The growing significance of structured data and the growing use of knowledge graphs across many industries will determine the direction of

Knowledge Graph Market worth $2.4 billion by 2028 - Exclusive Report by MarketsandMarkets™

The future of pharmaceutical innovation hinges on enhanced data discovery and collaboration. Through data sharing and collective effort, the pharmaceutical industry can accelerate the development of new therapies.

Finding a Collaborative, Data-Driven Future for Pharma

Eliud Polanco is the president at Fluree. He is responsible for product strategy and customer delivery operations for high-tech start-ups. Eliud previously served as the co-founder and chief executive officer of ZettaLabs, which used artificial intelligence and machine learning to prepare raw data for analytics use and recently merged with Fluree.

Eliud Polanco and Steve Hamby

[Fluree Blog] - Making Data FAIR(EST) - In our newest blog post, we explore the evolution of data management from FAIR to FAIREST. We revisit the FAIR principles - Findability, Accessibility ...

September Newsletter

"Oracle Corporation (US), IBM Corporation (US), Amazon Web Services, Inc. (US), DataStax (US), Ontotext (Bulgaria), Stardog Union (US), Hewlett Packard Enterprise (US ...

Graph Database Market Analysis And Trends By Segmentations, Top Key Players, Geographical Expansion, Future Development & Forecast -2028

CymaBay announced recently the initiation of its 52-week, placebo-controlled, randomized, phase 3 study — 'Intended to Determine the Effects of seladelpar on normalization of Alkaline phosphatase (ALP) Levels in subjects with Primary Biliary Cholangitis...

Contract Manufacturing & Logistics

Meanwhile, the firm reported increased liquidity as BTC flowed into exchanges. The new funding brings Fluree Public Benefit Corporation's total seed funding to .5 million. It also has access to .5 million in defense contracts as matching funding through ...

Personal Financial Management Uc Berkeley

Fluree develops secure database management platforms in Web3. Together, the two organizations hope to alleviate problems within the pharmaceutical industry. Fluree and Vitality TechNet believe ...

Vitality TechNet partners with North Carolina firm on pharmaceutical regulatory information management

Fluree, which develops secure database management platforms in Web3, has partnered with Orlando’s Vitality TechNet to build a semantic data infrastructure for pharmaceutical organizations ...

Fluree partners with Orlando firm on pharmaceutical regulatory information management

A kidney disease drug with a ‘durable and clinically meaningful impact on kidney function’ has been granted priority review by the US Food and Drug Administration (FDA). Calliditas Therapeutics made the announcement on Friday (August 18) that the FDA ...

FDA grants priority review for full approval of Calliditas' Tarpeyo to slow kidney decline

