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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.

There is a growing acknowledgement that citizen observatories, and other forms of citizen-generated data, have a significant role in tracking progress towards the Sustainable Development Goals. This is evident in the increasing number of Sustainable Development Goals’ indicators for which such data are already being used and in the high-level recognition of the potential role that citizen science can play. In this article, we argue that networks of citizen observatories will help realise this potential. Drawing on the Cos4Cloud project as an example, we highlight how such networks can make citizen-generated data more interoperable and accessible (among other qualities), increasing their impact and usefulness. Furthermore, we highlight other, perhaps overlooked, advantages of citizen observatories and citizen-generated data: educating and informing citizen scientists about the Sustainable Development Goals and co-creating solutions to the global challenges they address

This book is the culmination of the COST Action CA15212 Citizen Science to Promote Creativity, Scientific Literacy, and Innovation throughout Europe. It represents the final stage of a shared journey taken over the last 4 years. During this relatively short period, our citizen science practices and perspectives have rapidly evolved. In this chapter we discuss what we have learnt about the recent past of citizen science and what we expect and hope for the future.

Interest in the formal representation of citizen science comes from portals, platforms, and catalogues of citizen science projects; scientists using citizen science data for their research; and funding agencies and governments interested in the impact of citizen science initiatives. Having a common understanding and representation of citizen science projects, their participants, and their outcomes is key to enabling seamless knowledge and data sharing. In this chapter, we provide a conceptual model comprised of the core citizen science concepts with which projects and data can be described in a standardised manner, focusing on the description of the participants and their activities. The conceptual model is the outcome of a working group from the COST Action CA15212 Citizen Science to Promote Creativity, Scientific Literacy, and Innovation throughout Europe, established to improve data standardisation and interoperability in citizen science activities. It utilises past models and contributes to current standardisation efforts, such as the Public Participation in Scientific Research (PPSR) Common Conceptual Model and the Open Geospatial Consortium (OGC) standards. Its design is intended to fulfil the needs of different stakeholders, as illustrated by several case studies which demonstrate the model’s applicability

Citizen science is one of the eight priorities ofthe European Open Science Agenda, togetherwith the creation of the European OpenScience Cloud (EOSC). Citizen Science yieldsin a community that is continuouslyexpanding. This represents large-scalechallenges for citizen observatories whofacilitate an efficient capture, identification,validation, stewardship and storage of largevolumes of citizen science data. Within thisframework, the Horizon 2020 project,Co-designed Citizen Observatories Servicesfor the European Open Science Cloud(Cos4Cloud), aspires to integrate citizenobservatories in the EOSC ecosystem,developing essential research and technologyto co-design and prototype innovative services

The European-Commission—funded project ‘Citclops’ (Citizens’ observatory for coast and ocean optical monitoring) developed methods, tools and sensors, which can be used by citizens to monitor natural waters, with a strong focus on long-term data series related to environmental sciences. The new sensors, based on optical technologies, respond to a number of scientific, technical and societal objectives, ranging from more precise monitoring of key environmental descriptors of the aquatic environment (water colour, transparency and fluorescence) to an improved management of data collected with citizen participation. The sensors were tested, calibrated, integrated on several platforms, scientifically validated and demonstrated in the field. The new methods and tools were tested in a citizen-science context. The general conclusion is that citizens are valuable contributors in quality and quantity to the objective of collecting, integrating and analysing fragmented and diverse environmental data. An integration of these data into data-analysis tools has a large potential to support authoritative monitoring and decision-making. In this paper, the project’s objectives, results, technical achievements and lessons learned are presented

Citizens observatories are a new concept of research infrastructure (http://www.citizen-obs.eu/). They are platforms that integrate the latest information technology to digitally connect citizens, and support the discipline known as Citizen Science through the improvement of the ability of environment observation. Additionally, citizens observatories are an excellent framework to develop innovative teaching methodologies and projects and broaden participation in Science, Technology, Engineering and Mathematics (STEM) disciplines. This potential for education comes from the opportunities offered by the active collaboration of citizens, with different levels and roles in shared processes of knowledge creation. In this contribution the authors will analyze the role of citizen observatories (and how people can collaborate with different participation roles) in two case studies: (1) the European project Citclops (Citizens¿ Observatory for Coast and Ocean Optical Monitoring, http://www.citclops.eu/), which introduced an innovative concept for water-quality monitoring, and developed tools and sensors that can be used by citizens to help oceanographers and limnologists in monitoring natural waters; and (2) the platform for monitoring biodiversity Natusfera (http://natusfera.gbif.es)

Much can be at stake depending on the choice of words used to describe citizen science, because terminology impacts how knowledge is developed. Citizen science is a quickly evolving field that is mobilizing people’s involvement in information development, social action and justice, and large-scale information gathering. Currently, a wide variety of terms and expressions are being used to refer to the concept of ‘citizen science’ and its practitioners. Here, we explore these terms to help provide guidance for the future growth of this field. We do this by reviewing the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology; discussing what citizen science is and reviewing related terms; and providing a collection of potential terms and definitions for ‘citizen science’ and people participating in citizen science projects. This collection of terms was generated primarily from the broad knowledge base and on-the-ground experience of the authors, by recognizing the potential issues associated with various terms. While our examples may not be systematic or exhaustive, they are intended to be suggestive and invitational of future consideration. In our collective experience with citizen science projects, no single term is appropriate for all contexts. In a given citizen science project, we suggest that terms should be chosen carefully and their usage explained; direct communication with participants about how terminology affects them and what they would prefer to be called also should occur. We further recommend that a more systematic study of terminology trends in citizen science be conducted.

