Blockchain Papers

Mariia Petryk, Jiasun Li

The successful operation of a blockchain system crucially relies on its management of software development activities. Not only does the technological functionality of a blockchain system depend on the quality of its source code, but also the “neutrality” of a blockchain system depends on access to and control over its source code. In this paper, we delve into the dynamic evolution of collaboration within the open-source developer community of Ethereum, a leading blockchain platform today. Utilizing network analysis techniques, we demonstrate the tendency of initially decentralized open-source communities to gravitate toward local modular structures. Additionally, our analysis reveals that inputs to the blockchain’s software code are concentrated among a small group of contributors. Our findings have implications for the managers of decentralized open-source technology and policymakers who aim to preserve impartial access to technology.

Talya Jesperson, Graham Jensen, Caroline Winter, Alyssa Arbuckle · 5 authors

This paper provides an update on the Canadian Humanities and Social Sciences (HSS) Commons, an in-development online hub for open social scholarship in Canada and beyond, and considers the next steps for the platform in an ever-evolving digital landscape. It outlines various recent outreach and engagement events intended to introduce the Canadian HSS Commons to the larger communities to which it belongs. Because the Canadian HSS Commons is committed to supporting the growth and evolving needs of these communities, this paper also considers how increasingly popular internet technologies such as Web3 and blockchain might play a part in the future of digital research infrastructure and the Canadian HSS Commons specifically. It concludes that while Web3 and blockchain currently raise important questions and concerns about governance, accountability, and commercialization, in the near future, these same technologies could also help engender new forms of functionality and participation on the Commons.

Anna Notaro

This article explores non-fungible tokens, better known as NFTs, or blockchain-based certificates of ownership for visual or physical assets, a cultural phenomenon which has come to the media attention following the sale of a non-fungible token photo collage, Everyday: The First 5,000 Days, for more than 69 million USD at a Christie's auction in March 2021. The sale made Mike Winkelman (aka Beeple) the third most valuable living artist, behind Jeff Koons and David Hockney starting off a conversation about NFTs which has covered a wide range of issues, including: the contested relationship between art and the market, the long debated question of collective and/or individual authorship within digital aesthetics, the most recent developments in Artificial Intelligence and their creative potential with regard to NFTs – i.e. the appearance of intelligent non-fungible tokens (iNFTs) – and, lastly, the role of cryptocurrencies as a tool for artists’ empowerment or, conversely, as a selling out, under new technological guises, to the capitalist logic of the market. The article reviews and evaluates such debates with the aim to offer critical pointers to help the reader navigate the emerging world of Crypto art.

Markus Putnings

The article describes the use and possible value creation of Non-Fungible Tokens (NFT) in the academic and open access publishing environment. It defines NFTs, describes disadvantages and possible solutions, especially in the intended scientific environment. An overview of existing NFT service providers from the publishing environment illustrates that there is not yet a suitable one for researchers. Accordingly, three possible scenarios are shown where NFT services could be located in a science-friendly way. One would be with library- or scholarly-led university presses, repositories, and other publication infrastructures (such as OJS or OMP). Another would be to use centralizing and channelling article submission platforms with which universities have contracts, such asChronosHub. The third and broadest approach would be through Digital ObjectIdentifier (DOI) registration agencies such as ChronosHub and DataCite, although complexities come into play here due to the triangular relationship with publishers registering DOIs (some of them having exclusive usage rights transferred to themselves). This complexity could be reduced by registeringNFTs only for open access publications with a Creative Commons Attribution license. A summary and outlook provide an overview of open questions and initial starting points to get started.