Fluree

fluree

It’s a rainy Sunday afternoon, and my friend, Alice, and I are playing “Where’s Waldo.”* This page is a particularly challenging one, and we’ve been looking for nearly twenty minutes.  I’m about ready to give up, when- finally- I spot Waldo, and I yell out, “I got him!” Note from the author: I am a lead software engineer at Fluree .This blog post  created by Lillian Podl og was originally posted on the Fluree blog here . Technologies used include Fluree , Iden3’s Circom and Iden3's SnarkJS . Follow along with this tutorial here: . fluree/legal-fishing “Oh really? Prove it then,” Alice says, hand on her hip. I raise my finger, and I’m about to point to Waldo’s location, but she stops me, exclaiming, “Wait, wait, wait! Wait just one second! I’ve put so much work into finding Waldo, and I don’t want you to ruin it for me.” “Hmm…” I say. “If only there was a way for me to prove to you that I know where Waldo is without revealing his location.” “Here, I have an idea,” Alice says. “I’ll make a photocopy of this page in the book, and you can cut Waldo out of the photocopy and show him to me. That way, I know for sure that you know where Waldo is, AND I still won’t know where he is.” As you might have guessed by the title of this blog, the scenario I’ve described is a classic example of a real-life zero knowledge proof. In this story (which **definitely** happened in real life), There are many types and potential applications of zero-knowledge proofs, including nuclear disarmament (yes, really) and verified anonymous voting. In this example project, I’ve focused on how using Fluree in conjunction with zero-knowledge proofs can begin to tackle the challenge of traceable fishing. Before we begin, I need to make the disclaimer that I am, by no means, an expert in zero-knowledge proofs. I welcome and encourage comments, suggestions, corrections, criticisms, and more in the comments. This project is an exploration of the possibility of using zero-knowledge proofs with . I am proving that I possess a piece of information (Waldo’s location), while at the same time not revealing that information. Fluree With relying on fish as their main source of protein, oceans are a critical food source. Given the importance of marine life to human nourishment, efforts have been made to regulate fishing locations, methods, and quantity. These regulation attempts are sometimes at odds with the desires of fishers who, among other concerns, are not too keen to reveal their fishing locations. This is where zero-knowledge proofs can come in.  Zero-knowledge proofs can allow a fisher to prove that they are, for example, fishing within an allowed area, without exposing the exact location. To follow along with this example, you can download the repository. If video is more your speed, you can also check out this project’s accompanying video above or on youtube. three billion people fluree/legal-fishing Iden3’s Circom and SnarkJS In this project, I use two Javascript libraries, both published by Iden3, to handle my zero-knowledge proofs. I use to write and compile an arithmetic circuit (more on this in a second). I then use this circuit in conjunction with the library to implement a zero-knowledge proof. (For those who are interested, the specific type of zero-knowledge proof we use here is called a zkSNARK, or zero-knowledge succinct non-interactive argument of knowledge, using the 8points protocol). The intuition behind this type of zero-knowledge proof is not as simple as the “Where’s Waldo” example, but it operates in a similar way. We first build a very specific type of electrical circuit that is only satisfied by inputs that match certain restrictions. circom snarkjs Using circom, we’ll create a representation of a circuit, but let’s imagine for a second that it’s a real-world circuit. You and I sit down, and we build an electrical circuit with 5 switches on one side. The circuit has a light bulb that will always light up if exactly 3 of the switches are on- it doesn’t matter which three. I leave the room, and you flip any three of the switches that you want. You then cover up the switches with a cardboard box so that no one can see them. I walk into the room, see the light bulb is shining, and I know that the circuit is complete. I know that your input (which switches you turned on) fit our criteria (exactly 3 switches turned on), but I won’t know exactly what your input was. This type of zero-knowledge proof is analogous to what we are mathematically accomplishing using circom and snarkjs. We won’t delve into the math here, but hopefully this has given you some intuition. InRange.circom The specific type of circuit we are creating is an arithmetic circuit, which is a circuit that can perform some arithmetic operations. If you are following along with the GitHub repository, the circuit is` `. src/circuits/InRange.circom Our circuit will take two public inputs: – an array of two numbers representing the min and max latitudes of the legal fishing range (must be positive numbers). latitudeRange – an array of two numbers representing the min and max longitudes of the legal fishing range (must be positive numbers). longitudeRange These two inputs will be visible to the public. This circuit will also take a private input: – an array of two numbers within the legal range. fishingLocation The circuit will output a 0 (if the circuit is not satisfied) or a 1 (if it is). To compile the circuit, you’ll need to have circom installed: npm install -g circom Then you’ll need compile the circuit: circom InRange.circom -o InRange.json This will take InRange.circom as an input an output InRange.json in the same directory. Setup Now, we need to setup the circuit. In order to do this, we’ll need to have snarkjs installed. npm install -g snarkjs And then we can issue: snarkjs setup -c InRange.json This will create two files, and . As the names suggest, the proving key is the key you’ll need to prove that your input (your location) is valid. The verification key is the key you’ll need to verify anyone else’s proofs. When we set up our Fluree ledger, we’ll be putting both the proving and verification key (as well as the circuit) on the ledger. proving_key.json verification_key.json Note – This type of zero-knowledge proof requires a trusted setup. The process of generating these keys will also create some toxic data that must be deleted. Participants need to trust that the toxic data was deleted. It is important to note that this toxic data would allow an untrustworthy participant to create a fake proof using inputs that don’t match the constraints. The toxic data would NOT allow a user to discover someone else’s secret location. But this toxic data is only created once, and there are methods to minimize the risk. For example, a multi-party trusted setup creates a situation where a number of participants come together to generate the proving and verification keys, and each of them possess a piece of toxic data. In a setup like this, the only way to create a fake proof would be if every single party was untrustworthy, and they all kept their toxic data and then colluded by bringing their toxic data together (hopefully an unlikely occurrence!). Calculating a Witness Before we can create a proof, we need to calculate all the signals in the circuit (including all the intermediate inputs) that match the circuit’s constraints. In order to do this, we’ll need to create an input.json, which has all of our inputs (including the private inputs). Neither the inputs.json, nor the witness.json files will be shared with anyone, but we do need to calculate them first. Our input file needs to be a map, where the keys are the names of all of the circuit’s inputs, and the values are our specific inputs. For example: { : [ , ], : [ , ], : [ , ]
} "latitudeRange" 20 21 "longitudeRange" 176 190 "fishingLocation" 20 180 We can then calculate the witness, which will generate the witness.json file. snarkjs calculatewitness -c InRange.json Create the Proof Now, we have all of the pieces to create the proof: snarkjs proof This command uses the proving key and the signals in witness.json to generate a proof.json (the actual proof) and public.json, which is a subset of your witness.json containing only your public inputs and the outputs. Verify the Proof You can now give any other party your verification_key.json, proof.json, and public.json, and they can verify that you put in an input that matched the constraints (a location within the legal range). Connecting this with Fluree In the repo, we not only have an example circuit with example keys and inputs, but we also have a small demo React app that makes it easy to connect this zero-knowledge proof to a Fluree instance. To get this running, you’ll need to: fluree/legal-fishing Download a fresh instance of Fluree. I used version . 0.11.5 Run Fluree (`./fluree_start.sh`). Fluree needs to be running on port 8080. This is the default port, so if you didn’t change any of the settings for version 0.11.5, everything will be all set for you. Create a database called `legal/fishing`. Issue a transaction to create the schema. You can find this transaction in ` `. seed/schema.json Issue a transaction to upload the circuit, verification key, and proving key to Fluree. You can generate and upload your own, or you can use the example in ` `. If uploading your own, be very careful to copy the keys and circuits exactly, otherwise the proof and verification won’t work. seed/seed/json Now, you can run `npm install` and `npm start` to start up the light-weight React app, which integrates Fluree with the zero-knowledge proofs. You can use the app to generate a proof and submit the proof and public signals to the Fluree ledger. You can also click on the Verify Proofs pages to see all the proofs that have been submitted to this ledger. You can click on “Verify Proof” to verify any given proof. Note that verifying a proof takes a little while, so expect to wait 10 – 20 seconds before a green “Verified!” alert comes up. For a full tour of the application, as well as a visual walk-through of getting the circuit and app setup, check out this project’s accompanying . video This zero-knowledge proof project allows you to create zero-knowledge proofs asserting that a given fishing location is within a legal range. By uploading the circuit, proving key, and verification key to Fluree, all the members of a network can see the keys and ensure the keys haven’t been changed or tampered with over time. By uploading the proofs to Fluree, we ensure there is a record of who submitted every proof, when they submitted, and whether and how they changed that proof. In addition, because the verification key is also on the ledger, any participant can independently verify any and every proof as many times as they want. Additional Considerations This small project is only a tiny part of the puzzle needed to ensure seafood traceability. For starters, this example only deals with a single rectangular-shaped area. A real-life project would, of course, be much more complicated than this. In the case of zero-knowledge proofs, verifying and creating proofs can be time-intensive, so implementing a real-world project would require careful consideration of timing. There are zero-knowledge proofs that specifically are optimized for range-proofs, which might be a better fit for this example. This could be an area of future exploration for us. Additionally, even if the proof itself took the full scope of real-world restrictions into account, a fisher’s location at the time of catch would have to be reported by a source that is reliable. For example, we might want a piece of hardware that is sufficiently tamper-proof reporting a fisher’s location, rather than, say, the fisher’s word. We would also need a reliable way to correlate a GPS location to a particular catch. For hardware, considerations of cost, hassle to the fishers, and tamper-proofness would all have to be weighed. A final area to consider is public knowledge and trust of zero-knowledge proofs. Even if mathematically, we can show that a zero-knowledge proof does not reveal a fisher’s location, the fisher would have to trust the organization implementing this system. The fisher would first have to trust that their location is not hidden somewhere in the proof they are uploading to the database. The proof is a large, JSON object that could conceivably hide information. The fisher would also have to trust that the hardware they are using to report their location is not sending it out through some backdoor. These are assuredly not insurmountable concerns, but they should be considered as food-for-thought. Research, implementation, and public understanding of zero-knowledge proofs have really grown in the past few years due to projects like , so this is definitely an area to look out for! Thanks everyone for reading, and I’m interested in any and all feedback. If this piqued your interest, you might be interested in checking out other projects that tackle the challenge of , as well as this curated . You can also get started with Fluree , and make sure to check out our as well! ZCash proof of location list of zero-knowledge proof content here documentation * For those unfamiliar with the “Where’s Waldo” books (or “Where’s Wally” outside of North America), Waldo is a cartoon man in a red-and-white striped shirt. “Where’s Waldo” books have page after page of hectic scenes, filled with people and colors. The object of the game is to try and spot Waldo.

Using Zero-Knowledge Proofs to Prove Legal Fishing Ranges with Fluree [A Step by Step Guide]