As the need for sustainable development practices around the world continues to grow, it has become imperative for citizens to become actively engaged in the global transition. By evaluating data collected from various global programs, researchers are able to identify strategies and challenges in implementing civic engagement initiatives. Analyzing the Role of Citizen Science in Modern Research focuses on analyzing data on current initiatives and best practices in citizen engagement and education programs across various disciplines. Highlighting emergent research and application techniques within citizen science initiatives, this publication appeals to academicians, researchers, policy makers, government officials, technology developers, advanced-level students and program developers interested in launching or improving citizen science programs across the globe

Marine ecosystems are characterized by an extraordinary mix of human activities, e.g.: tourism, fishing and industry (petrochemical plants and aquaculture, etc.). New policies concerning environmental resources should have citizens' support and consider public attitudes from the beginning. The development of these policies is becoming more complex with larger datasets required to support the assessment of impacts on whole ecosystems over long periods of time. Access to the considerable funding needed for data collection is limited, so it is important to look at new cost‐effective ways of obtaining and processing environmental data. Citizen science has the potential to increase the knowledge base about marine ecosystems through the participation of people with no specific scientific training to collect and analyze large data sets. In this contribution we introduce the new, open citizen science platform called >Natusfera> (natusfera.gbif.es). Inspired by the existing platform iNaturalist, one of the main goals of this new platform is to facilitate the participation of any community interested in collaborating in environmental monitoring, independently of the community size and the capabilities of their members. To do so, the Natusfera development has been conceived to break three main potential barriers: (1) Technological barriers. Communities will not require having ICT expertise in the group to run Natusfera and to adapt it to their particular interest. (2) Knowledge barriers. Communities may start participating even if they do not have the expertise to identify/interpret their own observations. (3) Linguistic barriers. The users will be able to choose freely the language to participate and exchange information in Natusfera. At present the platform is available in five languages: English, Spanish, Catalan, Galician and Euskera. The platform is now being adapted to support as many languages as possible using a system for collaborative translation. As examples of mana

Marine processes are observed with sensors from both the ground and space over large spatio-temporal scales. Citizen-based contributions can fill observational gaps and increase environmental stewardship amongst the public. For this purpose, tools and methods for citizen science need to (1) complement existing datasets; and (2) be affordable, while appealing to different user and developer groups. In this article, tools and methods developed in the 7th Framework Programme of European Union (EU FP 7) funded project Citclops (citizens’ observatories for coast and ocean optical monitoring) are reviewed. Tools range from a stand-alone smartphone app to devices with Arduino and 3-D printing, and hence are attractive to a diversity of users; from the general public to more specified maker- and open labware movements. Standardization to common water quality parameters and methods allows long-term storage in regular marine data repositories, such as SeaDataNet and EMODnet, thereby providing open data access. Due to the given intercomparability to existing remote sensing datasets, these tools are ready to complement the marine datapool. In the future, such combined satellite and citizen observations may set measurements by the engaged public in a larger context and hence increase their individual meaning. In a wider sense, a synoptic use can support research, management authorities, and societies at large.

Marine processes are observed with sensors from both the ground and space over large spatio-temporal scales. Citizen-based contributions can fill observational gaps and increase environmental stewardship amongst the public. For this purpose, tools and methods for citizen science need to (1) complement existing datasets; and (2) be affordable, while appealing to different user and developer groups. In this article, tools and methods developed in the 7th Framework Programme of European Union (EU FP 7) funded project Citclops (citizens’ observatories for coast and ocean optical monitoring) are reviewed. Tools range from a stand-alone smartphone app to devices with Arduino and 3-D printing, and hence are attractive to a diversity of users; from the general public to more specified maker- and open labware movements. Standardization to common water quality parameters and methods allows long-term storage in regular marine data repositories, such as SeaDataNet and EMODnet, thereby providing open data access. Due to the given intercomparability to existing remote sensing datasets, these tools are ready to complement the marine datapool. In the future, such combined satellite and citizen observations may set measurements by the engaged public in a larger context and hence increase their individual meaning. In a wider sense, a synoptic use can support research, management authorities, and societies at large.

Marine processes are observed with sensors from both the ground and space over large spatio-temporal scales. Citizen-based contributions can fill observational gaps and increase environmental stewardship amongst the public. For this purpose, tools and methods for citizen science need to (1) complement existing datasets; and (2) be affordable, while appealing to different user and developer groups. In this article, tools and methods developed in the 7th Framework Programme of European Union (EU FP 7) funded project Citclops (citizens’ observatories for coast and ocean optical monitoring) are reviewed. Tools range from a stand-alone smartphone app to devices with Arduino and 3-D printing, and hence are attractive to a diversity of users; from the general public to more specified maker- and open labware movements. Standardization to common water quality parameters and methods allows long-term storage in regular marine data repositories, such as SeaDataNet and EMODnet, thereby providing open data access. Due to the given intercomparability to existing remote sensing datasets, these tools are ready to complement the marine datapool. In the future, such combined satellite and citizen observations may set measurements by the engaged public in a larger context and hence increase their individual meaning. In a wider sense, a synoptic use can support research, management authorities, and societies at large

