ciencia ciudadana

 Citizen participation in the collection of scientific data promotes a more democratic science, by involving society in R+D+i processes and reinforcing accountability. In this sense, there are a variety of citizen science initiatives launched by entities such as CSIC, CENEAM or CREAF, among others. In addition, there are currently numerous citizen science platform platforms that help anyone find, join and contribute to a wide variety of initiatives around the world, such as SciStarter.

Some references in national and European legislation

Different regulations, both at national and European level, highlight the importance of promoting citizen science projects as a fundamental component of open science. For example, Organic Law 2/2023, of 22 March, on the University System, establishes that universities will promote citizen science as a key instrument for generating shared knowledge and responding to social challenges, seeking not only to strengthen the link between science and society, but also to contribute to a more equitable, inclusive and sustainable territorial development.

On the other hand, Law 14/2011, of 1 June, on Science, Technology and Innovation, promotes "the participation of citizens in the scientific and technical process through, among other mechanisms, the definition of research agendas, the observation, collection and processing of data, the evaluation of impact in the selection of projects and the monitoring of results,  and other processes of citizen participation."

At the European level, Regulation (EU) 2021/695 establishing the Framework Programme for Research and Innovation "Horizon Europe", indicates the opportunity to develop projects co-designed with citizens, endorsing citizen science as a research mechanism and a means of disseminating results.

Citizen science initiatives and data management plans

The first step in defining a citizen science initiative is usually to establish a research question that requires data collection that can be addressed with the collaboration of citizens. Then, an accessible protocol is designed  for participants to collect or analyze data in a simple and reliable way (it could even be a gamified process). Training materials must be prepared and a means of participation (application, web or even paper) must be developed. It also plans how to communicate progress and results to citizens, encouraging their participation.

As it is an intensive activity in data collection, it is interesting that citizen science projects have a data management plan that defines the life cycle of data in research projects, that is, how data is created, organized, shared, reused and preserved in citizen science initiatives. However, most citizen science initiatives do not have such a plan: this recent research article found that only 38% of the citizen science projects consulted had a data management plan.

Figure 1. Data life cycle in citizen science projects Source: own elaboration – datos.gob.es.

On the other hand, data from citizen science only reach their full potential when they comply with the FAIR principles and are published in open access. In order to help have this data management plan that makes data from citizen science initiatives FAIR, it is necessary to have specific standards for citizen science such as PPSR Core.

Open Data for Citizen Science with the PPSR Core Standard

The publication of open data should be considered from the early stages of a citizen science project, incorporating the PPSR Core standard as a key piece. As we mentioned earlier, when research questions are formulated, in a citizen science initiative, a data management plan must be proposed that indicates what data to collect, in what format and with what metadata, as well as the needs for cleaning and quality assurance from the data collected by citizens.  in addition to a publication schedule.

Then, it must be standardized with PPSR (Public Participation in Scientific Research) Core. PPSR Core is a set of data and metadata standards, specially designed to encourage citizen participation in scientific research processes. It has a three-layer architecture based on a Common Data Model (CDM). This CDM helps to organize in a coherent and connected way the information about citizen science projects, the related datasets and the observations that are part of them, in such a way that the CDM facilitates interoperability between citizen science platforms and scientific disciplines. This common model is structured in three main layers that allow the key elements of a citizen science project to be described in a structured and reusable way. The first is the Project Metadata Model (PMM), which collects the general information of the project, such as its objective, participating audience, location, duration, responsible persons, sources of funding or relevant links. Second, the Dataset Metadata Model (DMM) documents each dataset generated, detailing what type of information is collected, by what method, in what period, under what license and under what conditions of access. Finally, the Observation Data Model (ODM) focuses on each individual observation made by citizen science initiative participants, including the date and location of the observation and the result. It is interesting to note that this PPSR-Core layer model allows specific extensions to be added according to the scientific field, based on existing vocabularies such as Darwin Core (biodiversity) or ISO 19156 (sensor measurements). (ODM) focuses on each individual observation made by participants of the citizen science initiative, including the date and place of the observation and the outcome. It is interesting to note that this PPSR-Core layer model allows specific extensions to be added according to the scientific field, based on existing vocabularies such as Darwin Core (biodiversity) or ISO 19156 (sensor measurements).

