Multispektraalse ruumhajuvusmõõtja nõuded ja analüüs

The volume scattering function (VSF), which describes the angular distribution of light scattered from an incident beam, is a fundamental inherent optical property of the aquatic environment. Despite its fundamental nature, there is little known about the range of variability in the VSF in the aquatic environment. This is mainly because the measurements of the function are difficult to perform. A lot of currently used radiate transfer models are based on a very limited set of measurements, which are made over 20 years ago. For the correct calculations of the radiate transfer, it is essential to know the variations of the phase function. Instruments, which have previously been used for measuring VSF, were complicated, bulky and most importantly: they are not able to take measurements of the function in full angular range. The purpose of this document is to describe the system requirements specifications of a Multispectral Volume Scattering Meter (MVSM). Document describes a new instrument for measuring the volume scattering function of seawater and other natural waters across a hemispheric angle range. System requirements and analysis is put together following modern methodology and standards. The measurement principles implemented in the device, are based on static scatter approach. Photomultiplier tube (PMT) is used to detect scattering light at different angles. Device’s mechanistic approach involves a use of a special periscope prism and a novel light shadow method

Democratising data science : effective use of data by communities for civic participation, advocacy and action

PhD ThesisWe live in an age of data, where it is being collected and archived in tremendous volumes and at great velocity. Smart cities are a good example of how we generate and use data with the aim of improving the lives of citizens. Cities adopting more technologies and embedding them in the physical fabric of the city will drastically change the way decisions are made in the city, in addition to the way citizens interact with the city. Research to date has predominantly focused on engineering agendas or has narrowly focused on citizens’ participation as passive producers of data in the smart city. This thesis takes a more holistic approach by focusing on both the engineering problem-solving agenda and community problem-solving activities. Taking a participatory research approach, the thesis explores such a context through three case studies that involve the design, development and analysis of two Community Informatics (CI) systems. In addition to producing two open-source CI technologies (SenseMyStreet and Data:In Place) for active citizen participation, this study posits a Citizen Advocacy Framework and Community-Data Interaction (CDI) model as novel theoretical framings that enable researchers to discuss and design for the effective use of data by communities. Furthermore, this thesis provides a practical example of the use of CDI for supporting communities to take local action. This improved understanding of the relationship between data and communities demonstrates a better direction for future research and the design of CI technologies as they work towards democratising data science and enabling the effective use of data by communities for active civic participation, advocacy and action

Making Open Data Work for Civic Advocacy

The value of data in supporting citizen participation in processes of place-making and community building is widely recognised. While the open data movement now permits citizens to acquire governmental data relating to their communities, little to no effort is made to ensure that these datasets are accessible and interpretable by non-professionals. Through a series of community engagements spanning an 18-month period, we co-designed Data:In Place, an open source web tool which supports citizens in accessing, interpreting and making sense of open data. Leveraging visual map-based querying, citizens can access official statistics about their community, interrogate the data, and map their own data sources to create data visualisations. Reflecting on the participatory design process and the designed technology, we provide a framing to make open data work for civic advocacy

SenseMyStreet: Sensor Commissioning Toolkit for Communities

The rise of big data and smart sensing, with the promise of more educated and informed decisions, has fuelled a shift towards more data-driven decision-making in local and national government. However, we are observing a disconnect between the people who are affected by these decisions and their access to tools and resources to collect data in order to provide the needed evidence for change. To truly democratise this process and for citizens to become active prosumers of data, new mechanisms of citizen data production are needed. In this paper we report on a two-year ethnographic and iterative co-design process with the local community. This work encompassed the design, development and deployment of SenseMyStreet (SeMS), a bespoke sensor commissioning toolkit that enables citizens and community groups to use and commission a city's scientific-grade environmental monitors, determining where they will be located on their streets and collecting data to evidence hyper-local issues. Unlike prior research, which creates alternative data sources to contest city data, our toolkit helps integrate citizen commissioned data into the city datasets used by citizens and decision-makers. Reflecting on the design process and evaluating the ways people engaged with the digital tools of the toolkit, we highlight how commissioning can be configured to promote equity in the smart city, empower citizens to take ownership of issues and facilitate the creation of community networks that utilise the data for local benefit

