DOI: 10.3897/rio.12.e193918

Authors: Erica Zaja, Will Brownlie, Rajabu Hamisi, Maja Arsic, Adelaide Asante, Hilary Barraclough, André Bationo, Martin Blackwell, Dana Cordell, James Elser, Oluwole Fatunbi, Kwame Frimpong, Elise Gallois, Enam Gbekor, Kailyn Harris-Gilliam, Philip Haygarth, Ludwig Hermann, Kenneth Irvine, Issy Lewis, Ning Liu, Vincent Logah, Kaushik Majumdar, Muneta Grace Manzeke-Kangara, Eric Mensah, Malika Mezeli, Michael Miyittah, Innocent Muhwezi, Frederick Otu-Larbi, Richard Padi, Kasper Reitzel, Seth Robinson, Collins Tay, Francis Tetteh, Louis Tetteh, Shamie Zingore, Bryan Spears

Abstract: Phosphorus sustains global food production and is, therefore, of crucial importance to human nutrition and health. However, its mismanagement can lead to water pollution and environmental degradation in addition to low crop yields. In many parts of sub-saharan Africa, phosphorus deficiency constrains agricultural productivity and exacerbates food insecurity. Despite these challenges, phosphorus remains a fragmented topic in global and African policy. To address these issues, the 8th Sustainable Phosphorus Summit (SPS8) was convened in Africa for the first time. SPS8 took place in Accra, Ghana, between 30th September and 3rd October 2025. The Summit was an international collaboration, with co-conveners from the Council for Scientific and Industrial Research (CSIR) – Ghana, the Forum for Agricultural Research in Africa (FARA), The UK Centre for Ecology & Hydrology West Africa Office, Lancaster University and Rothamsted Research. In this paper, we give a detailed overview of the key messages and insights that emerged from highlight talks, lectures, working groups and field trips. We also discuss and reflect on the challenges of delivering an inclusive summit, from designing solutions to benefit-sharing. SPS8 demonstrates that inclusive, cross-sector knowledge-exchange events are crucial to support and enable phosphorus sustainability on the continent of Africa and globally and to enable the next generation of interdisciplinary phosphorus researchers.

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DOI: 10.3897/rio.11.e181727

Authors: Alexandra-Maria Klein, Anda Adamsone-Fiskovica, Georgina Alins, Per Angelstam, Aurelie Belveze, Jordi Bosch, Tom Breeze, Richard Comont, Elise de Groot, Lynn Dicks, Anselm Rodrigo Dominguez, György Dudás, Lotta Fabricius Kristiansen, Mariia Fedoriak, Nicola Gallai, Michael Garratt, Mikelis Grivins, Christina Grozinger, Nigel Jenner, Georgios Kleftodimos, David Kleijn, Anikó Kovács-Hostyánszki, Bodo Krauss, Sara Leonhardt, Julia Osterman, Annie Ouin, Amy Plowman, Simon Potts, Claus Rasmussen, Laura Roquer-Beni, Daniele Rossi, Maj Rundlöf, Oliver Schweiger, Henrik Smith, Jane Stout, Louis Sutter, Martin Thorsøe, George Vlontzos, Dimitry Wintermantel, Nina Kranke, Amibeth Thompson

Abstract: RestPoll is a transdisciplinary project aiming to provide society with tools to reverse wild insect pollinator declines and to position Europe as a global leader in pollinator restoration and set the future agenda for pollinator restoration worldwide. The RestPoll consortium combines the expertise of natural and social scientists, as well as representatives of NGOs, businesses and ministries. RestPoll - together with stakeholders ranging from individual land managers to public authorities - co-designs, evaluates and refines measures and cross-sectoral approaches to restore pollinators and their services. Central to RestPoll is the establishment of a Europe-wide network of pollinator restoration case-study areas with Living Labs, which are unique hubs for experimentation, demonstration and mutual learning at various spatial scales (field, farm, landscape, European scales), in landscapes dominated by intensively managed crops or grasslands. The RestPoll consortium explores, tests, evaluates and refines cross-sectoral pollinator restoration approaches to conserve biodiversity and to benefit nature and society. Our holistic approach also aims to engage in participatory planning and the development of new business models along the food value chain by engaging through newly-developed participatory approaches at diverse social, ecological and political scales. Learning outcomes are communicated to a diverse range of regional and European partners and collaborators, which allows for making a lasting impact beyond the end of the project.