Figure 2. PPSR CORE layering architecture. Source: own elaboration – datos.gob.es.

This separation allows a citizen science initiative to automatically federate the project file (PMM) with platforms such as SciStarter, share a dataset (DMM) with a institutional repository of open scientific data, such as those added in FECYT's RECOLECTA and, at the same time, send verified observations (ODMs) to a platform such as GBIF without redefining each field.

In addition, the use of PPSR Core provides a number of advantages for the management of the data of a citizen science initiative:

• Greater interoperability: platforms such as SciStarter already exchange metadata using PMM, so duplication of information is avoided.
• Multidisciplinary aggregation: ODM profiles allow datasets from different domains (e.g. air quality and health) to be united around common attributes, which is crucial for multidisciplinary studies.
• Alignment with FAIR principles: The required fields of the DMM are useful for citizen science datasets to comply with the FAIR principles.

It should be noted that PPSR Core allows  you to add context to datasets obtained in citizen science initiatives. It is a good practice to translate the content of the PMM into language understandable by citizens, as well as to obtain a data dictionary from the DMM (description of each field and unit) and the mechanisms for transforming each record from the MDG. Finally, initiatives to improve PPSR Core can be highlighted, for example, through a DCAT profile for citizen science.

Conclusions

Planning the publication of open data from the beginning of a citizen science project is key to ensuring the quality and interoperability of the data generated, facilitating its reuse and maximizing the scientific and social impact of the project. To this end, PPSR Core offers a level-based standard (PMM, DMM, ODM) that connects the data generated by citizen science with various platforms, promoting that this data complies with the FAIR principles and considering, in an integrated way, various scientific disciplines. With PPSR Core , every citizen observation is easily converted into open data on which the scientific community can continue to build knowledge for the benefit of society.

Jose Norberto Mazón, Professor of Computer Languages and Systems at the University of Alicante. The contents and views reflected in this publication are the sole responsibility of the author.

Citizen science is consolidating itself as one of the most relevant sources of most relevant sources of reference in contemporary research contemporary research. This is recognised by the Centro Superior de Investigaciones Científicas (CSIC), which defines citizen science as a methodology and a means for the promotion of scientific culture in which science and citizen participation strategies converge.

We talked some time ago about the importance importance of citizen science in society in society. Today, citizen science projects have not only increased in number, diversity and complexity, but have also driven a significant process of reflection on how citizens can actively contribute to the generation of data and knowledge.

To reach this point, programmes such as Horizon 2020, which explicitly recognised citizen participation in science, have played a key role. More specifically, the chapter "Science with and for society"gave an important boost to this type of initiatives in Europe and also in Spain. In fact, as a result of Spanish participation in this programme, as well as in parallel initiatives, Spanish projects have been increasing in size and connections with international initiatives.

This growing interest in citizen science also translates into concrete policies. An example of this is the current Spanish Strategy for Science, Technology and Innovation (EECTI), for the period 2021-2027, which includes "the social and economic responsibility of R&D&I through the incorporation of citizen science" which includes "the social and economic responsibility of I through the incorporation of citizen science".

In short, we commented some time agoin short, citizen science initiatives seek to encourage a more democratic sciencethat responds to the interests of all citizens and generates information that can be reused for the benefit of society. Here are some examples of citizen science projects that help collect data whose reuse can have a positive impact on society:

AtmOOs Academic Project: Education and citizen science on air pollution and mobility.

In this programme, Thigis developed a citizen science pilot on mobility and the environment with pupils from a school in Barcelona's Eixample district. This project, which is already replicable in other schoolsconsists of collecting data on student mobility patterns in order to analyse issues related to sustainability.