[EN] Water is the most important resource for living on planet Earth, covering more than 70% of its surface. The oceans represent more than 97% of the planet total water and they are where more than the 99.5% of the living beings are concentrated. A great number of ecosystems depend on the health of these oceans; their study and protection are necessary. Large datasets over long periods of time and over wide geographical areas can be required to assess the health of aquatic ecosystems. The funding needed for data collection is considerable and limited, so it is important to look at new cost-effective ways of obtaining and processing marine environmental data. The feasible solution at present is to develop observational infrastructures that may increase significantly the conventional sampling capabilities. In this study we promote to achieve this solution with the implementation of Citizen Observatories, based on volunteer participation. Citizen observatories are platforms that integrate the latest information technologies to digitally connect citizens, improving observation skills for developing a new type of research known as Citizen Science. Citizen science has the potential to increase the knowledge of the environment, and aquatic ecosystems in particular, through the use of people with no specific scientific training to collect and analyze large data sets. We believe that citizen science based tools —open source software coupled with low-cost do-it-yourself hardware— can help to close the gap between science and citizens in the oceanographic field. As the public is actively engaged in the analysis of data, the research also provides a strong avenue for public education. This is the objective of this thesis, to demonstrate how open source software and low-cost do-it-yourself hardware are effectively applied to oceanographic research and how can it develop into citizen science. We analyze four different scenarios where this idea is demonstrated: an example of using open, [CAT] L’aigua és el recurs més important per la vida al planeta Terra, cobrint m és del 70% de la seva superfície. Els oceans representen m és del 70% de tota l’aigua del planeta, i és on estan concentrats més del 99.5% dels éssers vius. Un gran nombre d’ecosistemes depenen de la salut d’aquests oceans; el seu estudi i protecció són necessaris. Grans conjunts de dades durant llargs períodes de temps i al llarg d’amples àrees geogràfiques poden ser necessaris per avaluar la salut dels ecosistemes aquàtics. El finançament necessari per aquesta recol·lecció de dades és considerable però limitat, i per tant és important trobar noves formes m és rendibles d’obtenir i processar dades mediambientals marines. La solució factible actualment és la de desenvolupar infraestructures observacionals que puguin incrementar significativament les capacitats de mostreig convencionals. En aquest estudi promovem que es pot assolir aquesta solució amb la implementació d’Observatoris Ciutadans, basats en la participació de voluntaris. Els observatoris ciutadans són plataformes que integren les últimes tecnologies de la informació amb ciutadans digitalment connectats, millorant les capacitats d’observació, per desenvolupar un nou tipus de recerca coneguda com a Ciència Ciutadana. La ciència ciutadana té el potencial d’incrementar el coneixement del medi ambient, i dels ecosistemes aquàtics en particular, mitjançant l’ús de persones sense coneixement científic específic per recollir i analitzar grans conjunts de dades. Creiem que les eines basades en ciència ciutadana —programari lliure juntament amb maquinari de baix cost i del tipus “fes-ho tu mateix” (do-it-yourself en anglès)— poden ajudar a apropar la ciència del camp oceanogràfic als ciutadans. A mesura que el gran públic participa activament en l’anàlisi de dades, la recerca esdevé també una nova via d’educació pública. Aquest és l’objectiu d’aquesta tesis, demostrar com el programari lliure i el maquinari de baix cost “fes-ho tu mateix” s

Marine processes are observed with sensors from both the ground and space over large spatio-temporal scales. Citizen-based contributions can fill observational gaps and increase environmental stewardship amongst the public. For this purpose, tools and methods for citizen science need to (1) complement existing datasets; and (2) be affordable, while appealing to different user and developer groups. In this article, tools and methods developed in the 7th Framework Programme of European Union (EU FP 7) funded project Citclops (citizens’ observatories for coast and ocean optical monitoring) are reviewed. Tools range from a stand-alone smartphone app to devices with Arduino and 3-D printing, and hence are attractive to a diversity of users; from the general public to more specified maker- and open labware movements. Standardization to common water quality parameters and methods allows long-term storage in regular marine data repositories, such as SeaDataNet and EMODnet, thereby providing open data access. Due to the given intercomparability to existing remote sensing datasets, these tools are ready to complement the marine datapool. In the future, such combined satellite and citizen observations may set measurements by the engaged public in a larger context and hence increase their individual meaning. In a wider sense, a synoptic use can support research, management authorities, and societies at large.

