Abstract Blockchain infrastructures have emerged as a disruptive technology and have led to the realization of cryptocurrencies (peerâtoâpeer payment systems) and smart contracts. They can have a wide range of application areas in eâScience due to their open, public nature and global accessability in a trustless manner. We propose and implement a smart contract called eBlocBroker, which is an autonomous blockchainâbased middleware system for volunteer computing and providing data resources for eâScience. The eBlocBroker infrastructure connects requesters who need to combine applications (jobs) with datasets and run them via an Ethereumâbased private blockchain network (Bloxberg) on providers that utilize computational and data resources on clouds or home servers. It uses cloud storage, such as B2DROP, IPFS, or Google Drive, to store and transfer data between requesters and providers. Each provider utilizes the Slurm workload manager to execute jobs submitted through eBlocBroker. In this paper, we demonstrate how an autonomous organization programmed as a smart contract can be used to deploy a marketplace that supports data and computationâintensive research projects. We propose a cost model implemented as a function in the smart contract which calculates and records computation and dataset usage costs. We develop a Pythonâbased system to communicate with eBlocBroker and orchestrate jobs' execution on the provider's end. We present eBlocBroker's features, infrastructure, implementation, algorithms and experimental results.
Yutian Chen, Cong Peng, Yu Dai, Min Luo · 5 authors
Multi-scalar multiplication (MSM) is an important building block in most of elliptic-curve-based zero-knowledge proof systems, such as Groth16 and PLONK. Recently, Lu et al. proposed cuZK, a new parallel MSM algorithm on GPUs. In this paper, we revisit this scheme and present a new GPU-based implementation to further improve the performance of MSM algorithm. First, we propose a novel method for mapping scalars into Pippengerâs bucket indices, largely reducing the number of buckets compared to the original Pippenger algorithm. Second, in the case that memory is sufficient, we develop a new efficient algorithm based on homogeneous coordinates in the bucket accumulation phase. Moreover, our accumulation phase is load-balanced, which means the parallel speedup ratio is almost linear growth as the number of device threads increases. Finally, we also propose a parallel layered reduction algorithm for the bucket aggregation phase, whose time complexity remains at the logarithmic level of the number of buckets. The implementation results over the BLS12-381 curve on the V100 graphics card show that our proposed algorithm achieves up to 1.998x, 1.821x and 1.818x speedup compared to cuZK at scales of 221, 222, and 223, respectively.
Scalability in blockchain remains a significant challenge, especially when prioritizing decentralization and security. The Ethereum community has proposed comprehensive data-sharding techniques to overcome storage, computational, and network processing limitations. In this context, the propagation and availability of large blocks become the subject of research to achieve scalable data-sharding. This paper provides insights after exploring the usage of a Kademlia-based Distributed Hash Table (DHT) to enable Data Availability Sampling (DAS) in Ethereum. It presents a DAS-DHT simulator to study this problem and validates the results of the simulator with experiments in a real DHT network, InterPlanetary File System (IPFS). Our results help us understand what parts of DAS can be achieved based on existing Kademlia DHT solutions and which ones cannot. We discuss the limitations of DHT solutions and discuss other alternatives.
Abstract Scientific workflows are essential for many applications, enabling the configuration and execution of complex tasks across distributed resources. In this paper, we contribute an Ethereum blockchain-based scientific workflow execution manager, which distributes workflows to run on cluster computing providers that utilize the Slurm workload manager to execute them. We extended our blockchain-based autonomous resource broker called eBlocBroker, which is a DAO-based decentralized coordinator, by providing distributed workflow execution via blockchain. Through various tests, we demonstrate how our eBlockBroker autonomous organization, which is programmed as a smart contract, can manage scientific workflow submission, scheduling, and execution on cluster computing providers. The utilization of blockchain for distributed workflow execution is a new concept. We are motivated because our system has been developed with e-Science in mind where scientific workflows are widely utilized.