This article highlights a fellow North Carolina-based technology startup – One Donation – and its mission to bring trusted and agile digital philanthropy to HR. Giving, made easy One Donation’s cloud-based charitable giving platform allows employees to find and donate to their favorite charities directly through payroll deduction. One Donation is a win-win: it provides employees with autonomy over which institutions receive their philanthropy with a choice of over 1.8 Million charities and HR with a platform that seamlessly integrates directly into existing payroll systems. Because all charitable donations through One Donation can be connected with an employer’s payroll provider, charitable giving is as easy as making a 401(k) contribution or healthcare deduction. Disrupting the Industry with Disruptive Technology The One Donation team needed to select a reliable technology stack that could scale to enterprise demand, interoperate with established players in the existing HR technology stack, and instill digital trust for its prospective users. For those reasons, One Donation built its software on Fluree’s technology. Let’s explore some of the key enabling features Fluree provides to give One Donation a competitive edge: Secure and Verifiable Donations Donors want to ensure that their contribution is reaching the desired destination. Simply by choosing Fluree, One Donation can provide its users with a verifiable audit trail of every donation executed on its platform. How? Fluree integrates digital trust into data using a cryptographically secured immutable ledger. Using blockchain technology, every Fluree transaction is signed at the source and cryptographically tied to previous transactions. This approach allows One Donation to verifiably prove the time, source, and history for each and every datum in the system. That’s automated trust, out of the box. Learn more about Fluree’s distributed ledger technology . here Data Agility Fluree is built on standards with an emphasis on enabling data agility. For example, One Donation uses Fluree’s GraphQL interface to expose all kinds of data to various consumers without having to build and manage multiple APIs for each client instance. This results in faster time-to-value: Rather than having donations go out quarterly or every six months, Fluree allows us to shorten that time to weeks at most. The ability to provide instant, agile transactions is a game-changer for workers, employers, and the charities they support.” -Ross Treakle, co-founder One Donation “ Learn more about Fluree’s GraphQL interface . here Enterprise Scale Organizations – big or small – building with Fluree can rest assured that we will scale right alongside them. One Donation uses Fluree’s to manage their client instances in a multi-tenancy environment. This simplicity results in lower costs for One Donation’s client base and fewer cloud dependencies for One Donation’s infrastructure management team — all without sacrificing performance. scalable and cloud-agnostic infrastructure Learn more about Fluree’s cloud-scale capabilities: Conclusion One Donation is looking to change the world – one donation at a time. Using Fluree’s Open Source technology, the One Donation team has built a product that emphasizes trust & transparency for consumers as well as integration-readiness and scale for businesses. Check them out: or on and . http://www.onedonation.org Linkedin Twitter

One Donation Brings Digital Trust to Charitable Giving￼

APIs are quickly becoming the front door to modern enterprises. But the API paradigm also comes with various hidden costs around development, management, governance, and security. A new data-centric security paradigm might be able to leapfrog many of these hidden costs. A side benefit is that this could open new opportunities for data agility while providing a tighter security perimeter in the process. Digital natives like Facebook, Google, Uber, and Airbnb have demonstrated the value of bringing agility to their data assets. They have grown to prominence on the back of APIs that allow their internal teams and customers to monetize their core data assets in new ways. But smaller companies do not have the same resources. They may benefit from finding ways to protect more data directly, rather than the APIs that sit in front of it. The Rising Costs of APIs The rise of APIs as the digital front door has led to new maintenance and data management costs and challenges. Various sources estimate organizations spend an average of $10,000 to $20,000 per API to develop, and about half that to maintain every year. The travesty of the API is that it also imposes this same cost on each customer, which can also slow adoption and the ability to innovate on top of your API. Traditional APIs are optimal for situations when there is one producer of data and one app consuming data. But things get trickier when there are many publishers and consumers of data. Today, data is secured using custom code which is built into the app server. But this model breaks down when there are many who can write and read the data.  In a many-to-many world, developers have to be concerned about ensuring the appropriate read and write rules are built into every application and that those apps are interoperable as updates are made and new apps are added. This can add up from a cost, time, and resource bandwidth perspective as enterprises develop multiple APIs to provide different kinds of services or to allow applications to connect in new ways. The number of APIs is growing dramatically as more enterprises move to microservice architectures that break applications into smaller components. Developers also must invest time and effort in organizing the data in the appropriate way for their given use case. This can lead to new kinds of data silos as developers find different ways to organize the data to solve a given task. Each of these silos creates another attack vector. Security and Governance Challenges of APIs Today security is implemented using APIs to provide permissioned data access. Developers must code the APIs to modify database queries to obey security rules. Today this is typically written in JavaScript or Java by a developer rather than a security expert. As a result, data governance responsibility is pushed to the API layer, meaning that the enterprise ends up imposing responsibility far beyond application management to the API developers. As new data governance regulations come into effect enterprises are going to need to double down on ensuring appropriate privacy safeguard for the data underpinning their apps. This can get messy if developers try to do this at the application or API layer since the data can exist across all sorts of systems and servers. A data-centric approach for traditional companies to be competitive in the new digital economy, data will have to become one of their more important assets. It’s hard to be nimble when the data is organized separately in various systems. If you have hundreds of app developers each setting up the data structure for their app separately, the data becomes harder to manage. The app developers each must think about what data to use, how to store it, and how to process it. This ends up creating all sorts for different silos. A much better practice is to set up guardrails across the organization for data access that can be enforced programmatically. This can allow developers to focus on what they are good at around coding logic, while leaving security and privacy decisions to the appropriate specialists. This can also help automate compliance with new privacy regulations like GDPR across development teams. Once the data is directly protected, it becomes practical to allow developers to retrieve the appropriate data using SQL statements to describe what data they want and the appropriate structure for their needs. This approach can also consolidate data silos and as a result reduce the number of potential attack vectors. Let the Data Defend Itself Another benefit of a data-centric approach to security is that teams can start to think about how to create rules that allow the data to defend itself. In the application development world, expressing infrastructure as code allows application teams to programmatically spin up and configure the infrastructure consistently. Similarly, figuring out how to express data governance rules as data coded into the database will allow teams to bring the same rigor to managing, governing, and securing data at the level of cells, tables, and rows consistently and automatically. For example, in a privacy-sensitive app, a data privacy officer could configure a rule to allow most users to see the last four digits of a social security number, but not the rest of it. This makes it possible to configure the data privacy preferences of a company’s customers in a way that is stored right inside the data. There could be generic rules that apply to everyone that has access to their healthcare data if they are connected to the persons as a provider or employer for them. And these rules could be managed in such a way that only the subject can make or amend these rules. While the data might exist openly, this gives the data subject precise control over who can see and access the data about them. Bringing Security Right to the Data The Internet security world has been migrating to a new paradigm for protecting enterprise applications and data at a regular cadence. In the 1980s organizations first started implementing packet filter firewalls at the boundaries of networks. These later morphed into application firewalls that prevented attacks on application logic, and then web application firewalls that focused on some of the specific vulnerabilities in the way web applications ran and the way they accessed legacy databases. More recently organizations have been replacing web applications with APIs as the front door to the enterprise. This has allowed teams to write an API once, which can be reused across applications running on mobile devices, browsers, or other servers. This shift has been followed by a massive move in the way hackers seek to attack the enterprise. Until recently, enterprises only had to ensure they were protected against the OWASP Web Application Security Top 10 Vulnerabilities like cross-site scripting and SQL injection. The group has now added a list of top 10 API vulnerabilities to contend with as well.  A recent survey found that 75% of all credential abuse attacks on financial institutions now target APIs directly. Perhaps it’s time for the industry to adopt a paradigm around tightening the security perimeter even further to protect data directly rather than out at the level of APIs used to access it. This could also centralize the rules for allowing appropriate access. Centralized governance, compliance and security teams could set up comprehensive rules for protecting the data in one place, which could automatically be observed across all the applications accessing it. A data-centric approach to security makes data governance more automated and scalable, which, in turn, allows organizations to open data sets more freely to consumers of that data. By ensuring data security at the data layer, enterprises can be more liberal with data sharing since the security rules will be automatically executed regardless of whether the data is at rest or in motion. This encourages quicker data decisions and data-driven innovation while mitigating security and compliance risk. This article is by Brian Platz, Fluree Co-CEO & Co-Founder About Brian Platz Brian is the Co-CEO and Co-Chairman of Fluree, PBC, an open-source platform for data ecosystems. Fluree is an immutable, temporal, ledger-backed semantic graph database that has a cloud-native architecture. Prior to starting Fluree, Brian co-founded SilkRoad technology which grew to over 2,000 customers and 500 employees in 12 global offices. Brian serves on the board of directors for Fuel 50, one of the highest growth HR technology startups. He is also the co-founder of A List Apart, a web publication, 22 book series, and global conference for the web development community to expand their knowledge.

