## 5 Challenges and Future Work for SWE
### Realizing the Human Sensor Web and Integrating Social Networks with the Sensor Web  
Since 2004, new kinds of Web applications have been created. They are called Web 2.0 applications, because they are fundamentally different from the previous generation of Web applications (_i.e._, Web 1.0 ones). Web 2.0 applications build online social networks to inter-connect users, treat users as information \"_prosumers_\" (_provider- consumer_), enable them to create \"user-generated content\", and harness their collective intelligence for innovative applications [130]. Web 2.0 has revolutionized the way today's users interact with each other and share information on the Web.  
By looking at Web 2.0 applications which allow sharing of _geographic_ information, [PERSON] [131] coined the term Volunteered Geographic Information (VGI) and proposed to extend the notion of sensor networks by incorporating humans as sensors. Examples of such applications enable users to share information about their bird sightings (see _[[http://www.birdpost.com_](http://www.birdpost.com_)]([http://www.birdpost.com_](http://www.birdpost.com_))) or allow uploadingmeasured weather data to an online social network [132]. Other applications allow their users to contribute to earthquake science by either filling out a Web form about the intensities of shaking and damage caused by an earthquake [133] or by contributing the built-in accelerometer of one's computer to a national seismic sensor network [134]. Based on observations of flood events from the affected population, [PERSON] _et al._[135] develop methods for the quality assessment of such human generated observations for rapid loss estimation.  
Thereby, it can be distinguished between _human sensed observations_ (such as textual descriptions) and _human collected observations_ gathered by sensors which are carried by a human (e.g., measurements performed by smart phones). The aim of the _Human Sensor Web_[136] is to integrate those two kinds of human observations by utilizing the SWE framework of standards. An example for a Human Sensor Web application which incorporates SWE is a water availability monitoring system for improving the water supply in East Africa [116]. Challenges with regard to the Human Sensor Web are broad, ranging from the design of ergonomic user interfaces, stimulating incentives of people to participate in the Human Sensor Web, handling of human cognition and resulting uncertainties, ensuring security, privacy, and trust, as well as dealing with the unstructured information provided by human observers.  
Analyzing and utilizing the social connections between users of online social networking platforms to enhance the Sensor Web is another emerging research direction. New models and architectures need to be designed in order to build a social networking-based Sensor Web. New algorithms need to be developed in order to exploit the social networks' underlying social graphs to enhance the Sensor Web. For example, [PERSON] [137] discussed the long tail phenomenon of the Sensor Web, and developed GeoCENS [138], a SWE-based online social network allowing scientists to share their sensor data. Based on the GeoCENS social network graph, a geospatial folksonomy and a collaborative tagging system have been developed [139] that recommend sensors and datasets according to a user's geographical area of interest.