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DOI: 10.3897/rio.11.e176120

Authors: Christos Arvanitidis, Olga Ameixa, Alberto Basset, Eva Chatzinikolaou, Claudia Coman, Berta Companys, Francesco De Leo, Klaas Deneudt, Federico Drago, John Eriksson, Tiziana Ferrari, Teodor Georgiev, Giovanni Giuliano, Stefan Gruber, Jens Habermann, Katharina Heil, Tim Hubbard, Cristina Huertas Olivares, Georgios Kotoulas, Dimitris Koureas, Natalia Manola, Vanessa Marrocco, Nicolas Pade, Ana Portugal Melo, Antonello Provenzale, Fotis Psomopoulos, Niels Raes, Susie Robinson, Patrick Ruch, Dick Schaap, Adrian Stanica, Tassos Stavropoulos, Heliana Teixeira, Peter van Tienderen, Costas Tsigenopoulos, Robert Waterhouse, Giuseppe Aprea, Michel Boër, Ana Casino, Laurent Delauney, Jonathan Ewbank, Ana Lillebø, Michael Mirtl, Jana Pavlic-Zupanc, Lyubomir Penev, Jaume Piera, Paraskevi Pitta, Ingrid Puillat, David Richter, Diana Stepanyan, Anton Ussi, Jan Węsławski, Gabriela Zuquim

Abstract: The interdependence of human, animal, plant and ecosystem health necessitates systemic, cross-domain collaboration to address global challenges, such as emerging diseases, climate change and biodiversity severe change. Through the Crete Declaration, Europe’s (e-)infrastructures, organisations and projects that focus on the functioning of our biosphere commit to jointly advancing the One Health approach. In doing so, the signatories aim to strengthen Europe’s resilience and leadership through the sharing of data and expertise, the development of innovative solutions and the promotion of evidence-based policies.

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DOI: 10.3897/rio.11.e171643

Authors: Kesang Wangchuk

Abstract: The International Center for Integrated Mountain Development (ICIMOD) organised a two-day consultative workshop in Phuntsholing, Bhutan, focusing on human-wildlife conflict (HWC) management in the Himalayan mid-hills, a region often overlooked in favour of the foothills where human-elephant conflicts dominate. The workshop brought together key officials from Bhutan, India and Nepal to synthesise discussions across five thematic areas: Gender and Social Inclusion (GESI), Stakeholders and Partnerships, Risk Management, Monitoring and Evaluation (M&E) and Sustainability and Scaling of Solutions.The meeting highlighted stark gender disparities in HWC impacts, with women disproportionately affected due to their roles in resource collection and agriculture, yet marginalised in decision-making. Socio-cultural norms, caste hierarchies and financial constraints further restricted their participation. Children, the elderly and persons with disabilities also faced heightened risks. Stakeholder mapping identified NGOs, international donors, the private sector and media as crucial partners in mitigation, with varying degrees of involvement across countries. Risk management strategies emphasised species-specific deterrents, gender-inclusive rapid response teams and landscape-level interventions.Community-driven M&E systems, supported by technology (e.g. drones, AI cameras), were deemed essential for tracking conflict trends and intervention effectiveness. Sustainability hinged on strengthening local ownership, assured funding and policy integration. Persistent challenges included gender inequity, conflicting stakeholder interests and weak M&E systems. Future directions advocate for institutional reforms (e.g. gender quotas), alternative livelihoods and transboundary collaboration. The workshop underscored the need for inclusive, adaptive strategies to foster sustainable human-wildlife co-existence in the Himalayan mid-hills.

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DOI: 10.3897/rio.11.e167869

Authors: Elena Delgado Rivera, Lucas de Moncuit, Christos Arvanitidis

Abstract: LifeWatch ERIC’s Gender Equality Plan (2025–2027) sets out a clear roadmap for promoting gender equality and equity throughout the organisation. As a continuation of the first plan published in 2022, this updated version introduces more focused and ambitious measures. It reflects LifeWatch ERIC's ongoing commitment to creating a fair, inclusive and respectful working environment for everyone, regardless of gender identity, sexual orientation, age, ethnicity, disability or other personal characteristics.The plan is aligned with the European Commission's requirements for Horizon Europe and aims to make gender aspects an integral part of our internal policies, decision-making, human resources and research activities. Rather than introducing separate or additional measures or programme, the GEP aims to reinforce the LifeWatch ERIC Culture Principle by integrating new measures with existing policies, procedures and best practices that have an impact on equality and diversity in the organisation. Ultimately, this plan goes beyond compliance and represents a broader commitment to organisational excellence, fairness and responsibility, recognising that true innovation can only occur when diversity is fully embraced and supported at all levels.