Save API Costs With Data-Centric Security 

Online security has become something of an oxymoron. Even the most futuristic advances in AI and edge computing can't protect data all the time. Data simply travels too far and wide for any single tool to keep pace. The solution involves changing the data packet itself. A new batch of cryptographic tools are rising to encrypt data in a hard shell wherever it travels. Verifiable credentials, decentralized identifiers (DIDs), and blockchain all use cryptography to prevent the manipulation of data. On the surface, these methods seem interchangeable; each is a single source of truth that verifies the authenticity of data. Each uses cryptography to secure data. Knowing when to use each type of technology, and how they work together, will prepare organizations not only to better secure their data but for the Web3 future of the entire internet. Verifiable Credentials at Risk The found that 86% of breaches were financially motivated. 58% of this year's compromised personal data was "nearly twice the percentage in last year's data", according to the report. Verizon Data Breach Investigations Report 2020 Bank statements, W-2s, house titles, electronic healthcare records, and social security statements are just a few examples of data available for the taking. Such documents are known as verifiable credentials. They are issued by a central authority and tied to critical personal assets such as citizenship, financial status, driving ability, and health. As such, they hold enough value that their authenticity needs to be confirmed. When verifiable credentials are placed online, they become vulnerable to theft. Everywhere the data travels -- a bank's server, lender, employer, transcript office, DMV, etc. -- becomes fair game for opportunists. Even if everyone on the internet had an encrypted file server, login credentials could still be made available by plugins or security holes in web applications. Seen in this light, online security appears broken. I prefer to call it "in transition". The problem isn't sub-par encryption. The problem is changing the way that credentials travel online. The means transforming the credential itself into an indecipherable shell, accessible only by someone who obtains, upon request, the right key. How Verifiable Credentials Interact with DIDs A paper verifiable credential might use holograms, signatures, and bar codes to prove authenticity. The online version of a verifiable credential is a machine-readable, provable, inalterable data packet. The data itself, which can be anything from a supply-chain history to your driver's license, is represented in the form of a JSON "payload". A person, for example the supervisor of a supply-chain assembly line or the DMV, signs the payload in the form of a cryptographic signature (basically a data fingerprint). The payload thus pairs with an accountable human or organization, proving credibility. The hash provided by the accountable human or organization is the DID that accompanies the payload. Together, the DID and the verifiable credential appear garbled online, readable only by designated keys (mathematical proofs that match the DID to its point of origin). Whoever receives the key to the DID , proving both the signature of the issuer and the integrity of the credential. For example: Yes, this part really was manufactured in the right assembly line in Hanoi. Yes, the North Carolina DMV really did issue this person their driver's license. checks for validation This is a massive improvement over the unprotected data that currently sits in millions of databases, ripe for theft. The current system of verification involves teams of people validating credentials through efforts such as background checks, reference phone calls, database queries and so on. DIDs are truly decentralized. You can register an identity from anywhere, storing it on a file system, AWS, in a web browser, thumb drive, phone app, or the blockchain. Verification becomes purely a matter of machine-to-machine communication. Thousands of JavaScript libraries enable users to code DID cryptography. Developers can write JSON apps in less than an hour that allow users to fill out form fields and create a verifiable credential, which in turn can be embedded in just about anything. Simply put, it enables us to use cryptography and public keys to prove things that would otherwise require human time and effort. You'd be able to prove your income and driver's license to a mortgage company simply by giving them permission to access a DID. Instead of looking at LinkedIn and calling references and conducting background checks, employers could, with an applicant's permission, verify the information to be true online by way of a DID. Machine-readable transcripts, in the form of DIDs, would enable students to transfer course credit seamlessly between institutions, without the need for spreadsheets, emails or people looking up records. When Blockchain Makes Sense DIDs are a promising technology and a natural next step for security on the internet. They are easily created and disseminated and they function well by themselves. Individual users have almost no reason to put a DID on a blockchain. Worst yet, organizations have cited trouble implementing blockchain; it has been called a solution without a problem. Why bring up blockchain at all in relation to DIDs? Like the DID, blockchain bypasses the need for a central authority to issue and enforce online rules. Trust is built into the workflow. In fact, the similarities between DIDs and blockchain are exactly what makes them compatible on an organizational level. A single person with DIDs for their driver's license, credit report, and social security number has no need for a blockchain. Many organizations can comfortably use DIDs without reaching for a blockchain. For large and/or complex organizations, however, blockchain is a superior option. Let's say you're operating a regional e-moped rental company. The e-mopeds are available in cities and require a valid driver's license. A user can apply a DID to easily unlock and re-dock a moped. No need for blockchain in sight. Now let's say your e-moped company grows. You decide to manufacture the mopeds yourself. Your company goes international, and laws in some countries require insurance. Suddenly you have a much more complex, integrated organization. How do you know that counterfeit parts aren't sneaking their way into the production line? How can you automatically verify the different licensure and insurance requirements in each country? How do you know if the mopeds in each country were serviced and repaired according to that country's regulations? Forcing every country's credentials into a single, global database is one answer. In practice, such a database is unlikely to succeed. The IT governance and data management requirements would be monstrous. There would have to be a hierarchy of centralized authority figures to manage each region's data, and ongoing coordination with regards to best practices and data security. At best, you'd have a messy situation. Blockchain cryptographically connects data records and distributes them to people within the blockchain organization. On a blockchain, records are always there. Anyone within the organization can access them. There is relative assurance that records haven't been tampered with. To go back to our example, every time a moped is manufactured, every purveyor of materials and each assembly line would issue a verifiable credential that is stored on a blockchain. By the time the completed moped arrives at its destination, it has its own immutable record of manufacture on a blockchain, which can be revisited, assessed, and analyzed at any time. Officials from customs agencies to cities can know where each moped was and when. Your company is assured of where each piece comes from. Service records, insurance records, license records and so on can be tracked in a similar fashion, ensuring easier oversight of data, and automating data management and security. Preparing for the Web3 Future Basically, blockchain is a log file with cryptography and business rules. It stops the manipulation of data. Just as the very first motorized cars didn't have seatbelts, doors, or windshields, the early internet lacked fundamental protections. In 20 years, we will likely be looking back on today as a time of primitive safety measures. Verifiable credentials, DIDs, and blockchain are evidence of what's to come: Web3, a more secure, widespread, machine-to-machine internet. They enable all online users to maintain trust by creating a single source of truth. And if 2020 has shown us anything, the notion of a single source of truth is, in fact, priceless. Brian is the Co-CEO and Co-Chairman of Fluree, PBC, an open-source platform for data ecosystems. Fluree is an immutable, temporal, ledger-backed semantic graph database that has a cloud-native architecture. Prior to starting Fluree, Brian co-founded SilkRoad technology which grew to over 2,000 customers and 500 employees in 12 global offices. Brian serves on the board of directors for Fuel 50, one of the highest growth HR technology startups. He is also the co-founder of A List Apart, a web publication, 22 book series, and global conference for the web development community to expand their knowledge. About Brian Platz