Chris Mao

Non-fungible tokens (“NFTs”) are an emerging digital asset that has captured global attention with multi-million-dollar price tags for seemingly basic pixelated JPEG files. In March 2021, British auction house Christie’s sold a digital artwork, ‘Everydays: The First 5,000 Days’, by artist Mike Winkelmann (“Beeple”) for the Ether equivalent of $69.3 million, making it the third-most expensive artwork by a living artist.1 Beeple’s sale was by no means alone—Sotheby's sold an NFT collection of 101 ‘Bored Apes’ for $24.4 million;2 CryptoPunk #7804, one of 10,000 unique ‘CryptoPunk’ NFTs sold for $7.56 million,3 and Twitter founder Jack Dorsey’s first-ever tweet sold for $2.9 million as an NFT.4 NFT sales in the first-half of 2021 have already exceeded $2.5 billion,5 and, as of October 2021, the total value of NFTs on the Ethereum blockchain is estimated to be at least $14.3 billion.6 On one hand, NFTs may be poised to revolutionize creative industries and drastically alter consumer interaction with digital media.7 On the other hand, the NFT market is simultaneously both ripe for speculative investment and vulnerable to criminal activity.8 To date, there appears to be no consensus on the regulation of NFTs, neither from the perspective of generally applicable laws, regulatory capture under existing financial market regulation, nor the implementation of new digital asset laws. This paper attempts to highlight several pertinent dangers of NFTs, from a profound misunderstanding of what an NFT transaction entails, their bubble-like pricing, to various criminal activity concerns. By illustrating how existing laws and regulations may not fully capture nor address these dangers, as well as the potential oversight of NFTs in newly proposed digital asset laws, this paper proposes a categorial approach to regulating NFTs, by reducing the current (and likely future) use-cases of NFTs to their constituent categories and in turn, suggesting the most appropriate regulatory approach to each. Ultimately, given the (potential) wide-ranging use-cases of NFTs, this paper proposes that the NFT’s intended use-case described in broad categorical terms, or more aptly, its underlying reference asset and simultaneous conveyance, or lack thereof, should dictate the regulatory approach.