Exploring the Role of Paradata in Digitally Supported Qualitative Co-Research

Academics and community organisations are increasingly adopting co-research practices where participants contribute to qualitative data collection, analysis, and dissemination. These qualitative practices can often lack transparency that can present a problem for stakeholders (such as funding agencies) who seek evidence of the rigour and accountability in these decision-making processes. When qualitative research is done digitally, paradata is available as interaction logs that reveal the underlying processes, such as the time spent engaging with different segments of an interview. In practice, paradata is seldom used to examine the decisions associated with undertaking qualitative research. This paper explores the role of paradata arising from a four-month engagement with a community-led charity that used a digital platform to support their qualitative co-research project. Through observations of platform use and reflective post-deployment interviews, our findings highlight examples of paradata generated through digital tools in qualitative research, e.g., listening coverage, engagement rate, thematic maps and data discards. From this, we contribute a conceptualisation of paradata and discuss its role in qualitative research to improve process transparency, enhance data sharing, and to create feedback loops with research participants

From Creating Spaces for Civic Discourse to Creating Resources for Action

In this paper, we investigate the role of technology to address the concerns of a civil society group carrying out community-level consultation on the allocation of £1 million of community funds. We explore issues of devolved decision-making through the evaluation of a sociodigital system designed to foster deliberative virtues. We describe the ways in which this group used our system in their consultation practices. Our findings highlight how they adopted our technology to privilege specific forms of expression, ascertain issues in their community, make use of and make sense of community data, and create resources for action within their existing practices. Based on related fieldwork we discuss the impacts of structuring and configuring tools for ‘talk-based’ consultation in order to turn attention to the potential pitfalls and prospects for designing civic technologies that create resources for action for civil society

Sisepositsioneerimine kasutades traadita kohtvõrgu kaardistamist koos järelprotsessimisega

Information about a person’s position is a valuable piece of context information on which many application and location services are based upon. In outdoor environments the Global Positioning System (GPS) and Assisted GPS (A-GPS) are widely used and they perform reasonably well, but they underperform when there is no clear access to the sky, i.e. in indoor environments. Most of the research conducted and solutions developed aim for real-time indoor positioning or personal tracking, but to the author’s knowledge there are not many studies on the subject of post- processing. Post-processing has many benefits over real-time solutions, like preserving battery life of a mobile device, leveraging bigger processing power, using more complex algorithms that cannot run on mobile devices, and ultimately getting better accuracy on a person’s movements tracks. In this thesis, an Indoor Positioning System (IPS) using WLAN fingerprinting with post- processing scheme is proposed. The system uses a large set of fingerprinted Received Signal Strength (RSS) collections obtained in the offline phase and references them in post-processing against data collected in the online phase. A series of field experiments have been conducted in University of Tartu’s Faculty of Mathematics and Computer Science building. The results show that with a post-processing scheme more computationally extensive algorithms can be used and better accuracy achieved than in real-time

Exploring the use of mobile phone data for domestic tourism trip analysis

status: publishe

Exploring the use of mobile phone data for domestic tourism trip analysis

In this work, we discuss how an existing algorithm to extract long-distance trips from mobile phone data (Janzen et al., 2016 a,b) can be supplemented with man-made heuristics to arrive at plausible domestic tourism trips. In total, we detect 18,380 domestic tourism trips from mobile phone data of 69,000 users sampled in 32 cities in France. By analysing temporal, spatial and social characteristics of the domestic tourism trips, we explore several possible directions for the use of mobile phone data when studying domestic tourism on a large scale. We show how temporal patterns of mobile phone use differ from baseline behaviour, how destinations of trips can algorithmically be derived, and how future research can integrate information on the activation of the social network. Our main contribution is that we describe current barriers and sketch direction for future research