La consulta íntegra de la tesi, inclosos els articles no comunicats públicament per drets d'autor, es pot realitzar prèvia petició a l'Arxiu de la UPC, Water is the most important resource for living on planet Earth, covering more than 70% of its surface. The oceans represent more than 97% of the planet total water and they are where more than the 99.5% of the living beings are concentrated. A great number of ecosystems depend on the health of these oceans; their study and protection are necessary. Large datasets over long periods of time and over wide geographical areas can be required to assess the health of aquatic ecosystems. The funding needed for data collection is considerable and limited, so it is important to look at new cost-effective ways of obtaining and processing marine environmental data. The feasible solution at present is to develop observational infrastructures that may increase significantly the conventional sampling capabilities. In this study we promote to achieve this solution with the implementation of Citizen Observatories, based on volunteer participation. Citizen observatories are platforms that integrate the latest information technologies to digitally connect citizens, improving observation skills for developing a new type of research known as Citizen Science. Citizen science has the potential to increase the knowledge of the environment, and aquatic ecosystems in particular, through the use of people with no specific scientific training to collect and analyze large data sets. We believe that citizen science based tools -open source software coupled with low-cost do-it-yourself hardware- can help to close the gap between science and citizens in the oceanographic field. As the public is actively engaged in the analysis of data, the research also provides a strong avenue for public education. This is the objective of this thesis, to demonstrate how open source software and low-cost do-it-yourself hardware are effectively applied to oceanographic research and how can it develop into citizen science. We analyze four different scenarios where this idea is demonstrated: an example of using ope, L’aigua és el recurs més important per la vida al planeta Terra, cobrint més del 70% de la seva superfície. Els oceans representen més del 70% de tota l'aigua del planeta, i és on estan concentrats més del 99.5% dels éssers vius. Un gran nombre d'ecosistemes depenen de la salut d'aquests oceans; el seu estudi i protecció són necessaris. Grans conjunts de dades durant llargs períodes de temps i al llarg d’amples àrees geogràfiques poden ser necessaris per avaluar la salut dels ecosistemes aquàtics. El finançament necessari per aquesta recol·lecció de dades és considerable però limitat, i per tant és important trobar noves formes més rendibles d’obtenir i processar dades mediambientals marines. La solució factible actualment és la de desenvolupar infraestructures observacionals que puguin incrementar significativament les capacitats de mostreig convencionals. En aquest estudi promovem que es pot assolir aquesta solució amb la implementació d’Observatoris Ciutadans, basats en la participació de voluntaris. Els observatoris ciutadans són plataformes que integren les últimes tecnologies de la informació amb ciutadans digitalment connectats, millorant les capacitats d’observació, per desenvolupar un nou tipus de recerca coneguda com a Ciència Ciutadana. La ciència ciutadana té el potencial d’incrementar el coneixement del medi ambient, i dels ecosistemes aquàtics en particular, mitjançant l'ús de persones sense coneixement científic específic per recollir i analitzar grans conjunts de dades. Creiem que les eines basades en ciència ciutadana -programari lliure juntament amb maquinari de baix cost i del tipus "fes-ho tu mateix" (do-it-yourself en anglès)- poden ajudar a apropar la ciència del camp oceanogràfic als ciutadans. A mesura que el gran públic participa activament en l'anàlisi de dades, la recerca esdevé també una nova via d’educació pública. Aquest és l’objectiu d’aquesta tesis, demostrar com el programari lliure i el maquinari de baix cost "fes-ho tu mateix" s’ap, Postprint (published version)

The technological advances in embedded systems and low-cost sensor have increased the interest of people in creating their own scientific instruments. The main advantage of this new Do-It-Yourself (DIY) instruments, is that DIY developers are able to obtain high resolution time series of parameters of interest that may share easily with the rest of the community by using existing communication channels (social media, mobile devices, ...). DIY is one of the key technologies to build the future Citizens' Observatories In the framework of coastal monitoring based on DIY and mobile technologies, the Citclops European project aims to develop systems to retrieve and use environmental data. Simple parameters related to changes in optical properties (colour, transparency) are used to evaluate the water quality in coastal systems. One of the proposed DIY technology for measuring water transparency is based on an open-hardware and open-source low cost buoy. The easy-to-use hardware and software facilitate the citizens' engagement in the scientific monitoring and is an ideal framework to develop transversal environmental education projects (involving science and technology) for young people

During the last decade, the use of recommender systems has been increasingly growing to the point that, nowadays, the success of many well-known services depends on these technologies. Recommenders Systems help people to tackle the choice overload problem by effectively presenting new content adapted to the user¿s preferences. However, current recommendation algorithms commonly suffer from data sparsity, which refers to the incapability of producing acceptable recommendations until a minimum amount of users¿ ratings are available for training the prediction models. This thesis investigates how the distributional semantics of concepts describing the entities of the recommendation space can be exploited to mitigate the data-sparsity problem and improve the prediction accuracy with respect to state-of-the-art recommendation techniques. The fundamental idea behind distributional semantics is that concepts repeatedly co-occurring in the same context or usage tend to be related. In this thesis, we propose and evaluate two novel semantically-enhanced prediction models that address the sparsity-related limitations: (1) a content-based approach, which exploits the distributional semantics of item¿s attributes during item and user-profile matching, and (2) a context-aware recommendation approach that exploits the distributional semantics of contextual conditions during context modeling. We demonstrate in an exhaustive experimental evaluation that the proposed algorithms outperform state-of-the-art ones, especially when data are sparse. Finally, this thesis presents a recommendation framework, which extends the widespread machine learning library Apache Mahout, including all the proposed and evaluated recommendation algorithms as well as a tool for offline evaluation and meta-parameter optimization. The framework has been developed to allow other researchers to reproduce the described evaluation experiments and make new progress on the Recommender Systems field easier, Durant l'última dècada, l'ús dels sistemes de recomanació s'ha vist incrementat fins al punt que, actualment, l'èxit de molts dels serveis web més coneguts depèn en aquesta tecnologia. Els Sistemes de Recomanació ajuden als usuaris a trobar els productes o serveis que més s¿adeqüen als seus interessos i preferències. Una gran limitació dels algoritmes de recomanació actuals és el problema de "data-sparsity", que es refereix a la incapacitat d'aquests sistemes de generar recomanacions precises fins que un cert nombre de votacions d'usuari és disponible per entrenar els models de predicció. Per mitigar aquest problema i millorar així la precisió de predicció de les tècniques de recomanació que conformen l'estat de l'art, en aquesta tesi hem investigat diferents maneres d'aprofitar la semàntica distribucional dels conceptes que descriuen les entitats que conformen l'espai del problema de la recomanació, principalment, els objectes a recomanar i la informació contextual. En la semàntica distribucional s'assumeix la següent hipotesi: conceptes que coincideixen repetidament en el mateix context o ús tendeixen a estar semànticament relacionats. Concretament, en aquesta tesi hem proposat i avaluat dos algoritmes de recomanació que fan ús de la semàntica distribucional per mitigar el problem de "data-sparsity": (1) un model basat en contingut que explota les similituds distribucionals dels atributs que representen els objectes a recomanar durant el càlcul de la correspondència entre els perfils d'usuari i dels objectes; (2) un model de recomanació contextual que fa ús de les similituds distribucionals entre condicions contextuals durant la representació del context. Mitjançant una avaluació experimental exhaustiva dels models de recomanació proposats hem demostrat la seva efectivitat en situacions de falta de dades, confirmant que poden millorar la precisió d'algoritmes que conformen l'estat de l'art. Finalment, aquesta tesi presenta una llibreria pel desenvolupament i avalu, Postprint (published version)