Barend Mons

This personal reaction is written from multiple perspectives. First and foremost, as the corresponding author of the original FAIR article. Second as the chair of the first High Level Expert Group (HLEG) of European Open Science Cloud (EOSC) (which is how I met Jean-Claude) and third from my current GO FAIR and CODATA perspective. None of what I write below is to be seen as a formal position of any of the organisations I am associated with.Let me start by stating that, after some periods silent of hope and of deep despair, I now strongly feel that, with the governance of the EOSC Association in place, EOSC will become a success after all. It will still be critical that the Association involves the member states (MSs) and actual researchers in an agile and non-bureaucratic manner, for which we need bottom-up mechanisms such as operated by the Research Data Alliance (RDA) and GO FAIR. But a balancing formal entity operating along the formalised Strategic Research and Innovation Agenda [1] and the Partnership proposal as well as the various “declarations” including the recent one under the German presidency [2] are an excellent guiding roadmap to a successful EOSC, obviously in global context.That said, at the risk of sounding like broken record, this reaction should also look at the points where it went “almost” wrong, as we should try and learn from our mistakes. I may make some enemies—or strengthen the opinion of existing ones—in the process, but then, a wise old friend, who also wrote one of the reactions once told me: “Barend, unless you made some enemies you probably lived in vain.” So I will speak my mind (“what's new'?). I also like to say that ”EOSC“ brought me some real new friends for life!First of all, the fact that quickly after its inception FAIR became a hype term①, which was probably partly even accelerated by the prominent role it played in early EOSC discussions with EC's Director General, also has its downsides. Like for the term “AI”, everyone co-opts the term and some start watering the concept down to a bloodless caricature from what it originally meant. In the case of FAIR this includes removing the central notion of machine actionability, mis-characterising it as a standard, conflating it with “open”, only linking it to data sensu stricto, ignoring software, algorithms and more. In general terms, people that sometimes seem to have never read the original article [3], the most flagrant abuse of the term I have heard (obviously not from an active researcher) is this: “If data are Findable, Accessible and Interoperable it is ”automatically' Reusable.“ This is of course ”swearing in FAIR church“ as the R (principles R1–3) [3] clearly state that rich provenance and reuse conditions are critical and in particular the provenance. The decision whether (even high quality) data are fit for purpose (reuse in a particular study) is a critical step and is imho (in my humble opinion) at the basis of the reproducibility problem we currently face. Therefore, I would like to re-emphaisize here my current one liner to summarise the aim of the FAIR guiding principles: ”The Machine Knows what I mean“. Those who feel that FAIR is too ambitious and for instance promote that ”achieving F and A is enough for now“ in my humble opinion fail to see the disruptive character of the solutions we need to make EOSC and its sister around the globe a real paradigm shift towards Open Science (OS). Or they are just trying to preserve the status quo and move incrementally at a pace they can follow.This nicely bridges to the first observation on EOSC as such. I indeed think that the first “Communication” that needed 126 iterations mentioned by Jean-Claude, which happened in the same time frame as our “HLEG-1” period, was symptomatic for a basic flaw in the discussions, which haunts us still today. Conflating the “ICT”/HPC (or basic e-infrastructure) with the data and end user applications for analytics, has caused an enormous hurdle. In the entire journey of the HLEG we had to carefully navigate around this cliff and it is still a highly controversial issue today. This part was the “Dunning Kruger effect” [4] pur sang: The “other side is easy” (because I am not hindered by any knowledge about it) and is “more or less already done” (because I do not understand the complexity). This is not only true for the active researchers who cannot use the current e-infrastructure efficiently (and naturally that is “entirely the fault of the nerds who build things I do not understand or cannot operate”), but also for e-infrastructure engineers who know everything about ICT and “thus” (?) also about data (because “that is just ones and zeros”) as Jean- Claude also noted. I also believe however, that it is a mistake to completely separate e-infrastructure for the data and services layer, as the e-infrastructure should route (and understand at least at middleware level) what processes are needed on the data and how the FAIR services “run”. Nowadays (after many iterations) I use the diagram below (Figure 1) to explain that all three basic elements of the “Internet of FAIR Data and Services” are needed. Each of them should be adorned with FAIR (machine actionable) metadata to seamlessly form a Web of FAIR Data and Services on top of the current, proven Internet backbones, thus forming the “Internet of FAIR Data and Services”, eventually creating an “Internet for Social Machines” [5] where people and machines can both efficiently use all services, independently and in collaboration.This does absolutely not mean that the foundation (e-infrastructure) of the triangle is “trivial” or “can be reused as is”. Not only middleware, but also the crucial and fundamental concept of FDOs needs to be developed in close collaboration between data and computer experts and is largely domain-agnostic.The seamless combination will become the principle “package” of information that machines (and also people) can understand and act upon. Major infrastructure builders should actually co-lead this, while domain scientists need to decide on which data formats and metadata schemes (i.e. FAIR Implementation Profiles [9]) should be built on this basic schema.Together with the Dunning Kruger effect, too many overlapping and redundant projects supporting the talking/meeting/landscaping, re-landscaping and re-re landscaping' has resulted in what I became to call the “EOSC is a bigger Me syndrome”. On the one hand, countless people voluntarily invested (and still invest) their time in the development of the EOSC, but others seem to only see EOSC as “yet another way to collect EC funding for their current solutions that are in my opinion not future- and OS proof. This misbalance between people investing their own time and effort based on intrinsic motivation and vision and on the other hand the ”reliance on EC subsidy“ caused a dichotomy during the scoping years of EOSC between disruptive and ”preservative“ approaches. The heavy reliance on EC subsidy also largely ignored the subsidiarity principle [10] and the fact that 90% of the eventual infrastructures and services that we need for EOSC will be paid by the MSs. Also data and research intensive industry was largely kept out of the loop, which was another mistake I have frequently pointed out. This helped to create and sustain the ”Brussels Bubble“ that Jean-Claude described. The Association will hopefully reverse that trend.Finally, the influence on the HLEG report of the then-commissioner was rather profound. The report was not only delayed almost 6 months after its proposed publication version, but there is also a nice additional “untold story” here: The originally proposed title of the report was: “A Cloud on the 2020 Horizon”. In my original foreword I explained the slightly “glooming” connotation of that title. When the report was finally approved, it appeared that the title had been unilaterally changed into “Realising A European Open Science Cloud [11]”. Not only did I have to hastily change my foreword (because it made no sense anymore) but also, my notorious statement that the “result” should neither be “European” (only), nor Open (only) nor (only) for Science and certainly not (just) a “Cloud” was entirely ignored in changing that title. But it again emphasises the “This is an EC thing” context, with the associated risk for confiscation of the concept by the “usual suspects” in EC subsidy land. However, I feel after three years of intensive deliberations, which may be considered lightning fast on the geological time scale, see George's reaction, we can conclude that most of the original HLEG recommendations are well-represented in the basic guiding documents of the EOSC Association, which makes me a happy man at the end of this crazy year.That leads me to the final observation: As a result of the (quote from Jean-Claude): “non-paper seen as the political turning point in support of EOSC” [12], GO FAIR (Global Open FAIR) [13] was started, originally by Germany and The Netherlands and soon joined by France as a temporary “kick-start”, bottom-up approach to accelerate EOSC (see also recommendation I-2.1. in the HLEG report, annex 1).Soon, GO FAIR became really global and the agile modus operandi of practical Implementation Networks yielded a number of crucial approaches to speed up the adoption of the FAIR guiding principles and the hourglass approach [14]. Now, late 2020, when the EOSC Association is a fact, GO FAIR (1.0) has achieved its goals (early implementation steps) and we need to reflect on its future. Next to the intrinsic value of the active GO FAIR IN community [15] as such, several particular assets that I need to mention here are the development of the FAIR Implementation Profile and Metadata4Machines approach, the development of easy to install FAIR data points for open, FAIR metadata publication and indexing, and last but not least the international effort (involving many players, also outside the direct GO FAIR initiative) to develop the minimal specs of the FDO framework [7] in a more specified form than when coined in the FAIR expert group report [5]. These assets (all open source and open access) can be carried over, not only to EOSC, but will have much wider, international, impact most likely leading to a continuation of GO FAIR (2.0) beyond its original time scope, namely three years, the predicted time it would take to complete the international policy and bureaucracy process to reach the status of a formal association as we have today. I hope the leaders of the Association will optimally learn from the successes and failures and near-road-accidents of the last three years and see EOSC as the European contribution to a “Global Open Science Commons”, also known as the Internet of FAIR Data and Services, in full, open collaboration with the international organisations that are now joining forces in the Data Together initiative [16]. After all, the major challenges we face are global, so is the research needed to face them and so are the solutions we hope to fiend. I fully trust the current leadership of the association to make that vision reality.Policy recommendationsGovernance recommendationsImplementation recommendations