Principal Engineer, Discover Financial Services, Houston, TX, USA, AdisheshuReddy Kommera
The Event-Driven Data Mesh Integration pattern revolutionizes modern data sharing by blending eventdriven architecture and the data mesh paradigm. This innovative approach decentralizes data ownership, enabling organizational domains to manage their data autonomously while ensuring real-time responsiveness and seamless scalability. Central to the pattern are event broker layers, domain-oriented data producers, event enrichment nodes, and a self-serve data product catalog. Key features include schema validation, policy-based governance, and real-time enrichment, fostering efficiency, compliance, and agility. Integrating AI-powered self-healing mechanisms further enhances resilience, automates recovery processes, and optimizes resource allocation. Applications span various sectors, from operational systems to analytics pipelines, enabling real-time decision-making and continuous improvement. This approach empowers organizations to innovate faster while maintaining robust data governance, scalability, and interoperability across autonomous domains, paving the way for intelligent and dynamic data ecosystems.
Fernando Bereta dos Reis, Mark Borkum, Monish Mukherjee, Hayden Reeve · 5 authors
This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.
Conor Flynn, Kristin P. Bennett, John Erickson, Aaron Green · 5 authors
With the agile development process of most academic and corporate entities, designing a robust computational back-end system that can support their ever-changing data needs is a constantly evolving challenge. We propose the implementation of a data and language-agnostic system design that handles different data schemes and sources while subsequently providing researchers and developers a way to connect to it that is supported by a vast majority of programming languages. To validate the efficacy of a system with this proposed architecture, we integrate various data sources throughout the decentralized finance (DeFi) space, specifically from DeFi lending protocols, retrieving tens of millions of data points to perform analytics through this system. We then access and process the retrieved data through several different programming languages (R-Lang, Python, and Java). Finally, we analyze the performance of the proposed architecture in relation to other high-performance systems and explore how this system performs under a high computational load.
In the rapidly evolving domain of distributed ledger technology, scalability and interoperability have become paramount challenges for both academic and industry sectors. In this paper, we introduce a comprehensive formal model to address atomic composability across multiple rollups on Ethereum. The proposed model incorporates mechanisms like buffering, dependency management, concurrency control, and the groundbreaking zero-knowledge proofs. Moreover, we evaluate its practical repercussions, strengths, and weaknesses, ensuring resilience against manipulative or erroneous actions. The application of the proposed model to shared sequencers and other existing solutions accentuates its versatility and universality.
The InterPlanetary File System (IPFS) is currently the largest decentralized storage solution in operation, with thousands of active participants and millions of daily content transfers. IPFS is used as remote data storage for numerous blockchain-based smart contracts, Non-Fungible Tokens (NFT), and decentralized applications. We present a content censorship attack that can be executed with minimal effort and cost, and that prevents the retrieval of any chosen content in the IPFS network. The attack exploits a conceptual issue in a core component of IPFS, the Kademlia Distributed Hash Table (DHT), which is used to resolve content IDs to peer addresses. We provide efficient detection and mitigation mechanisms for this vulnerability. Our mechanisms achieve a 99.6\% detection rate and mitigate 100\% of the detected attacks with minimal signaling and computational overhead. We followed responsible disclosure procedures, and our countermeasures are scheduled for deployment in the future versions of IPFS.
Non-fungible tokens (NFTs) are becoming increasingly popular in Play-to-Earn (P2E) Web3 applications as a means of incentivizing user engagement. In Web3, users with NFTs ownership are entitled to monetize them. However, due to lack of objective NFT valuation, which makes NFT value determination challenging, P2E applications ecosystems have experienced inflation. In this paper, we propose a method that enables NFT inflation value management in P2E applications. Our method leverages the contribution-rewards model proposed by Curve Finance and the automated market maker (AMM) of decentralized exchanges. In decentralized systems, P2E Web3 applications inclusive, not all participants contribute in good faith. Therefore, rewards are provided to incentivize contribution. Our mechanism proves that burning NFTs, indicating the permanent removal of NFTs, contributes to managing inflation by reducing the number of NFTs in circulation. As a reward for this contribution, our method mints a compensation (CP) token as an ERC-20 token, which can be exchanged for NFTs once enough tokens have been accumulated. To further increase the value of the CP token, we suggest using governance tokens and CP tokens to create liquidity pools for AMM. The value of the governance token is determined by the market, and the CP token derives its value from the governance token in AMM. The CP token can determine its worth based on the market value of the governance token. Additionally, since CP tokens are used for exchanging NFTs, the value of the NFT is ultimately determined by the value of the CP token. To further illustrate our concept, we show how to adjust burning rewards based on factors such as the probability of upgrading NFTs' rarity or the current swap ratio of governance and CP tokens in AMM.