On the website of AtmOOs Academic you can visualise the results of all the editions that have been carried out annually since the 2017-2018 academic year and show information on the vehicles used by students to go to class or the emissions generated according to school stage.

WildINTEL: Research project on life monitoring in Huelva

The University of Huelva and the State Agency for Scientific Research (CSIC) are collaborating to build a wildlife monitoring system to obtain essential biodiversity variables. To do this, remote data capture photo-trapping cameras and artificial intelligence are used.

The wildINTEL project project focuses on the development of a monitoring system that is scalable and replicable, thus facilitating the efficient collection and management of biodiversity data. This system will incorporate innovative technologies to provide accurate and objective demographic estimates of populations and communities.

Through this project which started in December 2023 and will continue until December 2026, it is expected to provide tools and products to improve the management of biodiversity not only in the province of Huelva but throughout Europe.

IncluScience-Me: Citizen science in the classroom to promote scientific culture and biodiversity conservation.

This citizen science project combining education and biodiversity arises from the need to address scientific research in schools. To do this, students take on the role of a researcher to tackle a real challenge: to track and identify the mammals that live in their immediate environment to help update a distribution map and, therefore, their conservation.

IncluScience-Me was born at the University of Cordoba and, specifically, in the Research Group on Education and Biodiversity Management (Gesbio), and has been made possible thanks to the participation of the University of Castilla-La Mancha and the Research Institute for Hunting Resources of Ciudad Real (IREC), with the collaboration of the Spanish Foundation for Science and Technology - Ministry of Science, Innovation and Universities.

The Memory of the Herd: Documentary corpus of pastoral life.

This citizen science project which has been active since July 2023, aims to gather knowledge and experiences from sheperds and retired shepherds about herd management and livestock farming.

The entity responsible for the programme is the Institut Català de Paleoecologia Humana i Evolució Social, although the Museu Etnogràfic de Ripoll, Institució Milà i Fontanals-CSIC, Universitat Autònoma de Barcelona and Universitat Rovira i Virgili also collaborate.

Through the programme, it helps to interpret the archaeological record and contributes to the preservation of knowledge of pastoral practice. In addition, it values the experience and knowledge of older people, a work that contributes to ending the negative connotation of "old age" in a society that gives priority to "youth", i.e., that they are no longer considered passive subjects but active social subjects.

Plastic Pirates Spain: Study of plastic pollution in European rivers.

It is a citizen science project which has been carried out over the last year with young people between 12 and 18 years of age in the communities of Castilla y León and Catalonia aims to contribute to generating scientific evidence and environmental awareness about plastic waste in rivers.

To this end, groups of young people from different educational centres, associations and youth groups have taken part in sampling campaigns to collect data on the presence of waste and rubbish, mainly plastics and microplastics in riverbanks and water.

In Spain, this project has been coordinated by the BETA Technology Centre of the University of Vic - Central University of Catalonia together with the University of Burgos and the Oxygen Foundation. You can access more information on their website.

Here are some examples of citizen science projects. You can find out more at the Observatory of Citizen Science in Spain an initiative that brings together a wide range of educational resources, reports and other interesting information on citizen science and its impact in Spain. do you know of any other projects? Send it to us at dinamizacion@datos.gob.es and we can publicise it through our dissemination channels.

For many people, summer means the arrival of the vacations, a time to rest or disconnect. But those days off are also an opportunity to train in various areas and improve our competitive skills.

For those who want to take advantage of the next few weeks and acquire new knowledge, Spanish universities have a wide range of courses on a variety of subjects. In this article, we have compiled some examples of courses related to data training.

Geographic Information Systems (GIS) with QGIS. University of Alcalá de Henares (link not available).

The course aims to train students in basic GIS skills so that they can perform common processes such as creating maps for reports, downloading data from a GPS, performing spatial analysis, etc. Each student will have the possibility to develop their own GIS project with the help of the faculty. The course is aimed at university students of any discipline, as well as professionals interested in learning basic concepts to create their own maps or use geographic information systems in their activities.