How Verifiable Creds, Decentralized Identifiers and Blockchain Work Together for a Safer Internet

Episode 26 of the : An interview with , Co-CEO of . Hacker Noon Podcast Brian Platz Fluree Today’s show would not be possible without Digital Ocean . Listen to the interview on , or , or watch on . iTunes Google Podcast YouTube In this episode and discuss database blockchain technology and the variety of approaches to building decentralized applications. Trent Lapinski Brian Platz “I think a lot starts changing when you can actually trust the data.” “With Fluree, you can actually grab the exact version of the database that was being used for that integration at exactly 12:01 AM and 0.23 milliseconds, and you can actually see and know what was in there, figure out what broke, and fix it.” — Brian Platz _In this episode Trent Lapinski and Brian Platz discuss database blockchain technology and the variety of approaches to…_www.podbean.com The Industry Interoperability of Fluree with Brian Platz P.S. If you dig the new Hacker Noon Podcast , consider giving us a 5 star review on iTunes. Today’s show would not be possible without Digital Ocean . Learn more at do.co/hackernoon . Also check out , and . February top stories the latest stories today’s homepage

The Industry Interoperability of Fluree with Brian Platz

Let's learn about via these 59 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Zero Knowledge Proofs /Learn Repo 1. Layer 2 Rollups Projects in 2021: A Comparison Ethereum layer 2 is a collection of solutions that are specifically designed to scale applications by handling transactions off the Ethereum Mainnet, Layer 1. 2. KZG10, IPA, FRI, and DARKS: Analysis Of Polynomial Commitment Schemes Among all popular polynomial commitment schemes, KZG is the best scheme in terms of succinctness but triggers security concerns. 3. Understanding the Zero-Knowledge Proof Method One of the biggest advantages of blockchain technology is the degree of information transparency it offers. 4. zKPs OR Zero-Knowledge Proofs: The Tiny Privacy Algorithm Behind Super Lightweight Blockchains Distributed public networks face a trilemma: digital transactions must provide privacy while meeting compliance requirements in a trustless environment. 5. Zero-Knowledge Proof Algorithm, PLONK—Protocol: Sin7Y Tech Review (17) In this report, Sin7Y will analyze the details of the PLONK protocol and elaborate on how the constraint relationship of the gate is valid. 6. Zero-Knowledge Proof Algorithm: ZK-Stark-FRI Protocol We reach the conclusion of the series “Understanding the value of a zero-knowledge proof algorithm - Zk-stark". 7. Lowering the Barrier of Entry to Zero Knowledge Proofs Next Generation Semiconductors: Designing accelerators for advanced cryptography 8. AppliedZKP zkEVM Circuit Code: A Guide This text aims to provide an easy guide to the basic framework and logic of the AppliedZKP zkEVM code base. 9. How to Create an Anonymous Voting System on the Blockchain Using Zero-Knowledge Proofs How to create an anonymous voting system on the blockchain using zero-knowledge proofs 10. True Privacy is When Users Decide Who Sees and Uses Their Data: Unhased #24 Unhashed is a QnA series where I speak with top execs of new and established blockchain projects to unravel the mystery of blockchain & crypto. 11. The Leo Programming Language Will Make Waves in Web3 Aleo is building a brand new programming language, Leo, which is used to build private web3 applications. 12. The Magic of Zero-Knowledge Proofs through the Source Code of Tornado Cash Understanding Zero-Knowledge Proofs through the source code of Tornado Cash 13. Why SNARKs Are the Technology of the Coming Decade Welcome to the SNARK Age, a pop-up newsletter exploring and celebrating a technology that we believe will have fundamental and deterministic impacts on privacy, computing, cryptography, and money in the years to come. We’ll be sharing (mostly) bite-sized issues highlighting the key events, milestones and people in the space. 14. JavaScript tutorial for Zero-Knowledge Proofs Using SnarkJS and Circom In this article, I will show you how you can use zk-SNARK in your JavaScript project by using circom and snarkjs. 15. "Defi & Traditional Finance Aren't Much Different, But Defi Requires Lesser Trust" - Alex Lee This interview discusses zero-knowledge proof and the use of ZKs for establishing trust in a blockchain system. 16. TinyRAM Review: Architecture, Design, and Assembly Instructions TinyRAM can be used to perform non-deterministic computations easily and plays an important role in zero-knowledge-proof systems. 17. Zero-Knowledge Proofs: The Simplest Explanation on the Internet history, concepts, principles, technical implementation, and development status of zero-knowledge proofs in the simplest language ever 18. Understanding Zero-Knowledge Proofs: Privacy is Freedom The metaverse will likely be a disaster for user privacy unless that is solved unless that privacy is solved. 19. How we can Better Understand PLONK Permutations over Lagrange-bases for Oecumenical Noninteractive arguments of Knowledge, or PLONKS are a new general-purpose zer-knowledge proof scheme. 20. A Refresher on Zero Knowledge Proof Systems and A New Contender Before we give our hero the undivided attention it deserves, let us try and explain zero-knowledge proof in one sentence. Zero-knowledge proofs allow you to prove that you know a ‘secret’, without actually telling and revealing the secret to the other. 21. How Are zk-SNARKs Possible? Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs. 22. How Private Are Your Blockchain Transactions? Multiple projects have been working on various blockchain scaling solutions, such as Sharding and Plasma offer greater scalability and Privacy. 23. Using Cloud-ZK for Developing ZKP Acceleration in the Cloud Cloud-ZK: A Toolkit for developing ZKP acceleration in the cloud 24. An Intro to Zero-Knowledge Proofs (ZKP) and Identity Learn about Zero Knowledge claims and how they can help in securing your Identity. 25. ZKPs or Zero Knowledge Proofs Are Evolving Blockchains [Explained in non-technical terms] ZKP can be used for much more than just privacy. ZKPs are so versatile that it may redefine how blockchains work. 26. Fflonk - A New Plonk Protocol: Sin7Y Tech Review (13) Through careful research, we found that a simple transformation can improve the performance of Verify significantly. 27. Elusiv Raises $3.5 million in Seed Funding Round Co-led by LongHash Ventures to Build Web3 Privacy Elusiv, a privacy protocol that is Zero-Knowledge based and compliant, has raised $3.5 million in a seed investment round 28. Is Data Monetization Dead? The advent of cryptocurrency and web3 has led to investigations and experiments into what ways could a total decentralized digital society manifest. 29. Understanding the Sinsemilla Hash Function in OlaVM Read on to know the Security Properties of a Cryptographic Hash Function, Random Oracle, and the Sinsemilla Hash Function. 30. On Zero-Knowledge Proofs And Why They Matter There is a lot of enthusiasm for the application of zero-knowledge proof systems, at Dusk Network we’ve developed the open-source PLONK zero-knowledge proof system. It can be used for many things, and what better way to demonstrate its potential with an example! 