Since its inception as one of the Bitcoin's underpinning technologies, the concept of Blockchain has traversed a long way from being merely a secure distributed ledger meant only for storing cryptocurrencies-based financial transactions to implementing innovative and revolutionary distributed systems for multifarious purposes.One of the contemporary and out-of-the-box Blockchain-based projects, namely Hyperledger, promises to make preeminent use of this technology by promoting cross-industry collaboration in developing Blockchain-based solutions, thus, opening a new chapter in distributed computing.However, attributing to its underlying design, leveraging Hyperledger-Fabric (HF) features still lacks an analysis from the perspective of security risks and efficiency concerns pertaining to real-time distributed computing-based systems and applications.In this regard, we investigate the HF architecture, along with various research endeavours undergone by researchers in recent years to combat its security and performance-related challenges.In light of the identified limitations and bottlenecks, we present our conceptual proposal and feasible insights for improving the efficacy of HF-based systems while not compromising their security.
Tobias Adrian, Federico Grinberg, Tommaso Mancini Griffoli, Robert M. Townsend · 5 authors
Cross-border payments can be slow, expensive, and risky. They are intermediated by counterparties in different jurisdictions which rely on costly trusted relationships to offset the lack of a common settlement asset as well as common rules and governance. In this paper, we present a vision for a multilateral platform that could improve cross-border payments, as well as related foreign exchange transactions, risk sharing, and more generally, financial contracting. The approach is to leverage technological innovations for public policy objectives. A common ledger, smart contracts, and encryption offer significant gains to market efficiency, completeness, and access, as well as to transparency, transaction and compliance costs, and safety. This paper is a first step aiming to stimulate further work in this space.
In order to realize collaboration on a global scale, academic research requires often large quantities of data to be shared between geographically dispersed organizations. The requirement to protect and govern data in a network of loosely coupled, autonomous institutions is an incentive for decentralized solutions, where the participants are in full control of their data without trusting a third-party provider to store and process the data. In order to increase data availability and fault tolerance in decentralized collaborative systems, we propose a layer, which is based on replication and decentralized authority over the data. The solution consists of an idea of peer-sets, which are groups of peers implementing collective data management, a consensus protocol which synchronizes a distributed ledger between peers, and an atomic commitment protocol used to implement optional two-way references between documents. This architecture may be utilized in various decentralized collaborative data-sharing systems, such as Onedata.
In this paper, we introduce SwarMED, a decentralized yet high throughput interoperability system for big biomedical data. SwarMED uses Etehreum blockchain for trustless security and Swarm p2p storage to handle high throughput transaction of big data. In SwarMED, we developed an indexing mechanism over the immutable storage of Swarm to achieve high-throughput while sharing millions of patient records and images among multiple parties. SwarMED achieved a high throughput of 250K medical records per second over a private network constructed over LSU-HPC cluster. This high throughput is 9x more comparing to conventional way of using p2p storage in conjunction with blockchain. This high throughput enables the patients to get realtime access to his comprehensive medical history and scientists to gain real-time access to different medical data for collaborative research complying to the constraints posed by existing laws. Our system-level analysis over different design alternatives over different transfer and storage architectures shows that, p2p storage platforms automatically provide significantly better scalability over traditional HTTP with increasing number of clients. Swarm provides 2x more I/O throughput and 10x less latency than IPFS, another p2p storage system making it a better choice for decentralized big data transaction.