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DOI: 10.3897/arphapreprints.e165615

Authors: Elena Delgado Rivera, Christos Arvanitidis

Abstract: LifeWatch ERIC’s Gender Equality Plan (2025–2027) sets out a clear roadmap for promoting gender equality and equity throughout the organization. As a continuation of the first plan published in 2022, this updated introduce more focused and ambitious measures. It reflects our ongoing commitment to creating a fair, inclusive, and respectful working environment for everyone, regardless of gender identity, sexual orientation, age, ethnicity, disability, or other personal characteristics.The plan is aligned with the European Commission's requirements for Horizon Europe and aims to make gender aspects an integral part of our internal policies, decision-making, human resources and research activities. Rather than introducing separate or additional measures or programs, the GEP aim to reinforce the LifeWatch ERIC Culture Principle by integrating new measures with existing policies, procedures and best practices that have an impact on equality and diversity in the organization. Ultimately, this plan goes beyond compliance and represents a broader commitment to organizational excellence, fairness, and responsibility, recognizing that true innovation can only occur when diversity is fully embraced and supported at all levels

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DOI: 10.3897/arphapreprints.e148125

Authors: Serena Rasconi, Laura Garzoli, Ana Gavrilović

Abstract: Abstracts of talks presented at ParAqua Conference held in Dubrovnik (Croatia), 16-17 April 2024

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DOI: 10.3897/rio.10.e138833

Authors: Lorna Mugambi, Gabriel Kiarie, Jason Kabi, Ciira wa Maina, Suvodeep Mazumdar

Abstract: The DSAIL-GeJuSTA Data Science Education Workshop was a joint initiative by the Centre for Data Science and Artificial Intelligence (DSAIL) and Gender Justice in STEM Research in Africa (GeJUSTA). GeJUSTA is a programme funded by the International Development Research Centre (IDRC) that is working towards increasing the representation of women in STEM. The workshop was held on 9 November 2023, during the 7th DeKUT International Conference on Science, Technology, Innovation and Entrepreneurship (STI&E) at Dedan Kimathi University of Technology (DeKUT). The conference ran from 8-10 November 2023. The event successfully convened 31 participants. The composition of the attendees was diverse, ranging from data-science educators, industry participants using data science, researchers who use data science and students in a myriad of courses, including engineering and pharmacy. The primary focus of the workshop was to have a discussion with the attendees and share practices around designing data-science curriculum, strategies for achieving gender equity in data-science education, addressing new technological challenges in education and fostering multidisciplinary approaches to data-science education. This report encapsulates the collective vision of the workshop participants, whose contributions have set the stage for progressive strides in data-science education.

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DOI: 10.3897/arphapreprints.e132163

Authors: Marit Schnepf, Simone Prestes Dürrnagel, Giacomo Laghetto, Teresa Pastor, Carol Ritchie

Abstract: NaturaConnect is a Horizon Europe research project, which aims to work closely with key stakeholders to co-develop tools and build capacity that will assist European Union Member States to design a resilient, coherent, and well-connected network of protected and conserved areas – the Trans-European Nature Network (TEN-N). The project aims to elicit stakeholder visions and to tailor knowledge and tools, resulting from engagement and dissemination efforts across Europe and in six specific case study areas. This report provides an overview of the stakeholder engagement during the first half of the project, outlines the capacity building approach and briefly discusses the main communication activities. An overview of applied methods in the stakeholder analysis, results from the stakeholder mapping and an evaluation of the engagement activities conducted until end of 2023 are described. Capacity building is a crucial project component in developing knowledge, understanding, skills and competences for users of the NaturaConnect frameworks, data and tools. The capacity building evaluation of this report focuses on the NaturaConnect Learning Platform and the NaturaConnect Training Needs Assessment. This mid-term report assesses engagement activities conducted until date in order to address any identified bottlenecks. The capacity building part provides an overview of applied methods and tools for assessing training needs and describes key features of the NaturaConnect Learning Platform.