Several research works have demonstrated that if users' ratings are truly context-dependent, then Context-Aware Recommender Systems can outperform traditional recommenders. In this paper we present a novel contextual pre-filtering approach that exploits the implicit semantic similarity of contextual situations. For determining such a similarity we rely only on the available users' ratings and we deem as similar two syntactically different contextual situations that are actually influencing in a similar way the user's rating behavior. We validate the proposed approach using two contextually tagged ratings data sets showing that it outperforms a traditional pre-filtering approach and a state-of-the-art context-aware Matrix Factorization model., Peer Reviewed, Postprint (published version)

Environmental problems should not be tackled by scientists or policy makers alone. Involving the general public in observing and understanding our changing world, and encouraging citizen stewardship for the (marine) environment are crucial elements for a sustainable way of facing current and future problems. The EC-funded project Citclops will start in October 2012 and is focused on retrieving, through crowdsourcing, data on three main optical properties related to sea-water quality: colour, transparency and fluorescence. Novel technologies will be developed to retrieve these properties based on citizens’ measurements with common mobile devices. Concerning water colour, smart-phone camera images, taken through citizens’ collaboration, will be used to calculate the Forel-Ule index for the water body, providing an indication of gross biological activity. Water-transparency is planned to be measured by three alternative sensor systems : i) smart-phone cameras; ii) low-cost moored instrumentation; and iii) underwater, wearable cameras with added low-cost sensing systems (quasi-digital sensors). Obtained ocean colour and transparency data will complement the longterm global data series which go back to the late 20th century. Finally, to assess the fluorescence of different water constituents, low-cost sensors and light-sources will be customized and connected to smart-phones and other mobile devices. All acquired data is automatically uploaded through a specific service or application (such as Google+ Instant Upload), archived remotely and processed, and resulting information is accessed through a webpage or a mobile application by end users, thus closing the loop to citizens and policy makers

Web services have attracted attention as a possible solution to share knowledge and application logic among different heterogeneous agents. A classic approach to this subject is using SOAP, a W3C protocol aimed to exchange structured information. The Web Services Interoperability organization (WS-I), defines a set of extensions, commonly called WS-*, which further enhance this knowledge exchange defining mechanisms and functionalities such as security, addressability or service composition. This thesis explores a relatively new alternative approach to the SOAP/WS-I stack: REST-based Web services. The acronym REST stands for Representational state transfer; this basically means that each unique URL is a representation of some object. You can get the contents of that object using an HTTP GET; you then might use a POST, PUT or DELETE to modify the object (in practice most of the services use a POST for this). All of Yahoo’s Web services use REST, including Flickr; del.icio.us API uses it; pubsub [http://www.pubsub.com/], Bloglines [http://www.bloglines.com/], Technorati [http://technorati.com/] and both, eBay and Amazon, have Web services for both REST and SOAP. Google seems to be consistent in implementing their Web services to use SOAP, with the exception of Blogger, which uses XML-RPC. The companies and organization that are using REST APIs have not been around for very long, and their APIs came out in the last seven years mostly. So REST is a new way to create and integrate Web services, whose main advantages are: being lightweight (not a lot of extra xml mark-up), human readable results, easy to build services (no toolkits required). Although REST is still generating discussion about possible implementations, and different proposals have been put forward, it provides enough mechanisms to allow knowledge-representations sharing among heterogeneous intelligent services. In this thesis, a novel way to integrate intelligent Web-services is designed and developed, and

This paper presents an agent-based methodological approach to design distributed service-oriented systems which can adapt their behaviour according to changes in the environment and in the user needs, even taking the initiative to make suggestions and proactive choices. The highly dynamic, regulated, complex nature of the distributed, interconnected services is tackled through a methodological framework composed of three interconnected levels. The framework relies on coordination and organisational techniques, as well as on semantically annotated Web services to design, deploy and maintain a distributed system, using both a top-down and bottom-up approach. We present results based on a real use case: interactive community displays with tourist information and services, dynamically personalised according to user context and preferences., Preprint

Personalization and recommendation systems are a solution to the problem of content overload, especially in large information systems. In this thesis, a personalized recommendation system enhanced with semantic knowledge has been developed in order to overcome the most common limitations of traditional approaches: the cold-start and the sparsity problems. The recommender consists of the following two main components. A user-profile learning algorithm combines user’s feedback from different channels and employs domain inferences to construct accurate user profiles. A recommendation algorithm, using content-based filtering, exploits the semantic structure of the domain to obtain accurate predictions and generate the corresponding recommendations. The system’s design proposed is flexible enough to be potentially applied to applications of any domain that can be properly described using ontologies. In addition to the development of the recommendation system, an existing Web-application in the tourism domain has been extended and adapted in order to be able to integrate the recommender into it. The overall recommendation system has been evaluated and the results obtained indicate that it satisfies the requirements established.