D. Jonathan Sebastian-Cardenas, Sri Nikhil Gupta Gourisetti, Peng Wang, Jesse Smith · 6 authors
Within the field of Transactive Energy Systems (TES), there is an active need for tools that can support and accelerate the development of these new grid solutions. Among the many tools available, blockchain stands out as a viable instrument that can help researchers develop decentralized, autonomous, and tamper-resistant grid applications. In this work, we explore the use of smart contracts (SCs), a subset of blockchain technology, and analyze their applicability to facilitating the implementation of TES solutions. In particular, we focus on presenting areas of opportunity and potential drawbacks, along with use cases that can benefit from this technology building upon previous research developed by Pacific Northwest National Laboratory and other research organizations. This work builds upon the fundamentals of TES and smart contract technology to develop a series of software templates that can be used by industry to build TES-oriented grid solutions. These templates are intended to be platform agnostic and take into consideration the unique properties of SCs and distributed ledger storage mechanisms to ensure actual code implementations remain aware of the limitations of the technology. The proposed templates have the potential to enable software architects to mix and match components to satisfy their application requirements, thereby reducing the number of resources required to implement blockchain-based solutions. These templates are divided into two main componentsâdata and behavioral models. The data models are intended to help software engineers represent the underlying grid objects along with their properties in a ledger-based storage system. The behavioral models are used to describe the processes and actions that actors within a system must perform to achieve a given outcome such as registering an asset, placing a bid, and performing bid clearances. These two components are documented in a Unified Modeling Language (UML) format and are intended for use in SC-based implementations, with special behavioral considerations to account for the asynchronous properties of the underlying ledger and the typical execution model of smart contracts. Finally, future research ideas and potential extensions to this work are discussed. In particular, known limitations and potential improvements of the developed product are identified and expected to be addressed in future revisions of the template model.
Blockchain is one of the IT industry's fastestgrowing technology niches. We chose to use blockchain technology to develop a web application for our project. We'll create a fully functional crypto-currency with full stack functionality and blockchain logic. We are proposing a new improvement in which we will not use any database server at the backend. Instead, we'll use Redis to create a publisher/subscriber network that will enable us to broadcast various messages and chain them across the network. Every node in the network will have a wallet, and they will make various transactions, which will then be added to the blockchain to block, and then broadcasted to the rest of the chain This eliminates the need for a database infrastructure to be created and maintained. We will create a mining algorithm (proof of work algorithm) for selecting blocks (collection of transactions) that will change its difficulty rate based on the computational power present in the node to node network, and for each block mined and successfully added to the chain will be rewarded with a reward in the form of our Cryptocurrency.
Liquidity is a liveness property of programs managing resources that pinpoints those programs not freezing any resource forever. We consider a simple stateful language whose resources are assets (digital currencies, non fungible tokens, etc.). Then we define a type system that tracks in a symbolic way the input-output behaviour of functions with respect to assets. These types and their composition, which define types of computations, allow us to design two algorithms for liquidity that have different precisions and costs. We also demonstrate the correctness of the algorithms.
Alessia Antelmi, Giuseppe DâAmbrosio, Andrea Petta, Luigi Serra · 5 authors
The amount of accessible computational devices over the Internet offers an enormous but latent computational power. Nonetheless, the complexity of orchestrating and managing such devices requires dedicated architectures and tools and hinders the exploitation of this vast processing capacity. Over the last years, the paradigm of (Browser-based) Volunteer Computing emerged as a unique approach to harnessing such computational capabilities, leveraging the idea of voluntarily offering resources. This article proposes VFuse, a groundbreaking architecture to exploit the Browser-based Volunteer Computing paradigm via a ready-to-access volunteer network. VFuse offers a modern multi-language programming environment for developing scientific workflows usingWebAssembly technology without requiring the user any local installation or configuration. We equipped our architecture with a secure and transparent rewarding mechanism based on blockchain technology (Ethereum) and distributed P2P file system (IPFS). Further, the use of Non-Fungible Tokens provides a unique, secure, and transparent methodology for recognizing the usersâ participation in the network.We developed a prototype of the proposed architecture and four example applications implemented with our system. All code and examples are publicly available on GitHub.