Raiane Coelho, Regina Braga, José David, Mário A. R. Dantas · 6 authors

Nowadays, scientific experiments are conducted collaboratively. In collaborative scientific experiments, we must consider aspects such as interoperability, privacy, and trust in shared data to allow the reproducibility of the results. A critical aspect associated with a scientific process is its provenance information, which can be defined as the origin or lineage of the data that helps understand the scientific experiment results. Another concern when conducting collaborative experiments is confidentiality, considering that only authorized personnel can share or view results. In this paper, we propose BlockFlow, a blockchain-based architecture, to bring reliability to the collaborative research, considering the capture, storage, and analysis of provenance data related to a scientific ecosystem platform (E-SECO).

Andrea Margheri, Massimiliano Masi, Abdallah Miladi, Vladimiro Sassone · 5 authors

No abstract is available for this record.

Artyom Kosmarski, Nikolay Gordiychuk

In this paper, we propose a novel framework for a scholarly journal, a token-curated registry (TCR). This model originates in the field of blockchain and cryptoeconomics and is essentially a decentralized system where tokens (digital currency) are used to incentivize quality curation of information. TCR is an automated way to create lists of any kind where decisions (whether to include N or not) are made through voting that brings benefit or loss to voters. In an academic journal, TCR could act as a tool to introduce community-driven decisions on papers to be published, thus encouraging more active participation of authors and reviewers in editorial policy and elaborating the idea of a journal as a club. TCR could also provide a novel solution to the problems of editorial bias and the lack of rewards/incentives for reviewers. In the paper, we discuss core principles of TCR, its technological and cultural foundations, and finally analyze the risks and challenges it could bring to scholarly publishing.

Mélanie Clément‐Fontaine, Roberto Di Cosmo, Bastien Guerry, Patrick Moreau · 5 authors

Software is a hybrid object in the world research as it is equally a driving force (as a tool), a result (as proof of the existence of a solution) and an object of study (as an artefact). This specific status means we need to define strategies, tools and procedures which are adapted to the various issues it raises. These include the citation of contributions to software design and production, the reproducibility of research results involving software and the wider usage and long-term sustainability of the software heritage created. This opportunity note by the Committee for Open Science's Free Software and Open Source Project Group describes the issues at stake and formulates actionable recommendations.

José Padarian, Alex B. McBratney

Abstract. Data sharing and collaboration are critical to solving large scale problems. The prevailing soil data-sharing model is based on different groups sending their data to a lead party. This model is of a centralised nature and, consequently, results in the participants ceding their control and governance over their data to the lead party. Here we explore the use of a distributed ledger (blockchain) to solve the aforementioned issues. We explain what a blockchain is and some of its characteristics to then describe some features of a blockchain that makes it an interesting candidate for an inter-institutional database. Finally, we describe the potential use case of developing a global soil spectral library with multiple, independent international institutions constituting the network.

