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README.md

COALA IP Spec / Whitepaper

TL;DR

COALA IP is a blockchain-ready, community-driven protocol for intellectual property licensing.

This presentation gives a quick summary. Here's an extended version.

This academic paper is about how blockchains can support, complement, or supplement IP, authored by the COALA IP working group.

Resources

Links to reference code implementations can be found here.

COALA IP is a community effort. Here's how to contribute to this doc, or to the code. Main contributors are listed at the bottom; thanks everyone! Don't be shy -- please give us your questions, suggestions or feedback :).

What follows here is the whitepaper, including full-on specifications. Here we go...

Abstract

Content creators on the internet are getting a raw deal. They get a fraction of the revenue earned by hosting and distribution platforms, even though their work is what keeps these sites filled with traffic-driving content. It's hard for a creative to make a living. Licensing is hard: the user experience is bad, with lawyers and middlemen extracting the most value. In many areas, more money goes to the distributors than to the creators. Even though many consumers would be happy to pay the people who made the content they love, they aren't given the chance–instead, they are surveilled and served ads. It doesn't have to be this way.

The Coalition of Automated Legal Applications — Intellectual Property (COALA IP) group was formed to address these problems. COALA IP's goal is to establish free, open, and easy-to-use methods of recording attribution and related metadata about works, assigning or licensing rights, mediating disputes, and authenticating claims by others. We believe there should be a global standard at the data level, without the need for centralized control.

This document details an approach of representing intellectual property claims on distributed ledgers (or blockchains). It is an effort to transform the Linked Content Coalition (LCC)'s implementation-agnostic Rights Reference Model (RRM) into a free and open standard by outlining technologies that could be leveraged for an implementation. This document aims to represent the interests of all involved stakeholders: creators, rightsholders, distributors, consumers, developers, and so on.

COALA IP's vision will be realized through three key efforts:

  1. Authoring a guide to provide an overview of the field and the need for a technical specification to represent intellectual property rights on distributed ledgers (see Introduction);
  2. Defining a technology-specific, but ledger-agnostic, free and open messaging and communication protocol for intellectual property rights and licensing transactions (see Implementing the RRM); and
  3. Building a community to define a minimally-viable set of data for the description of intellectual property rights and licensing agreements.

Introduction

This section describes the technological concepts used in this document to model a generic and extensible protocol for managing digital rights. Each write-up is meant only as a brief overview; to gain a more comprehensive understanding, we encourage you to explore the reference materials provided as embedded links or in the Sources subsections.

The LCC Framework

The LCC Framework is a set of documents published by the Linked Content Coalition (LCC) to "unify digital rights data management." The key documents include:

The LCC's Ten Targets

The LCC's foremost goals are to enable, for all parties, the widest possible access to accurate rights information, as well as the automation of rights licensing and assignment for both commercial and free use. The LCC released the "LCC Ten Targets for the Rights Data Network" as a general guide toward achieving these goals. It asks for the following:

  1. Every Party has a unique global identifier;
  2. Every Creation has a unique global identifier;
  3. Every Right has a unique global identifier;
  4. All identifiers are associated with a URI that will persistently resolve them within the internet;
  5. Links between identifiers are platform agnostic and non-proprietary
  6. Metadata is platform agnostic or interoperable; mappings should be available to translate between schemata authorized by multiple parties;
  7. The provenance of rights has to be made explicit;
  8. Any participant has the ability to make standardized, machine-readable statements about rightsholdings in Creations;
  9. Conflicts in rights declarations should be automatically identifiable; and
  10. Registered Creations are associated with corresponding digital "fingerprints" or "watermarks".

For more in-depth information about the goals of the LCC, see the "LCC Ten Targets for the Rights Data Network".

Sources:

The LCC Entity Model

Note: You don't need to know the LCC Entity Model to understand the rest of this document. The Entity Model is a meta-model used by the LCC to model their higher-level Rights Reference Model.

