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Communities in Gansu province in China store snow in the winter months for use in the dry summers.Credit: Hai Ying/EPA/Shutterstock

Among the world’s ‘poly-crises’, the crisis of water is one of the most urgent. Worldwide, around 2 billion people lacked access to safe drinking water in 2020; and an estimated 1.7 billion did not have even basic sanitation. Every year, more than 800,000 people die from diarrhoea, because of unsafe drinking water and a lack of sanitation. Most of those are in low- and lower-middle income countries. This is a mind-boggling and unacceptable situation. Even more so in an age when huge investments are being made in instant video calling, personalized medicine and talk of inhabiting other planets.In 2015, the international community declared tackling the water crisis one of the United Nations Sustainable Development Goals (SDGs). The sixth SDG commits the world to “ensure availability and sustainable management of water and sanitation for all”. But the UN acknowledges that SDG 6 is “alarmingly off track”.International diplomacy is finally starting to get its act together. In March, world leaders will assemble in New York City for the UN 2023 Water Conference. It will be the first such event in nearly half a century, a fact that by itself should shame us all.Last October, the UN published the results of a consultation with government representatives as well as specialist and stakeholder communities on their priorities for the conference. Around 12% of respondents were from education, science and technology fields. The consensus was that data and evidence, improved access to knowledge (including Indigenous and local knowledge) and open research will be essential to getting SDG 6 back on track. Delegates attending the March conference will be looking to harness the full spectrum of established water sources and technologies, including freshwater and rainwater sources, treated groundwater, desalinated seawater and hydropower.There’s a wealth of knowledge already out there, in the form of established technologies, innovative alternatives and research that captures centuries-old knowledge and the practices of communities themselves. In the past, such knowledge has been ignored, or what has been learnt has been forgotten. Twenty years ago, for example, the UN invested in a major piece of research that captured examples of how communities living in water-stressed regions have used research and innovation to access water. The research highlighted, for example, how people in arid regions of China store snow in cellars during the winter that can then be melted for use in the summer months.Prerequisites for tackling the water crisis include consolidating what is already known and building on that knowledge. That’s why on 19 January, the Nature Portfolio of journals launched Nature Water. This journal will provide a space for all researchers — including those in natural and social sciences, and in engineering — to collectively contribute their knowledge, insights and the results of their learning, so that the world is on a more equitable and sustainable track. The launch issue includes research in fundamental, applied and social science, as well as opinion and analysis. Our editorial teams are committed to facilitating open science1.Some paths forward are clear. Damir Brdjanovic at the IHE Delft Institute for Water Education in the Netherlands writes in Nature Water that there’s a vast body of research on alternatives to sewered sanitation — and how to use less or no water to safely dispose of faecal matter and inactivate pathogens2. There are alternatives to the flush toilet and underground, piped sewer networks. And Rongrong Xu at the Southern University of Science and Technology in Shenzhen, China, and colleagues report that there are ways to create hydropower, especially in Africa and Asia, without the same environmental and social impacts3.However, research does not exist in a vacuum. The representatives of low- and middle-income countries also want to prioritize funding. The South African government, in its response to the UN consultation, says that the annual cost to meet the SDG water and sanitation targets is between 2.3% and 2.7% of the country’s gross domestic product (between US$7 billion and $7.6 billion annually). A project called the Global Commission on the Economics of Water, co-chaired by economist Mariana Mazzucato and climate scientist Johan Rockström (among others), is promising “new thinking on economics and governance” in time for the conference.Conflict theoryThose who will be attending the conference in March also told the UN they want to see international cooperation be made a priority for water and sanitation, especially in an era of heightened geopolitical tensions. More than 25 years ago, former vice-president of the World Bank Ismail Serageldin famously wrote that twenty-first-century conflicts would be over water, rather than oil. We are fortunate that this has not yet happened, although Serageldin told Nature that relations between countries that share water sources are worsening. Egypt is formally in dispute with Ethiopia over dam-building projects on the Nile River; the same is true of India and Pakistan in the Indus River Basin.In its response to the UN, Egypt’s delegation observed that the majority of people rely on water sources that are shared between nations, most of which lack formal agreements, including all-important data sharing agreements. Rhea Verbeke, at the Catholic University of Leuven in Belgium, writes in Nature Water of the “sobering experience” of seeing no external submissions to an open database on water purification that was created more than one year ago4.The delegates assembling in New York need to accept that their countries’ visions will not be realized until all nations can somehow carve out a path to cooperate amid tension and conflict. Research can help to provide at least some of the right language, which is why it needs to be taken on board when decisions are being made. 