologies. Next, we take into consideration O&M and the external links are made only linked data as a method of publishing annotated for the location attribute, using the Geonames sensor data, while the aspects of applying rea- dataset. Barnaghi and Presser [3] propose a soning mechanism on sensor data are briefly platform for publishing linked sensor data fol- mentioned as possible future directions. lowing the four principles proposed by Berners- Lee [10]. The platform offers an interface for publishing linked senor data without requiring 2. Related Work from its user a related technical background. However, the user is requested to manually en- ter relevant keywords that describe the sensors Sheth et al. [8] propose the Semantic Sensor ( ) for obtaining a list of suggested concepts from Web SSW as a solution for the problem of on-line repositories. “too much data and not enough knowledge” that appeared with the rapid development of sensor In our work we propose methods for automa- networks. In their view, the SSW represents tizing the translation of simple sensor descrip- semantically annotated sensor data with spa- tions into semantic sensor descriptions and for tial, temporal and thematic metadata, facilitat- processing sensor measurements for extracting 1 http://www.pachube.com/ 2 http://www.sensorpedia.com/ A Framework for Semantic Enrichment of Sensor Data 169 more meaningful values for the properties ob- • domain layer, defining the domain concepts served. We adopt a strategy of analysis of sensor related to a specific scenario where the sen- measurements before building the semantic rep- sor networks are used (e.g., floods, land- resentations and we use tools capable of dealing slides, oil spills, etc). with large amounts of sensor data. The description languages are used in repre- senting ontologies. These are named ontology 3. Semantic Enrichment of Sensor Data languages and are included in the larger family of formal languages. Ontology languages en- The requirements for building the SSW refer code the domain knowledge and the rules used to knowledge representation, description lan- for reasoning on that knowledge. guages and semantic reasoners. Two of the most common used languages for A fundamental definition of knowledge repre- knowledge representation are Web Ontology sentation is given by Davis et al. [10] as “a sur- Language (OWL) and RDF. Both languages are rogate, a substitute for the thing itself”, seen as a W3C standardized and different versions are de- model. One of the categories of knowledge rep- fined, presenting varying levels of expressivity. resentation appropriate for the model required RDF is a data model based on subject-predicate- is represented by ontologies. object triples and uses XML for specifying syn- A detailed survey of semantic specification of tax. RDF Schema introduces semantics to a sensor networks is provided in [12],where eleven RDF data model; it describes concepts, such as sensor network ontologies are analyzed. The classes, properties of classes and hierarchies of ontologies developed for modeling sensor net- these. However, RDF and RDF Schema sup-