The LCC Entity Model (LCC EM) specification defines an Entity model composed of five attribute types:

  • Category: A broad category the Entity belongs to (e.g. Language=iso3166-1a2:EN ("English"))
  • Descriptor: The name of the Entity (e.g. Name="Andy Warhol")
  • Quantity: A numeric value related to the Entity (e.g. Height=20cm)
  • Time: A time or date related to the Entity (e.g. DateOfCreation=1999)
  • Link: A link to another Entity (e.g. "Andy Warhol" ––isCreator––> "32 Campbell's Soup Cans")

These attributes are each represented as sub-models in the specification and, together with unidirectional links, make up the actual Entity model. An entity can be linked to other entities bidirectionally, as the attached figure shows:

The attributes of the Entity model are designed to be generic to allow for more complex data models (e.g. the LCC RRM) to be built on top.

Sources:

The LCC Rights Reference Model

The LCC Rights Reference Model (LCC RRM) is a formal framework of representing intellectual property rights. The RRM describes a high-level data model built on top of the LCC Entity Model, composed of the following entity types:

  • Party: A person or an organization (e.g. "Richard Prince", "American Apparel", or "Sky Ferreira")
  • Creation: Something created by a Party (e.g. "Untitled Instagram Portrait")
  • Place: A virtual or physical location (e.g. "New York City" or "http://www.newyorkcity.com")
  • Right: A set of permissions that entitle a Party to do something with a Creation (e.g. production and sale of t-shirts bearing the Creation)
  • RightsAssignment: A decision by a Party resulting in the existence of a Right (e.g. "Richard Prince grants American Apparel the right to produce and sell t-shirts bearing Untitled Instagram Portrait in North America")
  • Assertion: A claim made about the substance of a Right (e.g. "Richard Prince claims he has copyright to Untitled Instagram Portrait", or "Sky Ferreira claims she has copyright to Untitled Instagram Portrait")
  • RightsConflict: A statement of disagreement over a Right (e.g. "Sky Ferreira and Richard Prince both claim copyright to Untitled Instagram Portrait")

Note: For the sake of simplicity, the Context type has been left out. It is defined by the RRM only as a parent/categorizing class of Right, RightsAgreement, Assertion, and RightsConflict and holds no significant value on its own.

These seven entity types are the building blocks of a global digital rights ontology. They can be linked to each other through specific, unidirectional relationships. The figure below specifies the total possible relationships between Entities:

Sources:

The LCC Principles of Identification

  • TODO:
    • Summarize briefly (as done in the other sections) what the document talks about, without going into too much detail

Sources:

The Semantic Web

The world wide web (web) is an information space for sharing information through linked documents. The web is mostly used by humans, with information published and accessed in human-readable formats (e.g. a webpage). Although machines are, in theory, capable of understanding this kind of information, in practice, this is usually difficult and inefficient. For example, while humans may easily understand a webpage with a table listing national populations, a machine would likely not understand or be able to deduce new information–even the appropriate context was given by naming a column as "Country Population".

To solve this, the semantic web introduces methods of publishing information in formats that are capable of holding semantic meaning for both humans and machines. This allows humans to publish human-readable information in a way that is also understandable to machines. The key underlying building block of these formats is the Resource Description Framework.

Sources:

  • A. Granzotto (2009): Exploiting spatio–temporal linked data to improve backlinks retrieval

The Resource Description Framework (RDF)

The Resource Description Framework is a framework for describing ontologies. It uses the Universal Resource Identifier (URI), a generalization of the Universal Resource Location (URL), to address resources. This allows RDF to be exceptionally interoperable and extensible.

RDF's core data structure is a graph-based model that uses sets of triplets to construct graph subsets. Each triplet consists of a subject, predicate, and object. In its smallest form, an RDF graph can be just a single triplet. Visualized, it would look like this:

Each node would usually be expressed as an URI to a resource that provides further details about the node's relationship to the graph.