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DOI: 10.3897/rio.9.e105155

Authors: Mathilde Bessert-Nettelbeck, Andreas Bischof, Ulrike Sturm, Emilia Nagy, Martina Schraudner, Julia Backhaus, Till Bruckermann, Susanne Hecker, Justus Henke, Karola Köpferl, Sabrina Kirschke, Christin Liedtke, Felix Mahr, Arne Maibaum, Audrey Podann, Wiebke Rössig, Martina Schäfer, Carolin Schröder, Philipp Schrögel, Victoria Shennan, Norbert Steinhaus, Mhairi Stewart, Vanessa van den Bogaert, Silke Voigt-Heucke

Abstract: Citizen science, transdisciplinary research, dialogic forms of science communication or public engagement: these and other research approaches and fields, often subsumed under participatory research, have in common that they enable people outside of academia to actively engage in the production of scientific knowledge. However, each of these fields sets its own goals, uses different formats and has a different scope and impact. The conference 'Opportunities and Limitations of Participation in Academia' held in September 2022 as part of the German Science Year 'Participate!' aimed to connect the various participation communities in Germany and to explore commonalities and success factors. Through intensive discussions in four working groups, a keynote speech and a panel discussion, the conference initiated an exchange of ideas and experiences amongst researchers in a converging field. This report is a summary of the key questions and outcomes of the conference.

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DOI: 10.3897/rio.9.e85860

Authors: Felicitas Kruschick, Kerstin Schoch

Abstract: Knowledge equity is a broad concept. Although it is linked to the goals of Open Science, it is rarely discussed in the scientific community. The term refers to a variety of aspects such as epistemology, research methods, data analysis, inclusive education, equal representation, participation, and science communication. It is reflected on individual, institutional, and structural levels.In this article, we attempt to outline the field theoretically against the background of a power-theoretical perspective and discuss what knowledge is in the first place. In a second step, we explore the question of what is hidden behind the terms equality and equity and to what extent these concepts can be linked to the underlying concept of knowledge. When can we speak of equity, why, and to what extent? Finally, the article links the overall social development of increasing sensitivity to diversity, which is discussed in conjunction with inclusive education and inclusion in general. Herein we refer to concepts of intersectional feminist research, the principles of Open Science, and a critical perspective on the concept of diversity.For illustration, exemplary projects associated with the Open Science Fellow Program, which address the issue of marginalized groups in the research process, are described. Among others, these relate to the following focal points: Data collection of non-binary gender, awareness of adultism, collaborative interpretation with interviewees, queer narratives, diversity in editorial boards, research in the context of North-South relations, participatory science communication using art, and exclusion factors of science communication.The overarching question we ask in this article is the extent to which knowledge equity is relevant to marginalized groups and exclusive dynamics in terms of an inclusive rationale and how those dynamics can be identified by using critical perspectives and self-reflexive considerations.