Interconnected service providers constitute a highly dynamic, complex, distributed environment. Multi-agent system design-methodologies have been try-ing to address this kind of environments for a long time. The European project ALIVE presents a framework of three interconnected levels that tackles this issue relying on organisation and coordination techniques, as well as on developments in the Web-services world. This paper presents initial results focused on a high-tech, real use case: interactive community displays with touristic information and services, dynamically personalized according to user preferences and local laws., Peer Reviewed, Preprint

This paper presents a case study for the development of an integration framework in the area of collaborative work environments. This framework is based on REST Web services, and has been designed and implemented as part of the Laboranova European project., Peer Reviewed, Preprint

La falta de servicios automáticos y personalizados de información fácilmente accesibles para los turistas y ciudadanos cuándo éstos se encuentran en la vía pública, impacta negativamente en el sector turístico, ya que implica una disminución del uso de los servicios que ofrece la ciudad y del grado de satisfacción de los usuarios. El proyecto SOPAT ha desarrollado un servicio personalizado de información y guía de ciudad que facilita el acceso a la información de interés a todo tipo de turistas y ciudadanos utilizando como plataforma experimental un punto de información multimedia con servicios interactivos en la zona pública., The lack of automatic, personalized services of information, which were easily accessible to tourists and citizens when they are in public spaces, negatively impacts the tourism sector, since it reduces the use of the services offered by the city and the satisfaction degree of the users. The SOPAT project has developed a personalized service of information and city guide that facilitates all kinds of tourists and citizens access to information of interest using an interactive community display as experimental platform.

Con este proyecto se quiere mejorar uno de los productos principales de la empresa, que consiste en un sistema de televisión interactiva que permite a los usuarios poder disfrutar de varios servicios tales como una aplicación ofimática, una guía local y la adquisición de contenidos de distintos tipos: películas, series, clips, música, información cultural y videojuegos entre otros. Actualmente existen varios sistemas de recomendación de contenido de vídeo que funcionan relativamente bien, pero únicamente en entornos con un gran número de usuarios que continuamente interactúan con el sistema. Esto implica, que los algoritmos de recomendación de contenido de vídeo actuales sólo tengan cabida en el entorno Web, dónde el número de usuarios puede llegar a ser considerable y se dispone de una alta densidad de información. Se pretende diseñar un sistema de recomendación en el que la precisión de las recomendaciones no dependa tanto de la densidad de información disponible, sino más bien en la calidad de la información, dado que estas son las características del entorno donde se implantará el sistema.

La falta de servicios automáticos y personalizados de información fácilmente accesibles para los turistas y ciudadanos cuándo éstos se encuentran en la vía pública, impacta negativamente en el sector turístico, ya que implica una disminución del uso de los servicios que ofrece la ciudad y del grado de satisfacción de los usuarios. El proyecto SOPAT ha desarrollado un servicio personalizado de información y guía de ciudad que facilita el acceso a la información de interés a todo tipo de turistas y ciudadanos utilizando como plataforma experimental un punto de información multimedia con servicios interactivos en la zona pública., The lack of automatic, personalized services of information, which were easily accessible to tourists and citizens when they are in public spaces, negatively impacts the tourism sector, since it reduces the use of the services offered by the city and the satisfaction degree of the users. The SOPAT project has developed a personalized service of information and city guide that facilitates all kinds of tourists and citizens access to information of interest using an interactive community display as experimental platform.

In this report an unsupervised and knowledge-based algorithm for concept sense disambiguation in concept maps is proposed. Concept maps are graphical tools for organizing and representing knowledge, based on concepts and labeled interconnections among them, forming propositions. The disambiguation process is carried combining Magnini’s domain, context information and the gloss. It’s supported in the Spanish WordNet lexical database and the lexical relations hypernyms-hyponyms, meronyms-holonyms and instance., Postprint (published version)

This document contains requirements and specifications for the data-storage layer of Laboranova’s integration architecture and for the data structure of the idea concept. This document presents technology choices for the implementation of the data-storage layer in a way that facilitates composing the different sub-projects (SPs) of Laboranova into a modular collaborative environment. The idea concept is central in Laboranova and working with ideas involves several aspects: • a conceptualisation of what an idea is; • data structures for ideas (Representations based on these data structures are passed among the software systems which make up the Laboranova environment.); • the integration of idea’s manipulation carried out by the different Laboranova’s tools. This document focuses on the data structures, taking into account the requirements of the visualization tool and the results obtained from a questionnaire (‘Laboranova Data Storage Questionnaire’) which was conducted in May 2007 among Laboranova’s partners. Such questionnaire was intended to gather requirements on technology and integration choices which affect some aspects of the idea data structure. This document also takes into account the user requirements gathered in D6.1.1 (‘Report on deployment scenarios and requirements’, version 1.0), which concern: • Idea management: archival and retrieval of ideas • Versioning: branching; vertical expansion of an idea; originating new ideas changing a first one • Relations between ideas: idea clustering • Flexibility and transparency: integrative design, providing a modular user environment • Integration with current practices: connecting Laboranova with previous tools and processes This document is divided in the following parts: • description of the integration architecture to frame this document with the context of Laboranova and the SPs that compose it; • overall description of the data layer; • conceptualization of the idea data structure by: A) giving a compilati, Postprint (published version)