Navya Gouru, Nagalakshmi Vadlamani

The potentiality of Blockchain technology is widespread and applied to diverse fields. Blockchain is a distributed ledger of transactions that store immutable records in chronological order in an append-only mode. Hence, humongous data is stored on the blockchain and will continuously expand over time. Blockchain has been rapidly adopted by many businesses for storing the provenance data because of its salient features like immutability, robustness and tamperproof. Blockchain stores data provenance as transactions that are collected from sources like a centralized cloud or decentralized cloud that helps in identifying cybercrimes. This paper emphasizes on the different approaches of querying the data provenance transactions stored in Ethereum Blockchain based on various search parameters using REST API web services. The approach not only queries based on the first-class data elements like blocks, transactions, account address and contract address but also queries based on the provenance data stored on the Ethereum Blockchain explained with a use case LegalProv.

Petter Tunstad

With data intensive computing helping advance state-of-the-art in varied fields, data provenance and lineage continue to remain formidable challenges in assisting with integrity and reproducibility in research and applications. This is particularly challenging for distributed scenarios, where data may be originating from decentralized sources without any centralized control by a single trusted entity. To date most of the data provenance systems are specific to particular domains, and are often centralized. Distributed ledgers such as blockchains have proved quite popular and effective in addressing trust and consensus without central control. There are a few recent proposals to employ blockchains for data provenance, however, they rely on currency in order to propose transactions using public blockchains.\n\nWe present HyperProv, a general framework for data provenance based on the permissioned blockchain Hyperledger Fabric (HLF), and to the best of our knowledge, the first provenance system that is ported to ARM based devices such as Raspberry Pi (RPi). HyperProv records the operation history and data lineage by tracking checksums, editors, timestamps, data pointers, dependencies, and more. Provenance data is retrieved and stored through a NodeJS client library to simplify interactions with the blockchain. HyperProv has a set of built-in queries using smart contracts that enable lightweight retrieval of large collections of provenance data. We evaluate the throughput, latency and resource consumption of HyperProv on x86-64 desktop machines, as well as RPi, demonstrating the feasibility of using HyperProv on RPi for tamperproof data provenance, useful in particular for Internet of Things use cases.

Maribel Acosta, Tim Berners‐Lee, Stefan Dietze, Anastasia Dimou · 9 authors

Decentralised data solutions bring their own sets of capabilities, requirements and issues not necessarily present in centralised solutions. In order to compare the properties of different approaches or tools for management of decentralised data, it is important to have a common evaluation framework. We present a set of dimensions relevant to data management in decentralised contexts and use them to define principles extending the FAIR framework, initially developed for open research data. By characterising a range of different data solutions or approaches by how TRusted, Autonomous, Distributed and dEcentralised, in addition to how Findable, Accessible, Interoperable and Reusable, they are, we show that our FAIR TRADE framework is useful for describing and evaluating the management of decentralised data solutions, and aim to contribute to the development of best practice in a developing field.

Emanuel E. Bessa, Joberto S. B. Martins

The Blockchain technology was initially adopted to implement various cryptocurrencies. Currently, Blockchain is foreseen as a general purpose technology with a huge potential in many areas. Blockchain-based applications have inherent characteristics like authenticity, immutability and consensus. Beyond that, records stored on Blockchain ledger can be accessed any time and from any location. Blockchain has a great potential for managing and maintaining educational records. This paper presents a Blockchain-based Educational Record Repository (BcER2) that manages and distributes educational assets for academic and industry professionals. The BcER2 system allows educational records like e-diplomas and e-certificates to be securely and seamless transferred, shared and distributed by parties.

Tom Hill

Key points Digital Science's paper is one of the first looking at the application of blockchain technology in scholarly publishing. Wholesale use of blockchain technologies is suggested as a possible replacement for scholarly publishers. There remain questions around the adoption of blockchain technologies, including privacy, researcher support, and fraudulent use. Blockchain technologies may provide a new means of understanding problems and customers' evolving expectations, but careful consideration is required of whether blockchain is the best solution.

Krzysztof Janowicz, Blake Regalia, Pascal Hitzler, Gengchen Mai · 8 authors

Distributed ledger technologies such as blockchains and smart contracts have the potential to transform many sectors ranging from the handling of health records to real estate. Here we discuss the value proposition of these technologies and cryptocurrencies for science in general and academic publishing in specific. We outline concrete use cases, provide an informal model of how the Semantic Web journal's peer-review workflow could benefit from distributed ledger technologies, and also point out challenges in implementing such a setup.