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DOI: 10.3897/rio.8.e95953

Authors: Ronit Purian, Natan Katz, Batya Feldman

Abstract: In this paper we aim to provide an implementation of the FAIR Data Points (FDP) spec, that will apply our bias detection algorithm and automatically calculate a FAIRness score (FNS). FAIR metrics would be themselves represented as FDOs, and could be presented via a visual dashboard, and be machine accessible (Mons 2020, Wilkinson et al. 2016). This will enable dataset owners to monitor the level of FAIRness of their data. This is a step forward in making data FAIR, i.e., Findable, Accessible, Interoperable, and Reusable; or simply, Fully AI Ready data.First we may discuss the context of this topic with respect to Deep Learning (DL) problems. Why are Bayesian Networks (BN, explained below) beneficial for such issues?Explainability – Obtaining a directed acyclic graph (DAG) from a BN training provides coherent information about independence variables in the data base. In a generic DL problem, features are functions of these variables. Thus, one can derive which variables are dominant in our system. When customers or business units are interested in the cause of a neural net outcome, this DAG structure can be both a source to provide importance and clarify the model.Dimension Reduction — BN provides the joint distribution of our variables and their associations. The latter may play a role in reducing the features that we induce to the DL engine: If we know that for random variables X,Y the conditional entropy of X in Y are low, we may omit X since Y provides its nearly entire information. We have, therefore, a tool that can statistically exclude redundant variablesTagging Behavior – This section can be less evident for those who work in domains such as vision or voice. In some frameworks, labeling can be an obscure task (to illustrate, consider a sentiment problem with many categories that may overlap). When we tag the data, we may rely on some features within the datasets and generate conditional probability. Training BN, when we initialize an empty DAG, may provide outcomes in which the target is a parent of other nodes. Observing several tested examples, these outcomes reflect these “taggers’ manners”. We can therefore use DAGs not merely for the purpose of model development in machine learning but mainly learning taggers policy and improve it if needed.The conjunction of DL and Casual inference — Causal Inference is a highly developed domain in data analytics. It offers tools to resolve questions that on the one hand, DL models commonly do not and, on the other hand, the real-world raises. There is a need to find a framework in which these tools will work in conjunction. Indeed, such frameworks already exist (e.g., GNN). But a mechanism that merges typical DL problems causality is less common. We believe that the flow, as described in this paper, is a good step in the direction of achieving benefits from this conjunction.Fairness and Bias – Bayesian networks, in their essence, are not a tool for bias detection but they reveal which of the columns (or which of the data items) is dominant and modify other variables. When we discuss noise and bias, we address these faults to the column and not to the model or to the entire data base. However, assume we have a set of tools to measure bias (Purian et al. 2022). Bayesian networks can provide information about the prominence of these columns (as they are “cause” or “effect” in the data), thus allow us to assess the overall bias in the database.What are Bayesian Networks?The motivation for using Bayesian Networks (BN) is to learn the dependencies within a set of random variables. The networks themselves are directed acyclic graphs (DAG), which mimic the joint distribution of the random variables (e.g., Perrier et al. (2008)). The graph structure follows the probabilistic dependencies factorization of the joint distribution: a node V depends only on its parents (a r.v X independent of the other nodes will be presented as a parent free node).Real-World ExampleIn this paper we present a way of using the DL engine tabular data, with the python package bnlearn. Since this project is commercial, the variable names were masked; thus, they will have meaningless names.Constructing Our DAGWe begin by finding our optimal DAG.import bnlearn as bnDAG = bn.structure_learning.fit(dataframe) We now have a DAG. It has a set of nodes and an adjacency matrix that can be found as follow:print(DAG['adjmat']) The outcome has this form Fig. 1a.Where rows are sources (namely the direction of the arc is from the left column to the elements in the row) and columns are targets (i.e., the header of the column receives the arcs). When we begin drawing the obtained DAG, we get for one set of variables the following image: Fig. 1b.We can see that the target node in the rectangle is a source for many nodes. We can see that it still points arrows itself to two nodes. We will discuss this in the discussion (i.e., Rauber 2021). We have more variables, therefore I increased the number of nodes. Adding the information provided a new source for the target (i.e., its entire row is “False”). The obtained graph is the following: Fig. 1c.So, we know how to construct a DAG. Now we need to train its parameters. Code-wise we perform this as follows:model_mle = bn.parameter_learning.fit(DAG, dataframe, methodtype='maximumlikelihood')We can change ‘maximulikelihood’ with ‘bayes’ as described beyond. The outcome of this training is a set of factorized conditional distributions that reflect the DAG’s structure. It has this form for a given variable: Fig. 1d. The code to create DAG presentation is provided in Fig. 2. DiscussionIn this paper we have presented some of the theoretical concepts of Bayesian Networks and the usage they provide in constructing an approximated DAG for a set of variables. In addition, we presented a real-world example of end to end DAG learning: Constructing it using BN, training its parameters using maximum likelihood estimation (MLE) methods, and performing and inference.FAIR metrics, represented as FDOs, can also be visualised and monitored, taking care of data FAIRness.

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DOI: 10.3897/rio.7.e71553

Authors: M.V. Eitzel

Abstract: In the face of the "crisis of reproducibility" and the rise of "big data" with its associated issues, modeling needs to be practiced more critically and less automatically. Many modelers are discussing better modeling practices, but to address questions about the transparency, equity, and relevance of modeling, we also need the theoretical grounding of social science and the tools of critical theory. I have therefore synthesized recent work by modelers on better practices for modeling with social science literature (especially feminist science and technology studies) to offer a "modeler’s manifesto": a set of applied practices and framings for critical modeling approaches. Broadly, these practices involve 1) giving greater context to scientific modeling through extended methods sections, appendices, and companion articles, clarifying quantitative and qualitative reasoning and process; 2) greater collaboration in scientific modeling via triangulation with different data sources, gaining feedback from interdisciplinary teams, and viewing uncertainty as openness and invitation for dialogue; and 3) directly engaging with justice and ethics by watching for and mitigating unequal power dynamics in projects, facing the impacts and implications of the work throughout the process rather than only afterwards, and seeking opportunities to collaborate directly with people impacted by the modeling.

