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23:33 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2015

Usability Engineering For Successful Open Citizen Science

Citizen science can be explained as the engagement by nonprofessional scientists in collecting data, analyzing data, developing technologies and the publication of these on a voluntary basis. In a majority of citizen science projects the data to be collected is geospatial and is being presented on maps. If the data is about environmental observations, this approach is often referred to as participatory sensing. A novel approach in this field is to equip citizens with DIY-environmental sensor stations and to establish citizen driven sensor networks. This approach leads to better data coverage but also contains motivational aspects, as citizens build up their own devices. Most existing DIY sensor stations are not fully open in terms of source code, data collection, hardware, educational documents or extensibility for other platforms. That's why they lack transparency for the user, e.g. for scientists, who are interested in the data or citizens who want to understand the algorithms. The SenseBox project started at the Institute for Geoinformatics, University of M?nster, and is an ongoing open citizen science project. Based on open hardware components (Arduino microcontrollers and compatible sensors) citizens build their own Internet of Things enabled sensor stations to collect environmental data (temperature, humidity, air pressure, loudness, VIS-light, UV-light). The data is being published as open data and visualized on a web based platform, the OpenSenseMap (OSeM). An educational edition of the SenseBox and didactical material are being introduced into high schools, where students learn to code, measure environmental phenomena and work scientifically. The whole source code is open source, instructions are being published as open educational resources (OER) and models for a 3D-printed waterproof case are available as open source as well. In a first project phase, around 50 SenseBox stations were deployed to citizens and schools in Germany. Some participants had problems in the building and registration process of the SenseBox, others disconnected their SenseBox after some time. In this paper we want to investigate, if usability problems were the cause of the low success rate and how the motivation of citizen scientist can be preserved to ensure long-term data collection. In a user study we plan to evaluate the workflow of (a) building up the SenseBox station, (b) register it on OSeM and (c) verify the communication. Therefore we invite non professionals to our institute for an observed usability study in a controlled environment. A number of ten attendees is sufficient to improve usability significantly. As a basis, the current state of our online tutorials, containing text documents with illustrations and examples, are provided to the participants. Sessions are video recorded, and participants are being interviewed afterwards. In a next step, the results are analyzed to enhance project documentation and hardware design to a more user friendly version. The enhanced construction kits are being rolled out and provided to a new group of citizen scientists. In a final step, a questionnaire is used as an evaluation for the user study and the motivation of the participants.
  • Published: 2015
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
26:06 FOSS4G, Open Source Geospatial Foundation (OSGeo) English 2015

OpenSenseMap - a Citizen Science Platform For Publishing and Exploring Sensor Data as Open Data

A plethora of map-based citizen science sensor platforms for different use-cases already exist. They provide cheap, preconfigured, plug and playable hardware and software solutions. Using data from multiple platforms and resources can be a challenging task in respect of discovering, exploring, downloading and converting. In this paper we present a one-stop-shop for sensor data that tries to tackle these problems. Therefore a basic data schema capable of metadata is established that allows publishing generic sensor platforms and sensor data. For exploration the OpenSenseMap, a web platform is implemented based on common web standards. Citizen science is often called “public participation in scientific research” [1] and describes the engagement by non-professional scientists in collecting and analyzing data, decision making, developing technology and publication of these on a voluntary basis. The idea of involving citizen in scientific projects is not new. Two examples are the Christmas Bird Count [2] and the Galaxy Zoo project, which identifies and classifies galaxies on sky images taken at the Sloan Digital Sky Survey. An always discussed concern about citizen science is data quality [3]. Due to limited knowledge of the volunteers and missing or questionable metadata, scientists often characterise data collected by citizens as valueless. In the beginning citizen science was connected with activities where humans were used as sensors [4]. Nevertheless, the scientific community is becoming more and more interested in citizen science today and citizen science projects are part of complex research projects [5]; e.g. ambient environment monitoring. We think two reasons boosted this trend. First, citizens are getting more interested in their environment and its effects on daily life. Also many popular citizen science projects are related to ambient environment monitoring and topics around smart cities; e.g. the AirQualityEgg project and the SmartCitizen project. Second, the vast development of technology makes it easy and affordable to build the necessary tools for a citizen science project. Microcontroller platforms like Arduino or tessel.io and the quality and price of sensors make it nowadays easy to build sensor platforms, which are easy to use and affordable in price. By using open-source hardware and software, it is easier - especially for traditional non-technical research communities- to create custom sensor platforms. Furthermore, the web makes it easier to share and discuss geospatial data at global scale. This work describes the requirements, design and implementation of the OpenSenseMap. OpenSenseMap is following the clientserver model [6] and its complete application stack is implemented in JavaScript. It describes the basic components and the underlying data model. All components are using open-source technology and are published under an open-source license too. The RESTful service is the heart of OpenSenseMap and implements the data publish and data retrieval functions. Developers may use it to build custom applications around OpenSenseMap or integrate OpenSenseMap into existing projects. The NodeJS application runs its own web server and implements the different HTTP request types. The OpenSenseMap concept is being evaluated with an technical and a user survey.
  • Published: 2015
  • Publisher: FOSS4G, Open Source Geospatial Foundation (OSGeo)
  • Language: English
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