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Human activities continue to degrade oceanic, coastal and inland waters. The generational change in the role of society in actively looking after the health of water resources can be achieved through the expansion of ocean and water literacy in schools. The Network of European Blue Schools established under the EU4Ocean Coalition for Ocean Literacy has improved ocean and water literacy; however, this Network needs to grow and be supported. Here, we present ProBleu, a recently funded EU project that will expand and support the Network, partly through the use of citizen science. The core of the proposed methodology is facilitating school activities related to ocean and water literacy through funding calls to sustain and enrich current school activities, and kick-start and support new activities. The outcomes of the project are anticipated to have widespread and long-term impacts across society, and oceanic, coastal and inland water environments.

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided “expert” data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who wa

Virtual citizen science platforms allow non-scientists to take part in scientific research across a range of disciplines. What they ask of volunteers varies considerably in terms of task type, variety, user judgement required and user freedom, which has received little direct investigation. A study was performed with the Planet Four: Craters project to investigate the effect of task workflow design on both volunteer experience and the scientific results they produce. Participants’ feedback through questionnaire responses indicated a preference for interfaces providing greater autonomy and variety, with free-text responses suggesting that autonomy was the more important. This did not translate into improved performance however, with the most autonomous interface not resulting in significantly better performance in data volume, agreement or accuracy compared to other less autonomous interfaces. The interface with the least number of task types, variety and autonomy resulted in the greatest data coverage. Agreement, both between participants and with the expert equivalent, was significantly improved when the interface most directly afforded tasks that captured the required underlying data (i.e. crater position or diameter). The implications for the designers of virtual citizen science platforms is that they have a balancing act to perform, weighing up the importance of user satisfaction, the data needs of the science case and the resources that can be committed both in terms of time and data reduction.

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided “expert” data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who wa

Virtual citizen science platforms allow non-scientists to take part in scientific research across a range of disciplines. What they ask of volunteers varies considerably in terms of task type, variety, user judgement required and user freedom, which has received little direct investigation. A study was performed with the Planet Four: Craters project to investigate the effect of task workflow design on both volunteer experience and the scientific results they produce. Participants’ feedback through questionnaire responses indicated a preference for interfaces providing greater autonomy and variety, with free-text responses suggesting that autonomy was the more important. This did not translate into improved performance however, with the most autonomous interface not resulting in significantly better performance in data volume, agreement or accuracy compared to other less autonomous interfaces. The interface with the least number of task types, variety and autonomy resulted in the greatest data coverage. Agreement, both between participants and with the expert equivalent, was significantly improved when the interface most directly afforded tasks that captured the required underlying data (i.e. crater position or diameter). The implications for the designers of virtual citizen science platforms is that they have a balancing act to perform, weighing up the importance of user satisfaction, the data needs of the science case and the resources that can be committed both in terms of time and data reduction.

There has been a massive growth in the number of people who film and upload amateur footage of events to services such as Facebook and Youtube, or even stream live to services such as LiveStream. We present an exploratory study that investigates the potential of these spectators in creating footage en masse; in this case, during a live trial at a local marathon. We deployed a prototype app, RunSpotRun, as a technology probe to see what kinds of footage spectators would produce. We present an analysis of this footage in terms of its coverage, quality, and contents, and also discuss the implications for a) spectators enjoying the race, and b) extracting the stories of individual runners throughout the race. We conclude with a discussion of the challenges that remain for deploying such technology at a larger scale.

The growing interest in citizen science has resulted in a new range of digital tools that facilitate the interaction and communications between citizens and scientists. Considering the ever increasing number of applications that currently exist, it is surprising how little we know about how volunteers interact with these technologies, what they expect from them, and why these technologies succeed or fail. Aiming to address this gap, JCOM organized this special issue on the role of User Experience (UX) of digital technologies in citizen science which is the first to focus on the qualities and impacts of interface and user design within citizen science. Seven papers are included that highlight three key aspects of user-focused research and methodological approaches. In the first category, "design standards", the authors explore the applicability of existing standards, build and evaluate a set of guidelines to improve interactions with citizen science applications. In the second, "design methods", methodological approaches for getting user feedback, analysing user behaviour and exploring different interface designs modes are explored. Finally, "user experience in the physical and digital world" explores crossovers with other fields to improve our understanding of user experiences and demonstrate how design choices not only influence digital interactions but also shape interactions with the wider world.

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided “expert” data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who wa

Virtual citizen science platforms allow non-scientists to take part in scientific research across a range of disciplines. What they ask of volunteers varies considerably in terms of task type, variety, user judgement required and user freedom, which has received little direct investigation. A study was performed with the Planet Four: Craters project to investigate the effect of task workflow design on both volunteer experience and the scientific results they produce. Participants’ feedback through questionnaire responses indicated a preference for interfaces providing greater autonomy and variety, with free-text responses suggesting that autonomy was the more important. This did not translate into improved performance however, with the most autonomous interface not resulting in significantly better performance in data volume, agreement or accuracy compared to other less autonomous interfaces. The interface with the least number of task types, variety and autonomy resulted in the greatest data coverage. Agreement, both between participants and with the expert equivalent, was significantly improved when the interface most directly afforded tasks that captured the required underlying data (i.e. crater position or diameter). The implications for the designers of virtual citizen science platforms is that they have a balancing act to perform, weighing up the importance of user satisfaction, the data needs of the science case and the resources that can be committed both in terms of time and data reduction.