El desarrollo y utilización de las ontologías, se está viendo cada vez más en ascenso, demostrando con ello su gran utilidad en los contextos en los que se necesite formalizar y compartir un conocimiento. Cada vez más se está requiriendo la creación de un ambiente que facilite la colaboración en el trabajo con las ontologías y hoy no están creadas las condiciones para esto. El proceso de elaboración de ontologías, las herramientas disponibles para su obtención y mantenimiento y los lenguajes de especificación que se están utilizando, tienen un alto grado de complejidad para su interpretación y amplia utilización por parte de personas no son expertas en el tema. Esto sugiere la utilización de herramientas más simple, que vinculada con las ontologías pueda ser comprendida y mejor aprovechadas por el hombre y que a su vez mantenga las capacidades para su interpretación computacionalmente. Los mapas conceptuales son una herramienta muy intuitiva para la representación del conocimiento que posee el hombre. Las facilidades que brinda en su elaboración, flexibilidad y estructura, lo han convertido en una herramienta muy útil para la gestión del conocimiento y la colaboración. La flexibilidad de los mapas conceptuales, lo convierte en una herramienta muy poco formal, a diferencia de las ontologías, sin embargo, se considera que esto no impide pensar que se puedan integrar con las ontologías y ser utilizados como un lenguaje de representación gráfico conceptual de estas. En esta investigación se propone la definición de un modelo que permite la integración entre las ontologías y los mapas conceptuales. El Modelo Unificado, como se le ha llamado, es resultado de la unificación de algunas características resultantes de análisis realizados a diferentes formas de representación del conocimiento de la Inteligencia Artificial y los mapas conceptuales. La características identificadas e integradas generó un conjunto de criterios que fundamentan la integración propuesta en ontología, Postprint (published version)

The work described in this document has been carried out in the frame of the @LIS TechNET project, which aims to create a live network across Europe and Latin America as a new, virtual, and interactive learning environment, based on software-agent technology. The purpose of this document is to describe a visualization tool developed for the TechNET's planning system. As background, this document also briefly describes what mixed-initiative planning is., Postprint (published version)