• Date and place: June 27-28 and July 1-2 in online mode.

Citizen science applied to biodiversity studies: from the idea to the results. Pablo de Olavide University (Seville).

This course addresses all the necessary steps to design, implement and analyze a citizen science project: from the acquisition of basic knowledge to its applications in research and conservation projects. Among other issues, there will be a workshop on citizen science data management, focusing on platforms such as Observation.org y GBIF.  It will also teach how to use citizen science tools for the design of research projects. The course is aimed at a broad audience, especially researchers, conservation project managers and students.

• Date and place: From July 1 to 3, 2024 in online and on-site (Seville).

Big Data. Data analysis and machine learning with Python. Complutense University of Madrid.  

This course aims to provide students with an overview of the broad Big Data ecosystem, its challenges and applications, focusing on new ways of obtaining, managing and analyzing data. During the course, the Python language is presented, and different machine learning techniques are shown for the design of models that allow obtaining valuable information from a set of data. It is aimed at any university student, teacher, researcher, etc. with an interest in the subject, as no previous knowledge is required.

• Date and place: July 1 to 19, 2024 in Madrid.

Introduction to Geographic Information Systems with R. University of Santiago de Compostela.

Organized by the Working Group on Climate Change and Natural Hazards of the Spanish Association of Geography together with the Spanish Association of Climatology, this course will introduce the student to two major areas of great interest: 1) the handling of the R environment, showing the different ways of managing, manipulating and visualizing data. 2) spatial analysis, visualization and work with raster and vector files, addressing the main geostatistical interpolation methods. No previous knowledge of Geographic Information Systems or the R environment is required to participate.

• Date and place: July 2-5, 2024 in Santiago de Compostela

Artificial Intelligence and Large Language Models: Operation, Key Components and Applications. University of Zaragoza.

Through this course, students will be able to understand the fundamentals and practical applications of artificial intelligence focused on Large Language Model (LLM). Students will be taught how to use specialized libraries and frameworks to work with LLM, and will be shown examples of use cases and applications through hands-on workshops. It is aimed at professionals and students in the information and communications technology sector.

• Date and place: July 3 to 5 in Zaragoza.

Deep into Data Science. University of Cantabria.

This course focuses on the study of big data using Python. The emphasis of the course is on Machine Learning, including sessions on artificial intelligence, neural networks or Cloud Computing. This is a technical course, which presupposes previous knowledge in science and programming with Python.

• Date and place: From July 15 to 19, 2024 in Torrelavega.

Data management for the use of artificial intelligence in tourist destinations. University of Alicante.  

This course approaches the concept of Smart Tourism Destination (ITD) and addresses the need to have an adequate technological infrastructure to ensure its sustainable development, as well as to carry out an adequate data management that allows the application of artificial intelligence techniques. During the course, open data and data spaces and their application in tourism will be discussed. It is aimed at all audiences with an interest in the use of emerging technologies in the field of tourism.

• Date and place: From July 22 to 26, 2024 in Torrevieja.

The challenges of digital transformation of productive sectors from the perspective of artificial intelligence and data processing technologies. University of Extremadura.

Now that the summer is over, we find this course where the fundamentals of digital transformation and its impact on productive sectors are addressed through the exploration of key data processing technologies, such as the Internet of Things, Big Data, Artificial Intelligence, etc. During the sessions, case studies and implementation practices of these technologies in different industrial sectors will be analyzed. All this without leaving aside the ethical, legal and privacy challenges. It is aimed at anyone interested in the subject, without the need for prior knowledge.

• Date and place: From September 17 to 19, in Cáceres.

These courses are just examples that highlight the importance that data-related skills are acquiring in Spanish companies, and how this is reflected in university offerings. Do you know of any other courses offered by public universities? Let us know in comments.

Content prepared by the datos.gob.es team.