Bonnie Lawlor

This paper offers an overview of the highlights of the NFAIS Conference, Blockchain for Scholarly Publishing, that was held in Alexandria, VA from May 15–16, 2018. The goal of the conference was to take a close look at the initiatives that have emerged as a result of the increasing global acceptance of blockchain technology. This technology, chiefly known as the foundation of Bitcoin and originally introduced as a means of securely managing cryptocurrency, has proven to have practical applications beyond finance. The basic technology is that of a distributed ledger and it is being broadly-adopted by multiple industries, including the scholarly publishing community. The capabilities of this new technology are prompting a direct exchange among stakeholders, as blockchain promises a more structured, decentralized, and immutably secure approach that has the potential to significantly impact researcher workflows - from data collection to peer review to access and published work. The technology inspires passion - there are those who believe that it will ultimately transform our lives while others are completely skeptical. The NFAIS conference provided a look at both sides of the coin (no pun intended).

Adrian-Tudor Pãnescu, Vasile Manta

This article presents a new method for managing digital reuse rights of research data, which leverages technologies such as the blockchain and smart contracts. This allows, on one hand, the creation of a permanent record on the agreements between the authors of the data and the reusers, with the possibility of verifying compliance at any time, and on the other hand, a higher level of granularity on defining the conditions of reuse. A practical implementation of such a workflow using the Solidity smart contract language is included, along with a brief analysis over the Ethereum blockchain network.

Shah Hassan

The purpose of this thesis was to investigate and study the various issues faced by educational and technological researchers while raising the funds for their respective projects and the issues faced by the fund’s providers. Multiple existing traditional fundraising platforms were identified, and their advantages and disadvantages were studied to check if it was suitable for educational and technological researchers to carry on their funding campaign using the existing platforms. Finally, the goal was to develop a decentralized research funding application which would replace the existing traditional methods of raising funds by providing the researchers the ability to create a fundraising campaign on Ethereum blockchain while ensuring the transparent and auditable usage of the funds provided for the development of the project by the stakeholders.\n\nThe research funding application was developed and deployed to Ethereum blockchain. During the development process, the technologies used were Solidity, HTML, CSS, Javascript and React. The requirements for the Minimum Viable Product of the research funding application were finalized and the project was implemented by following the Waterfall software development model. \n\nAs a result, the requirements set for the research funding application were accomplished and the application was deployed to the blockchain and can be accessed by the general public. Furthermore, additional features such as the ability to create and manage multiple funding campaigns by a single entity were also developed successfully.

Charlotte Pascoe, Gerry M Devine

PIMMS (Portable Infrastructure for the Metafor Metadata System) provides institutions with tools to capture information about the workflow of running simulations from the design of experiments to the implementation of experiments via simulations running models. PIMMS uses the Metafor methodology for simulation documentation which consists of a common information model (CIM), a set of controlled vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web infrastructure and portal.PIMMS will refactor the "CMIP5 questionnaire" metadata management tool, that is collecting climate model metadata for the CMIP5 model inter-comparison project, so that it can be more easily portable into stand alone installations within the university environment and customised to address the specific requirements of individual research groups. Initial model descriptions may take time to complete but once they have been cre ated the PIMMS infrastructure can be used to document subsequent variations by describing only those elements that are changed. An established PIMMS infrastructure will fit seamlessly into the research metadata workflow and significantly reduce subsequent documentation effort. The key to the customisation of PIMMS is in the modularity of its tools and the clear separation of structure (CIM) from content (CV). The PIMMS project will extend the CMIP5 controlled vocabulary to encompass descriptions of paleoclimate models and will also demonstrate how the CIM can be used to document an Integrated Assessment Model (IAM). This proof of concept prototype will create a new controlled vocabulary in collaboration with Ermitage and use it to reconfigure PIMMS to collect metadata in a different discipline. PIMMS will further explore how the CV that is used to configure PIMMS may be of further use to our stake holders and the wider JISC community through the development of the Uni versity of Cambridge chemicaltagger tool. PIMMS will provide a local portal so that research groups can view and search their own content, as well as publish their metadata content to institutional, national and international services. In addition PIMMS will also include data node software so that data documented with PIMMS can also be published to the web, both locally, and to national and international services.