Les contribucions d'aquesta tesi uneixen dues disciplines: ciències ambientals (específicament, gestió d'aigües residuals) i informàtica (específicament, intel·ligència artificial). El tractament d'aigües residuals com a disciplina opera fent servir un rang de diferents enfocaments i mètodes que inclouen: control manual, control automàtic on-line, modelat numèric o no-numèric, models estadístics i simulacions. La tesi caracteritza la recerca interdisciplinària de tècniques d'intel·ligència artificial (raonament basat en regles, raonament basat en casos, ontologies i planificació) a sistemes de suport a la decisió a l'entorn ambiental. El disseny de l'arquitectura d'aquesta aplicació, el sistema OntoWEDSS, augmenta els sistemes clàsics de raonament existents (raonament basat en regles i basat en casos) amb una ontologia de domini per a la gestió de plantes de tractament d'aigües residuals. La integració de l'ontologia WaWO recentment creada proporciona a OntoWEDSS una major flexibilitat en la capacitat de gestió. La construcció del sistema de suport a la decisió OntoWEDSS es basa en l'estudi d'un cas específic, però el sistema també és d'interès general ja que l'arquitectura basada en l'ontologia pot aplicar-se a qualsevol estació depuradora i, a un nivell apropiat d'abstracció, a altres dominis ambientals. El sistema OntoWEDSS millora la diagnosi de l'estat de l'estació depuradora, proporciona suport a la solució de complexes problemes relacionats amb aigües residuals, i facilita el modelatge del coneixement i la seva reutilització mitjançant l'ontologia WaWO. En particular, a la investigació s'han aconseguit els següents objectius: (1) la millora del modelatge de la informació sobre processos de tractament d'aigües residuals i la clarificació de part de la confusió existent en la terminologia del domini, (2) la incorporació de coneixement microbiològic (referent al procés del tractament i modelat mitjançant una ontologia) dins del procés de raonament, (3) la c, Las contribuciones de esta tesis unen dos disciplinas: ciencias ambientales (específicamente, gestión de aguas residuales) e informática (específicamente, inteligencia artificial). El tratamiento de aguas residuales como disciplina opera utilizando un rango de diferentes enfoques y métodos que incluye: control automático on-line, modelado numérico o no-numérico, razonamiento basado en reglas, razonamiento basado en casos, soporte a la decisión y planificación. La tesis caracteriza una aplicación interdisciplinaria de técnicas de inteligencia artificial a sistemas de soporte a la decisión en el dominio ambiental. El diseño de la arquitectura de esta aplicación, el sistema OntoWEDSS, aumenta los sistemas híbridos de razonamiento ya existentes (razonamiento basado en reglas y basado en casos) con una ontología de dominio para la gestión de plantas de tratamiento de aguas residuales. La integración de la ontología WaWO, de nueva creación, proporciona a OntoWEDSS una mayor flexibilidad en la capacidad de gestión. La construcción del sistema de soporte a la decisión OntoWEDSS se basa en el estudio de un caso específico, pero el sistema resulta también es de interés general puesto que la arquitectura basada en ontologías puede aplicarse a cualquier planta de tratamiento de aguas residuales y, a un nivel apropiado de abstracción, a otros dominios ambientales. El sistema OntoWEDSS mejora la diagnosis del estado de la planta de tratamiento, proporciona soporte a la resolución de complejos problemas relacionados con aguas residuales, y facilita el modelado del conocimiento y su reutilización mediante la ontología WaWO. En particular, la investigación ha alcanzado los siguientes objetivos: (1) la mejora del modelado de la información sobre procesos de tratamiento de aguas residuales y la clarificación de parte de la confusión existente en la terminología relacionada, (2) la incorporación de conocimiento microbiológico (referente al proceso del tratamiento y modelado median, The contributions of this thesis bridge two disciplines: environmental science (specifically, wastewater management) and computer science (specifically, artificial intelligence). Wastewater management as a discipline operates using a range of different approaches and methods which include: manual control, on-line automatic control, numerical or non-numerical models, statistical models and simulation models. The thesis characterizes an interdisciplinary research on artificial intelligence techniques (rule-based reasoning, case-based reasoning, ontologies and planning) applied to environmental decision-support systems. The integrated architecture's design of this application, the OntoWEDSS system, augments classic reasoning systems (rule-based reasoning and case-based reasoning) with a domain ontology about the management of wastewater treatment plants. The integration of the newly created WaWO ontology provides a more flexible management capability to OntoWEDSS. The construction of the OntoWEDSS decision support system is based on a specific case study but the system is also of general interest, given that its ontology-underpinned architecture can be applied to any wastewater treatment plant and, at an appropriate level of abstraction, to other environmental domains. The OntoWEDSS system improves the diagnosis of the state of a treatment plant, provides support for wastewater-related complex problem-solving, and facilitates knowledge modeling and reuse by means of the WaWO ontology. The following research targets have been achieved in particular: (1) the improvement of the modeling of the information about wastewater treatment processes and the clarification of a part of the existing terminological confusion in the domain, (2) the incorporation of ontology-modeled microbiological knowledge related to the treatment process into the reasoning process, (3) the creation of a decision support system with three layers (perception, diagnosis and decision support) which, Questa tesi contribuisce alla intersezione di due discipline: le scienze ambientali (specificamente, la gestione delle acque di rifiuto) e la informatica (specificamente, la intelligenza artificiale). Nel trattamento delle acque di rifiuto come disciplina si utilizzano diversi metodi, che includono: controllo manuale, controllo automatico on-line, modelli numerici o non-numerici e simulazioni. La tesi caratterizza un'applicazione interdisciplinare di tecniche di intelligenza artificiale a sistemi di aiuto alla decisione in campo ambientale. L'architettura di questa applicazione, il sistema OntoWEDSS, amplia i sistemi di ragionamento ibrido esistenti (ragionamento basato su un sistema di regole, ragionamento basato sull'esperienza, aiuto alla decisione e pianificazione) con un'ontologia di dominio per la gestione di depuratori di acque di rifiuto. L'integrazione dell'ontologia WaWO, di nuova creazione, fornisce a OntoWEDSS una maggiore flessibilità nella sua capacità di gestione. La costruzione del sistema OntoWEDSS si basa sullo studio di un caso specifico, però il sistema risulta anche di interesse generale dato che l'architettura basata su un'ontologia può essere applicata a un qualsiasi depuratore e, considerando un adeguato livello d'astrazione, ad altri domini ambientali. Il sistema OntoWEDSS migliora la diagnosi dello stato del depuratore, fornisce aiuto alla soluzione di problemi complessi relazionati con le acque di rifiuto e facilita la modellizzazione della conoscenza e la sua riutilizzazione mediante l'ontologia WaWO. In particolare, la ricerca realizzata ha raggiunto i seguenti obiettivi: (1) il miglioramento dell'informazione sui processi di depurazione e il chiarimento di parte della confusione esistente nella terminologia relativa, (2) l'incorporazione di conoscenza microbiologica (riguardo al processo di depurazione e mediante la modellizzazione ontologica) nel processo di ragionamento, (3) la creazione di un sistema di aiuto alla decisione con, Postprint (published version)

We present an ontology (named WaWO - Waste Water Ontology), integrated into an existent environmental decision-support system (named DAI-DEPUR+), designed to model the information about a wastewater treatment process through the definition of the basic terms and relations comprising the vocabulary of the wastewater treatment area. The WaWO ontology is built following the ideas of Uschold and Grüninger and is a hierarchically structured set of terms and a set of axioms for describing the domain of wastewater treatment. It is the manifestation of a shared understanding of the wastewater domain that is agreed among a number of agents: mainly, experts in environmental and chemical engineering. This ontology incorporates some new features for the wastewater domain, such as: semi-automatic generation of knowledge bases, modeling of the cause-effect relations existing within a wastewater treatment plant, integration with predictive reasoning based on transition networks., Postprint (published version)

Presentation of an environmental decision-support system integrating a rule-based expert system, a case-based reasoner and an ontological knowledge-base. This system is able to model the information about a wastewater treatment process through the definition of the basic terms and relations comprising the vocabulary of the wastewater treatment area. Furthermore, this management system optimizes the operation of wastewater treatment by a more reliable management and making easier its self-portability., Postprint (published version)

Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature-for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes-short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from 'not citizen science' (0%) to 'citizen science' (100%). The survey included 50 vignettes, of which five were developed as clear cases of not-citizen science activities, five as widely accepted citizen science activities and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field.

Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature-for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes-short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from 'not citizen science' (0%) to 'citizen science' (100%). The survey included 50 vignettes, of which five were developed as clear cases of not-citizen science activities, five as widely accepted citizen science activities and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field.