There has been a massive growth in the number of people who film and upload amateur footage of events to services such as Facebook and Youtube, or even stream live to services such as LiveStream. We present an exploratory study that investigates the potential of these spectators in creating footage en masse; in this case, during a live trial at a local marathon. We deployed a prototype app, RunSpotRun, as a technology probe to see what kinds of footage spectators would produce. We present an analysis of this footage in terms of its coverage, quality, and contents, and also discuss the implications for a) spectators enjoying the race, and b) extracting the stories of individual runners throughout the race. We conclude with a discussion of the challenges that remain for deploying such technology at a larger scale.

The growing interest in citizen science has resulted in a new range of digital tools that facilitate the interaction and communications between citizens and scientists. Considering the ever increasing number of applications that currently exist, it is surprising how little we know about how volunteers interact with these technologies, what they expect from them, and why these technologies succeed or fail. Aiming to address this gap, JCOM organized this special issue on the role of User Experience (UX) of digital technologies in citizen science which is the first to focus on the qualities and impacts of interface and user design within citizen science. Seven papers are included that highlight three key aspects of user-focused research and methodological approaches. In the first category, "design standards", the authors explore the applicability of existing standards, build and evaluate a set of guidelines to improve interactions with citizen science applications. In the second, "design methods", methodological approaches for getting user feedback, analysing user behaviour and exploring different interface designs modes are explored. Finally, "user experience in the physical and digital world" explores crossovers with other fields to improve our understanding of user experiences and demonstrate how design choices not only influence digital interactions but also shape interactions with the wider world.

Change detection in satellite images is a key concern of the Earth Observation field for environmental and climate change monitoring. Satellite images also provide important clues to both the past and present surface conditions of other planets, which cannot be validated on the ground. With the volume of satellite imagery continuing to grow, the inadequacy of computerised solutions to manage and process imagery to the required professional standard is of critical concern. Whilst studies find the crowd sourcing approach suitable for the counting of impact craters in single images, images of higher resolution contain a much wider range of features, and the performance of novices in identifying more complex features and detecting change, remains unknown. This paper presents a first step towards understanding whether novices can identify and annotate changes in different geomorphological features. A website was developed to enable visitors to flick between two images of the same location on Mars taken at different times and classify 1) if a surface feature changed and if so, 2) what feature had changed from a pre-defined list of six. Planetary scientists provided “expert” data against which classifications made by novices could be compared when the project subsequently went public. Whilst no significant difference was found in images identified with surface changes by expert and novices, results exhibited differences in consensus within and between experts and novices when asked to classify the type of change. Experts demonstrated higher levels of agreement in classification of changes as dust devil tracks, slope streaks and impact craters than other features, whilst the consensus of novices was consistent across feature types; furthermore, the level of consensus amongst regardless of feature type. These trends are secondary to the low levels of consensus found, regardless of feature type or classifier expertise. These findings demand the attention of researchers who wa

Virtual citizen science platforms allow non-scientists to take part in scientific research across a range of disciplines. What they ask of volunteers varies considerably in terms of task type, variety, user judgement required and user freedom, which has received little direct investigation. A study was performed with the Planet Four: Craters project to investigate the effect of task workflow design on both volunteer experience and the scientific results they produce. Participants’ feedback through questionnaire responses indicated a preference for interfaces providing greater autonomy and variety, with free-text responses suggesting that autonomy was the more important. This did not translate into improved performance however, with the most autonomous interface not resulting in significantly better performance in data volume, agreement or accuracy compared to other less autonomous interfaces. The interface with the least number of task types, variety and autonomy resulted in the greatest data coverage. Agreement, both between participants and with the expert equivalent, was significantly improved when the interface most directly afforded tasks that captured the required underlying data (i.e. crater position or diameter). The implications for the designers of virtual citizen science platforms is that they have a balancing act to perform, weighing up the importance of user satisfaction, the data needs of the science case and the resources that can be committed both in terms of time and data reduction.

There has been a massive growth in the number of people who film and upload amateur footage of events to services such as Facebook and Youtube, or even stream live to services such as LiveStream. We present an exploratory study that investigates the potential of these spectators in creating footage en masse; in this case, during a live trial at a local marathon. We deployed a prototype app, RunSpotRun, as a technology probe to see what kinds of footage spectators would produce. We present an analysis of this footage in terms of its coverage, quality, and contents, and also discuss the implications for a) spectators enjoying the race, and b) extracting the stories of individual runners throughout the race. We conclude with a discussion of the challenges that remain for deploying such technology at a larger scale.