31. 🟧 un.Block #39: Design of Cross-chain Bridges; Let's Go Snail Trail! In the last year, cross-chain bridges have been one of the hottest theses. 32. zk-SNARK Concepts Explained In Different Levels of Complexity I’ve decided to write an ELI15 for zk-SNARK jargon since I’ve yet to come across something similar during my studies. 33. Zerocoin Flaws, Private Atomic Swap Adoption, and UX [An Analysis] We started as a PoW coin however soon realised for the sake of security (namely preventing 51% attacks and ASIC miners), we'd be better suited to having a Proof-of-Stake consensus mechanism. So we moved over from mining to staking without a hitch and took advantage of this new setup by developing our own 'Leased Proof-of-Stake' mechanism, which allows users to stake their coins via a service provider who take a small percentage from each staking reward for running the service. 34. How to Design the ZKVM Circuit We will not perform the field division operation at the circuit level, instead, we will make it by verifying the following logical relationship. 35. The Power of Zero-Knowledge Proofs - Exploring the New ConsenSys zkEVM See how ConsenSys zk-rollups are evolving at a rapid pace and leading the way in helping Ethereum to scale to new levels. 36. Zero-Knowledge Proof Algorithm, PLONK —Circuit: Sin7Y Tech Review (16) We recently investigated the Zero-Knowledge proof algorithm-PLONK. Read on to know our learning experience. 37. Using Zero-Knowledge Proofs to Prove Legal Fishing Ranges with Fluree [A Step by Step Guide] It’s a rainy Sunday afternoon, and my friend, Alice, and I are playing “Where’s Waldo.”* This page is a particularly challenging one, and we’ve been looking for nearly twenty minutes.  I’m about ready to give up, when- finally- I spot Waldo, and I yell out, “I got him!” 38. Zero-Knowledge Proofs: An Intersection of Data Verification and Privacy Dive into the world of zero-knowledge proofs & learn about the challenges and opportunities that will arise by combining them with oracles. 39. How to Use Zero Knowledge Dapp Boilerplate Learn how to build zero knowledge dapps, using zero knowledge proofs boilerplate. Build age verification dapp using zero knowledge proofs. 40. ZoKrates - zkSNARKs On Ethereum (made easy) ZkSNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) or sometimes called "black magic" by some developers are generally considered hard to get into. 41. In Search For Future Crypto Trends Future trends in crypto might revolve around metaverse and NFT, Zero Knowledge proofs, evolution of DeFi, growth of Social Identity importance, and Multi-Chain. 42. What is Zero-Knowledge Proof ? Let’s explain exactly what that term means in one sentence: 43. ZK-Rollups are the Most Promising Way for the Blockchain Industry to Scale Smart Contracts Jagdeep Sidhu is the lead core developer of Syscoin and CTO of the publicly-traded company, Blockchain Foundry Inc who talks with us on ZK Roll ups. 44. How I Built an Anonymous Voting System on the Ethereum Blockchain Using Zero-Knowledge Proof How I built an anonymous voting system on the Ethereum blockchain using zero-knowledge proof 45. Enforcing Scalability and Data Integrity on Blockchain with Zero-Knowledge Proof Layer 2 and sidechain protocols have deployed the use of zero-knowledge proof to perform batch transfer processing rolled into a single off-chain transaction. 46. Why You Need To Add A Dash of Zero-Knowledge Proof to Your Projects Advanced technologies such as zero-knowledge proof systems require extensive knowledge from developers, making it difficult for businesses to adopt. Without a deep understanding of the underlying cryptographic logic, it is quite frankly impossible to implement correctly. 47. Trade it Like it is HOT: A Review of Popular ZK Projects and the Zero-Knowledge Proof Technology Privacy has always been regarded as one of the most valuable features in the cryptocurrency community. 48. ZK Rollup: The Most Preferred Ethereum Layer 2 Scaling Solution In this article, I explained the Ethereum zkrollup for beginners.and I started with discussing rollup before zkrollup and Optimistic rollup. 49. "Privacy and Zero-Knowledge Proof Are Going To Be Critical for A Free Society" - Kieran Mesquita This article talks about zero-knowledge proof and how zero-knowledge proofs work establishing trust with technology. 50. HashKey Capital's Deng Chao Talks About Market Developments and the Future of Web3 in 2023 Deng Chao, a representative of HashKey Group, a blockchain-focused investment firm, discusses the market developments in the web3 space in 2022. 51. Building an AI On-Chain Modulus Labs is a Web3 project that aims to bring AI capabilities to the blockchain in a decentralized manner, enabling creators to own and control their models 52. Exploring Popular zkEVM Solutions:  AppliedZKP, Matter Labs, Hermez, and Sin7Y zkEVM is said to be the crown jewel of Ethereum scaling schemes. Our 5th article compares and contrasts popular zkEVM solutions and proposes several questions. 53. Developing a Stable Coins Architecture on the ALEO Blockchain In this work we not only propose a mechanism of a stable coin, but a monetary system of two interconnected coins within a ALEO blockchain. 54. Zero Knowledge Proof: Explain it Like I’m 5 (Halloween Edition) Explaining crypto is hard, explaining crypto in simple words is harder. Explaining Zero Knowledge Proof to a child? Easy! So here you go — ZKP explained with some Halloween candy. 55. Zero-Knowledge Proofs: Adventures in the Dark Forest An RTS game on Ethereum… WHAT?! That's possible?! That’s exactly what the Dark Forest, an innovative blockchain game named after Liu Cixin’s eponymous second novel of the Remembrance of Earth’s Past trilogy, is. In fact, it is the first real-time strategy game running on Ethereum in existence. 56. Going Deep into the Specification for Marlin Read on to know about zero-knowledge proof algorithm Marlin which is a R1CS based proof system. 57. Privacy Scales Better: Understanding Zcash, Zero Knowledge Proofs (zKP) & Electric Coin Company innovations at the ECC show not only  that Privacy and Scalability are correlated but also that Governance and Development is more fruitful when rewarded. 58. ZK Rollups in 2023: From SNARK to STARK and Beyond ZK rollups are capturing the attention of the industry. Will they be the future of rollups? Are they good investments? Read this complete guide and research. 59. 20 Future Technologies That Will Change the World by 2050 I recently shared an article called “The “Next Big Thing” in Technology : 20 Inventions That Will Change the World”, which got a few dozen thousand hits in the past couple of weeks. This calls for a sequel. The previous 20 technologies were specifically centered on the next 20 years of technology development; but there’s a lot more to unravel when looking beyond the near future, though certainty obviously decreases with time. Thank you for checking out the 59 most read stories about Zero Knowledge Proofs on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo

59 Stories To Learn About Zero Knowledge Proofs

Meet the Winners of Startups in North and Central America

It's official - the So far, we have received 260 stories and given prizes to 11 winners. As always, we got some superb decentralized internet stories in August. So here we are with more prizes for our writers. Decentralized Internet Writing Contest is a great success! Keep Those Amazing Stories Coming, Comrades! For newbies who want a little context - HackerNoon has built a partnership with giving away monthly prizes worth TON to the best HackerNoon decentralized internet stories! Free Ton 3,500 Here's how you can participate: on HackerNoon. Set up an account the . Check out Decentralized Internet Writing Competition's rules and submit it with as one of the tags. Pen your story #Decentralized-Internet So, who are the winners for the month of August? 👀 Let's find out. Top 15 Contenders for the Month of August First, we picked all the stories on HackerNoon, published in August 2021. As always, we chose the top 15 stories using an algorithm that gives weightage respectively to: tagged with #Decentralized-Internet 60:30:10 Number of hours read Number of people reached Freshness of the content Here is the list of our top 15 contenders: How To Stake ETH 2.0 Without Running a Node and 32 ETH Why YouTube’s biggest competition will come from decentralized video platforms by Banks Make Money Off you, Not for You - Unhashed #16 @musharraf by Future Expectations: What Will Affect Ethereum Price in 2021? @cryptoheisenberg by How Verifiable Creds, Decentralized Identifiers and Blockchain Work Together for a Safer Internet @Fluree by In Decentralized AI We Trust @mywaymywei by How Blockchain can Disrupt the Restaurant Industry @Ishan Pandey by The Cryptocurrency Industry Is The Next Basic Infrastructure of The Internet @johnnylyu by Miner Extractable Value (MEV): The Biggest Thorn in DeFi @Ingalandia by The Graph and Web3 Take On Google and Web2: The Impending Data Economy Wars @alexmexicotte Plookup — An Algorithm Widely Used in zkEVM by @sin7y by Top 5 Crypto + Bitcoin Podcasts @benjaminbateman by Avoid rug pulls, don’t get REKT, and DYOR; the degen’s definitive guide to DeFi @financevote by The Lay of the Cryptoland - Part I: Coins, Wallets, and Exchanges @archis by Lonero Needs the Hackernoon Community's Help @TheLoneroFoundation Human vs. Algorithm Voting. Yes, voting. To keep the selection process transparent and to make sure our algorithm is not abused or misused in any way, we have kept the human factor in the selection process. Our editors then voted for their favorite stories from the above list. Now let's announce the results. was the top choice of both algorithm and humans! How To Stake ETH 2.0 Without Running a Node and 32 ETH Congratulations for winning 2000 TON crystals! @sergey-baloyan Staking in Ethereum 2.0 is blocking ETH in a smart contract to participate in the network as a validator and receive a reward for confirming blocks. Staking became possible after the launch of a new version of the network on the Proof-of-Stake (PoS) consensus algorithm. This consensus algorithm is similar to well-known mining, but instead of using computational resources validators block coins in the wallet to run a special node. In second place, we have . Why YouTube’s biggest competition will come from decentralized video platforms Yay, you've won 1000 TON crystals @jeremykauffman Decentralized video platforms can put in place governance structures to deal with illegal content swiftly. But decentralized platforms will always seek to prioritize user choice, and not restrict content based on social or political beliefs. For a functioning democracy and progressing society, people must be free to exchange and debate ideas, even unpopular ones. All kinds of mainstream ideas, like evolution, heliocentrism, the treatment of ulcers, even democracy itself, were once fringe. Where would we be today if all once-uncommon ideas were immediately silenced? by has won the third position and 500 TON crystals In Decentralized AI We Trust @mywaymywei There are countless examples that central authorities have been overstepping their boundaries to favor themselves when using AI whether it’s using data without user consent or promoting a neutral platform with intentionally biased AI decisions. Imagine if these AI services could prove to you how and when your data is being used - a mechanism that a third party could verify these AI services. Every transaction and decision made by these AI services are transparent for audit and can not be altered. All winners are requested to contact and to claim their prizes. support@hackernoon.com hang@hackernoon.com All hail to decentralization💥. See ya next month! Note: Free TON has now rebranded as Everscale .

#Decentralized-Internet Writing Competition: August Results Announced!