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DOI: 10.3897/rio.6.e53921

Authors: Julia Prieß-Buchheit, Arja Aro, Iliyana Demirova, Dirk Lanzerath, Pavel Stoev, Nicolaus Wilder

Abstract: The Path2Integrity project is a two-component coordination and support action to enhance research integrity cultures. Path2Integrity develops and fosters role-models and rotatory role-play scenarios for secondary school students, undergraduates, graduates, and early career researchers. A Path2Integrity campaign for scientific facts about research integrity and role-models, raises awareness of research integrity within secondary schools and universities. A complementary Path2Integrity handbook of instructions, which contains vivid stories involving research integrity and rotatory role-playing increases students’ ability to form judgements about the acceptance or rejection of norms in research. A train-the-trainer program shows how to use the Path2Integrity handbook of instructions, especially how to apply the handbook to the educators’ discipline and how to implement it into organisations. Partners from the Consortium have award-winning experience in creating those settings, which allows Path2Integrity to work with educational practices already in existence. Taking into account that different disciplines and different schools of thought are involved, it is the Consortium’s paramount concern, to ensure explicitly that the Path2Integrity handbook and campaign are based on optimal and systematic evidence-based decisions.

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DOI: 10.3897/rio.4.e31827

Authors: Johanna Seibt, Christina Vestergaard

Abstract: This article introduces a new communicational format called Fair Proxy Communication. Fair Proxy Communication is a specific communicational setting in which a teleoperated robot is used to remove perceptual cues of implicit biases in order to increase the perceived fairness of decision-related communications. The envisaged practical applications of Fair Proxy Communication range from assessment communication (e.g. job interviews at Affirmative Action Employers) to conflict mediation, negotiation and other communication scenarios that require direct dialogue but where decision-making maybe negatively affected by implicit social biases. The theoretical significance of Fair Proxy Communication pertains primarily to the investigation of 'mechanisms' of implicit social cognition in neuropsychology, but this new communicational format also raises many research questions for the fields of organisational psychology, negotiation and conflict research and business ethics. Fair Proxy Communication is currently investigated by an interdisciplinary research team at Aarhus University, Denmark.

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DOI: 10.3897/rio.4.e26370

Authors: Pradeep Joseph

Abstract: The state of health disparities in the United States has remained relatively stable over a number of years. Although overall outcomes for all patients have improved, a difference persists in how different racial, ethnic, and gender groups have fared in our health care system. Many programs that have sought to combat this problem have been predicated on the belief that only a small number of providers in the medical community are aware of their own biases. Accordingly, it was believed that bias awareness is the direct conduit for this particular change in the health system. However, the results of such programs have been unsatisfactory. The reason for such ineffectiveness is that many programs have not taken into account the presence of implicit bias within the patient-provider relationship. This complex form of bias operates in specific ways, and must be dealt with appropriately. The use of digital checklists to aid in clinical decision making has proved to be both a way that patients can receive equitable care, and a way to improve overall patient outcomes. Secondly, in order to reach the most at-risk populations, health care must expand beyond the hospital walls, and out into the community. Nurse navigator programs have been shown to accomplish this with great success. Together, checklists and nurse navigators are the necessary next-step in the battle against health care disparities. What’s more, this two-pronged approach is relatively simple to implement. By making use of current electronic medical records, digital checklists can be quickly installed. Likewise, nurse navigator programs, a comparatively inexpensive option, can be rolled out quickly because of their simple design. A focus on the patient-provider relationship and community outreach is critical for progress in eliminating health care disparities.

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DOI: 10.3897/rio.3.e21702

Authors: Cameron Neylon

Abstract: HarassMap is an NGO based in Cairo that collects and maps crowdsourced data on sexual harassment in Egypt. Alongside this crowd-sourced data gathering it also offers training, workshops and advocacy programs, working with relevant parties to reduce the acceptability of all forms of sexual harassment. The project has been running since 2010 based on the Ushaidi platform. Over this time it has collected a very large number of mapped events reported largely by anonymous members of the public. The data has value both in terms of its richness; mapping data, category of harassment and descriptions are all recorded; and also as a longitudinal dataset that can inform on the success of interventions as well as the development of new forms of harassment. The project has been approached in the past by a number of researchers interested in using the data it has collected. The interest from HarassMap in Pilot Project participation was originally to obtain technical support to address how best to share data. While some technical advice was offered the focus on practice and planning was still useful. Identifying what data resources the project had, and in what form, allowed them to develop an online portal through which data can be made available to researchers on request.

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