Because the existing wind turbine safety is limited by the traditional centralised management, it faces many security risks. Therefore, the future wind turbine management and control scheme is developing towards distributed security and high performance. Relying on Ethereum block technology to build smart contracts can help solve the security protection problems of network authority control and management in wind power energy systems. First, based on the analysis of wind power network security management needs, establish a mathematical model of security indicators for the control centre and subordinate nodes, respectively, when the permissions are out of control; second, based on the Ethereum smart contract release platform, according to the mathematical model of security indicators run wind power contract management (WPCM), predict the results of out-of-control simulation, and compare with the communication parameters of a typical wind farm in Northwest Europe. Studies have shown that the established wind power energy network security management plan has the characteristics of high security and good robustness, and the system processing speed is fast, which meets the offshore wind farm communication standard.
The mathematical model "Peer-to-peer distributed system for securable information storage and processing in enterprise networks" is described hereinafter. It is a versatile distributed operating system designed for the protection of distributed computing and insulation of private networks without restricting the possibilities of effective interactions, cryptographic security, protection from unauthorized access with the application of biometry and an innovative protocol of data exchange for topology control based on distributed ledger technology. The modeling was performed with the purpose of evaluation of performance of the system depending on productivity of the hardware of its nodes and the network's telecommunications equipment.
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 âdeclarationsâ 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 âalmostâ wrong, as we should try and learn from our mistakes. I may make some enemiesâor strengthen the opinion of existing onesâin the process, but then, a wise old friend, who also wrote one of the reactions once told me: âBarend, unless you made some enemies you probably lived in vain.â So I will speak my mind (âwhat's new'?). I also like to say that âEOSCâ brought me some real new friends for life!First of all, the fact that quickly after its inception FAIR became a hype termâ , 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 âAIâ, 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 âopenâ, 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: âIf data are Findable, Accessible and Interoperable it is âautomatically' Reusable.â This is of course âswearing in FAIR churchâ as the R (principles R1â3) [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: âThe Machine Knows what I meanâ. Those who feel that FAIR is too ambitious and for instance promote that âachieving F and A is enough for nowâ 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 âCommunicationâ that needed 126 iterations mentioned by Jean-Claude, which happened in the same time frame as our âHLEG-1â period, was symptomatic for a basic flaw in the discussions, which haunts us still today. Conflating the âICTâ/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 âDunning Kruger effectâ [4] pur sang: The âother side is easyâ (because I am not hindered by any knowledge about it) and is âmore or less already doneâ (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 âentirely the fault of the nerds who build things I do not understand or cannot operateâ), but also for e-infrastructure engineers who know everything about ICT and âthusâ (?) also about data (because âthat is just ones and zerosâ) 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 ârunâ. Nowadays (after many iterations) I use the diagram below (Figure 1) to explain that all three basic elements of the âInternet of FAIR Data and Servicesâ 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 âInternet of FAIR Data and Servicesâ, eventually creating an âInternet for Social Machinesâ [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 âtrivialâ or âcan be reused as isâ. 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 âpackageâ 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 âEOSC is a bigger Me syndromeâ. 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 âyet 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 âreliance on EC subsidyâ caused a dichotomy during the scoping years of EOSC between disruptive and âpreservativeâ 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 âBrussels Bubbleâ 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 âuntold storyâ here: The originally proposed title of the report was: âA Cloud on the 2020 Horizonâ. In my original foreword I explained the slightly âgloomingâ connotation of that title. When the report was finally approved, it appeared that the title had been unilaterally changed into âRealising A European Open Science Cloud [11]â. Not only did I have to hastily change my foreword (because it made no sense anymore) but also, my notorious statement that the âresultâ should neither be âEuropeanâ (only), nor Open (only) nor (only) for Science and certainly not (just) a âCloudâ was entirely ignored in changing that title. But it again emphasises the âThis is an EC thingâ context, with the associated risk for confiscation of the concept by the âusual suspectsâ 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): ânon-paper seen as the political turning point in support of EOSCâ [12], GO FAIR (Global Open FAIR) [13] was started, originally by Germany and The Netherlands and soon joined by France as a temporary âkick-startâ, 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 âGlobal Open Science Commonsâ, 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