As 2020 is coming to an end, let's see it off in style. Our journey in the world of Graph Analytics, Graph Databases, Knowledge Graphs and Graph AI culminates. The representation of the relationships among data, information, knowledge and --ultimately-- wisdom, known as the data pyramid, has long been part of the language of information science. Digital transformation has made this relevant beyond the confines of information science. COVID-19 has brought years' worth of digital transformation in just a few short months. In this new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. So how do we go from data to information, and from information to knowledge? This is the key question aims to address. Knowledge Connexions Graphs in all shapes and forms are a key part of this. is a visionary event featuring a rich array of technological building blocks to support the transition to a knowledge-based economy: Connecting data, people and ideas, building a global knowledge ecosystem. Knowledge Connexions The Year of the Graph will be there, in the workshop "From databases to platforms: the evolution of Graph databases". George Anadiotis, Alan Morrison, Steve Sarsfield, Juan Sequeda and Steven Xi bring many years of expertise in the domain, and will analyze Graph Databases from all possible angles. This is the first step in the relaunch of the . Year of the Graph Newsletter subscribers just got a 25% discount code. To be always in the know, , and follow the newly launched ! In addition to getting the famous YotG news stream every day, you will also get a 25% discount code. Year of the Graph Database Report subscribe to the newsletter Year of the Graph account on Twitter From databases to platforms: the evolution of Graph databases This workshop wants to help answer everything you’ve always wanted to ask about graph databases, but did not have the chance to. We have tons of news in the Graph Database world. Fluree is going open source, after securing a new round of funding. , enabling SQL access to Knowledge Graphs and visual mapping of tabular data to RDF. Neo4j released a , and a . Ontotext announced a new version, 9.4 new version of its Graph Data Science Library Connector for Apache Spark TigerGraph announced , and a for faster Graph analytics using FPGA hardware. TerminusDB which enables sharing, building, integrating databases collaboratively. And . free licenses for its Enterprise version for databases up to 50GB partnership with Xilinx released  TerminusHub, MarkLogic got acquired by Vector Capital Fluree, the graph database with blockchain inside, goes open source A hitherto under the radar graph database that uses blockchain to support data lineage and verification wants to take over the world, starting with the US Department of Defense. Speaking of graph databases - we have new book releases. " " by Dave Bechberger and Josh Perryman has just been released by Manning Books. It aspires to be a  comprehensive overview of Graph DBs and how to build applications using them, working with Apache open source tools (all code examples use Gremlin). Graph Databases in Action If you are looking for a simpler, getting started book: , a Neo4j Special Edition, introduces the basics of graph database technology from building a rich graph data model to deploying your 1st graph-powered application. Graph Databases For Dummies Last but not least: Denise Gosnell's " ", and Panos Alexopoulos' " , both from O'Reilly. The former is more focused on analytics, the latter on data models for knowledge graphs. To learn the theory and practice of those skills from Alexopoulos, and have the chance to win a copy his book, ! The Practitioner's Guide to Graph Data Semantic Modeling for Data" join his KnowCon2020 sessions Flawless Semantic Modeling in OWL and SKOS The theory and practice of semantic data modeling, focusing on recognizing and avoiding bad practices when developing ontologies, taxonomies, knowledge graphs and other semantic data artifacts There are 2 approaches used to model graph-shaped data: property graphs and RDF, or semantic graphs. In a series of posts, Irene Polikoff from Top Quadrant outlines their differences. Knowledge Graphs vs Property Graphs – Part III Part 3 completes this article series by discussing some important topics beyond the critical differentiators in the terminology and capabilities of Property Graphs and Knowledge Graphs covered in Parts 1 and 2. In terms of adoption versus hype, we have mixed messages from Gartner. On the one hand, the Hype Cycle for Artificial Intelligence 2020 places Knowledge Graphs on the Peak of Inflated Expectations. On the other hand, the . Hype Cycle for Emerging Technologies 2020 places Ontologies and Graphs on the Trough of Disillusionment In reality, none of this matters too much. What matters is that Knowledge Graphs are seeing increasing adoption in the real world. More and more applications based on Knowledge Graphs are being built and deployed, and Knowledge Graph research and innovation is accelerating. 2 Megatrends Dominate the Gartner Hype Cycle for Artificial Intelligence, 2020 While five new AI solutions enter this year’s Hype Cycle for AI, the democratization of AI and the industrialization of AI megatrends dominate the AI landscape in 2020. More Gartner. The 2020 Magic Quadrant for Metadata Management Solutions is out, and just like 2019, it includes 2 vendors whose solutions rely on knowledge graphs and semantics. and the - both present in KnowCon2020. Data.world Semantic Web Company with its PoolParty solution Gartner Magic Quadrant for Metadata Management Solutions Demand arising from a variety of data and analytics initiatives drives strategic requirements for metadata management solutions. This Magic Quadrant will help data and analytics leaders find the most appropriate vendor and solution for their organizational needs. Where Deep Learning ends, Knowledge comes to the rescue. Gary Marcus is one of AI's top minds, and has been a vocal critic of the Deep Learning monoculture for years. He has put forward a well-rounded proposal on how to Reboot AI by infusing it with knowledge, including in the form of knowledge graphs. . Marcus will share this vision in KnowCon2020 What's next for AI: Gary Marcus talks about the journey toward robust artificial intelligence Gary Marcus is one of the more prominent, and controversial, figures in AI. Going beyond his critique on Deep Learning, which is what many people know him for, Marcus puts forward a well-rounded proposal for robust AI Deep Learning on graphs sounds great, but are there any real applications? While Graph Neural Networks are used in recommendation systems at Pinterest, Alibaba, Twitter, another success story is the Transformer. Here's how they are connected. Transformers are Graph Neural Networks My engineering friends often ask me: deep learning on graphs sounds great, but are there any real applications? If you want to learn more about Graph AI, there are a few ways to do this. One is to check out these . GNNs is a relatively new field of Deep Learning, which is getting popular as it proves superior to other machine learning models that work with graph data. Here is a collection of educational resources. Learning Resources for Graph Neural Networks Another way is to join #KnowCon2020, as we have a number of sessions dedicated to Graph AI. #KnowCon2020 features some of the world's top experts on this topic, such as Michael Bronstein, Ines Chami, and Giuseppe Futia Graph AI Graph AI, the intersection of Graphs and Machine Learning, is extraordinarily promising. Knowledge Graphs can help Machine Learning systems bootstrap. Machine Learning can help build Knowledge Graphs. Hyper-relational knowledge graphs (e.g. Wikidata) enable associating additional key-value pairs with a main triple to disambiguate/restrict validity of a fact. StarE is message passing based graph encoder capable of modeling such hyper-relational KGs. Michael Galkin elaborates. Message Passing for Hyper-Relational Knowledge Graphs Traditional KGs are based on triples, whereas new KGs like Wikidata use statements and qualifiers to instantiate each edge further making the graph hyper-relational Wrapping up with Wikidata. Wikidata is an RDF Knowledge Base, and SPARQL is the RDF query language. This . SPARQL tutorial addresses people who don't have previous programming background, to enable them to use Wikidata Wikidata is a fantastic open data knowledge graph, but it's difficult to navigate and query. Navigating means clicking from one item to the next. Querying requires typing in SPARQL. provides a drill-down data exploration interface. Wikidata Walkabout Wikidata looks like a new superpower Knowledge Graph. Its structure allows for representation of richer relations, and as it is crowd authored, it enables richer information, but introduces several challenges Knowledge Graph Context in Deep Learning Approaches Encoding KG Aliases in Attentive Neural Network for Entity Linking. To get the Year of the Graph Newsletter in your inbox, . subscribe here Previously published at https://yearofthegraph.xyz/newsletter/2020/11/graphs-and-knowledge-connexions-the-year-of-the-graph-newsletter-autumn-2020/

Year of the Graph: Analytics, Databases, Knowledge Graphs and Graph AI [Autumn Newsletter]

Application programming interfaces (APIs) have been around for 20 years, but, as points out, just one in five community banks in the USA had deployed APIs before 2020, and they aren’t even on the radar of at least 20% of the banks. Ron Shevlin Contrast this with Europe, where 97% of UK banks are already using them, and even the lowest uptake country, the Netherlands, has 83% of its banks deploying APIs.The reason for this huge gap between the USA and Europe is the latter’s Open Banking initiative, however Shevlin says that American banks cannot simply use this as an excuse for their low adoption of the technology. As a result of the lack of API deployment, US banks are missing out on a number of opportunities, including the reduction of time and costs in several business processes, particularly product application-related processes. The best known API providers include Stripe, Plaid and Yodlee. These three have furthered the connections between financial institutions and fintech companies. However, Shevlin says there are three fintech startups that are “poised to have a significant impact on the banking industry: Pinwheel, Sila, and Codat.” Pinwheel Pinwheel, which has just announced a $7 million funding raise, offers an API for payroll data, “that handles everything from income and employee verification to easily switching and managing direct deposit.” How would this revolutionise banking? According to a Techcrunch article, “For consumers, the main draw is automated direct deposit control, which will allow consumers to control where their paychecks go. For instance, if they want to split a direct deposit into multiple accounts, or regularly move part of their paycheck into a savings app like Digit or Acorns, Pinwheel can help them do that easily.” Sila According to Coindesk, Sila, “is an API platform that issues an ERC-20 stablecoin called SilaToken (SILA). Every transaction on the platform is done using the token, which is pegged 100:1 to the U.S. dollar. Sila plans to install card payments, international payments, business ID verification and begin issuing tokens within one business day. Its partner bank, Evolve Bank & Trust, plans to connect to the Clearing House system, a network started by big banks that provides access to instant payments.” Techcrunch comments that Sila’s API would: “Supplant ACH as the payments choice for companies who need to move money. Sila’s API for identity verification, which empowers developers to identify users and use that info in the company’s banking API, allows users to debit their accounts and move funds from one account to another. On top of that infrastructure, Sila allows for the creation of smart contracts, which should allow for more rapid deployment of financial apps.” Codat Codat, which is based in London, has an API focused on small businesses, and is signing up 10,000 new customers per month. According to TechCrunch: “Codat is building an API that connects with all the systems that hold all the relevant financial data. That type of information is usually spread across multiple systems, and small businesses often use different systems. On the other side, banks, insurance companies and more can speed up their internal processes and give you an educated answer for your next loan or insurance product.” Codat is especially on point right now as small businesses are struggling and need funds. However, the current lending processes are time-consuming and confusing. Its API simplifies and streamlines the flow of data between small businesses and financial institutions, and could potentially disrupt the way SME loans are handled today. Blockchain As an API Alternative? On the other hand, perhaps APIs aren’t the ultimate answer for a banking revolution. Brian Platz, co-CEO of Fluree, says, “The answer isn't to build a better API; rather, it is to turn the database inside out and let data escape from the walls that confine it. Blockchain is how data frees itself. It’s time to end the era of data APIs and begin to look into the blockchain.”

Stories, News & Mentions about FLUREE

Fluree’s Stories on HackerNoon

Fluree's News & Mentions