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While much focus in recent years has been put on Open Access publishing, this is only a small part of Open Science. According to the 2015 FOSTER taxonomy19, Open Science integrates Open Access, Open Data, Open Source, and Open Reproducible Research (all of which we will touch on here, see Fig. 1a), while UNESCO and others have extended this further (e.g.,6). Open Data is commonly associated with the ‘FAIR Principles’20, which describe how to make data findable, accessible, interoperable, and reusable. The FAIR principles were introduced in 2016 and provide vital guidance that can be applied irrespective of whether the data itself is strictly open or not21. Note that the FAIR principles do not enforce Open Access, i.e., FAIR data is not automatically Open Data. Conversely, Open Data that is neither FAIR nor managed (see Fig. 1b) can easily be useless data. Thus, the combination of Open and FAIR data is extremely important. However, even Open Access publishing combined with Open and FAIR data does not necessarily make the research reproducible and re-usable, as discussed further below.Fig. 1: The many elements of Open Science.a, Open Science (centre, blue) and the four elements of Open Science pointed out by UNESCO most pertinent to this article (orange-ish circles with text). The remaining elements of Open Science described by UNESCO were removed for space reasons. They are represented in the ‘…’ circle along with the smaller decorative bubbles to show that Open Science covers many facets, big and small6. b, FAIR data vs. Open Data vs. Managed Data. Image modified from ref. 36. Managed data means that the data has in some way been collected, stored, organized and maintained. There is a large proportion of managed data that is neither FAIR nor Open, along with a large proportion of unmanaged Open Data. Since both cases are difficult to include in reproducible workflows, scientists and journals alike should be working on expanding the intersection between FAIR and Open Data.Full size imageOpen Access is the subset of Open Science that includes principles and practices for distributing research outputs online, free of cost or other access barriers22,23. This includes for instance Open Access publications (e.g., the dissemination of research as so-called Green, Gold or Diamond Open Access) or the use of preprint servers to access earlier versions of research articles.Open Data refers to the availability of the data behind the published research, typically hosted in either institutional or domain-specific data repositories (e.g., HydroShare for hydrological data24), or generic repositories such as Zenodo or FigShare. For Open Access publications and Open Data, appropriate license conditions should be stipulated, so that the conditions of re-use are clear. Creative Commons (CC) licenses are commonly used, with CC0 (public domain) and CC-BY (re-use with attribution) being the most permissive. Other restrictions on CC licenses can cause problems for downstream use. For instance, the ‘ND’ (no derivatives) clause forbids re-use for derivative works, i.e., any actual re-use other than re-distribution of the original work, while ‘NC’ (non-commercial use only) can prevent commercial companies (e.g., instrument vendors) from integrating Open Data into vendor-provided instrument libraries that could be used by researchers. The ‘SA’ (share-alike) clause can enforce a license on downstream users that they may not be able to comply with, thus preventing integration of Open Data in other open projects (due to incompatible licenses). While Open Data is an important starting point, without the availability of appropriate metadata and sufficient FAIRness to make the data findable, accessible, re-useable and interoperable, Open Data alone is only of limited use. In the era of ‘big data’, it is now relatively easy to create a quick dump of data, but curation and FAIRification of data requires a concerted effort, which may necessitate either incentives (carrot) or mandates (stick). The Global Natural Products Social Molecular Networking (GNPS) ecosystem25 is a prime example for incentivising Open Data sharing. Starting primarily as a mass spectral data repository for metabolomics, the developers have consistently added features and functionality over the years to value-add the repository and increase motivation for deposition. For example, MASST26 has enabled discovery of the neurotoxin domoic acid and analogues within marine samples and food such as ocean-caught mackerel.Open Source software and code refer to the public availability of source code27, i.e., sets of computer instructions ranging from data processing scripts and algorithms to fully blown numerical models, desktop applications, or even operating systems. The purpose of open source is to provide transparency, and most importantly, re-usability and adaptability of the code, with a common aim of collaborative development. Licenses for Open Source works are generally designed to explicitly cover code sharing, thus Open Source licenses are generally preferred over CC, with common examples including GPL, Apache and MIT27. Suitable code repositories with version control and issue tracking are indispensable for collaborative open source developments, with common platforms including GitHub, GitLab, Bitbucket and more. For all three above-mentioned aspects of Open Science, i.e., Open Access, Open Data and Open Source, the generation of permanent identifiers such as a Digital Object Identifier (DOI)28 is an integral aspect of FAIR and vital to preserve the discoverability and lifetime of such projects.Finally, open reproducible research is a culmination of all three aspects above. With systems such as RMarkdown and Jupyter Notebooks, it is now possible to have fully compliable research outputs and reproducible manuscripts. The Journal of Open Source Software even accepts submissions as GitHub pull requests and compiles the entire submission on their system; one example relevant to water research is patRoon 2.0 (ref. 29). The ‘open-source knowledge infrastructure for collaborative and reproducible data science’ Renku facilitates traceability and reproducibility of complex workflows involving networks of interconnected code, data and figure files. It does so by automatic provenance tracking of output files and the creation of a version-controlled git repository containing all information, including the computational environment. More