The following example was used in the Creative Commons Rights Expression Language (ccREL) W3C submission:

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
        xmlns:xhtml="http://www.w3.org/1999/xhtml/vocab#">
    <rdf:Description rdf:about="http://www.lessig.org/blog/">
        <xhtml:license rdf:resource="http://creativecommons.org/licenses/by/3.0/" />
    </rdf:Description>
</rdf:RDF>

This example triplet states licensing information about Lawrence Lessig's blog in a machine-readable way. Lessig's blog (the subject) is licensed (the predicate) under a Creative Commons Attribution 3.0 license (the object). Provided by Creative Commons, ccREL is just one example of a context-providing schema that is built on top of RDF. Others, such as the Open Digital Rights Language (ODRL), also exist.

RDF itself includes multiple implementations, each varying in their underlying data structures. Embedding RDF in HTML pages and RDF/XML syntax are two of the more popular implementations, albeit with relatively heavy syntaxes and learning curves. In 2014, alongside the release of RDF 1.1, a new RDF-compatible, Javascript Object Notation (JSON)-based data structure was accepted by the W3C: JSON-LD. JSON-LD fit the semantic web's Linked Data concept into the widely popular JSON format and provided a much more approachable format to work with RDF.

Sources:

Linked Data

JSON Linked Data

JSON-Linked Data (JSON-LD) is a data structure that merges the concepts of linked and interoperable data into the JSON format with RDF support. In the context of RDF, JSON-LD allows users to link a JSON object's properties to a corresponding RDF schema through the concept of a context.

Assume we have the following set of data, modelling a user:

{
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06"
}

For a human, it's obvious this is about a person named Andy Warhol, born August 6, 1928. However, for a machine, which lacks the intuition and context of a human, resolving this representation into the same conclusion is difficult.

JSON-LD solves this problem by introducing context to JSON documents. On a high level, this allows data to be linked to already defined schemata. Adding a special @context key to the document provides a reference to the schema of the underlying data. Transforming our previous example to use JSON-LD:

{
    "@context": "http://schema.org/Person",
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06"
}

Upon seeing this data, a JSON-LD parser could use the @context property and send a GET to http://schema.org/Person to receive the defined schema and perform validation. If another application developer were to handle this data, they could rely on the same schema definition rather than their own. Over time, as more and more services use JSON-LD, data representations across services would begin to unify to improve cross-service data interoperability.

Take, for example, our previous user model. Right now, each application or service might use their own model definitions: one site could choose birthday, while another uses day_of_birth or birthDay, to represent the user's birthday. These models might also be of different formats: some could be in YYYY-MM-DD while others DD-MM-YYYY. Despite all of them containing the same semantic meaning, custom logic would have to be written to not only handle the mapping between the different keys, but also to convert their values to a standard format.

JSON-LD's context solves these problems by allowing for:

  1. A unified mapping of keys that comply to base schemata; and
  2. Value validation for primitive data types.

To see how context achieves this, we need to explain how JSON-LD magically maps our example's self-defined keys (givenName, familyName and birthDate) to their matching properties on the Person schema. If you look at the Person definition, you'll notice that we didn't choose random keys–they were already part of the schema definition. Because of this, JSON-LD parsers are able to automatically map and validate our example model's properties against their schema definitions.

For more clarity, let's see how a JSON-LD parser would look at our example:

  1. Notice @context contains http://schema.org/Person
  2. GET http://schema.org/Person and add it to @context as part of the schema
  3. For each of the model's keys, check if they map to any keys provided in the resolved @context
    1. For each matched key (a "term"), traverse the @context until a definition is found (a "term definition"), usually as a leaf node in the @context
    2. "Expand" the data, replacing keys' names with their URI definitions

Continuing with our example, this is the result after expansion:

{
    "http://schema.org/givenName": [
        {
            "@value": "Andy"
        }
    ],
    "http://schema.org/familyName": [
        {
            "@value": "Warhol"
        }
    ],
    "http://schema.org/birthDay": [
        {
            "@value": "1928-08-06"
        }
    ],
}

The JSON-LD parser notices that the model contains keys matching the Person schema, and uses http://schema.org/Person to replace these matches with an URI to their schema definition. The result, termed as "Expanded Document Form", is now a set of data that has been automatically mapped to the given schemata. This form can be considered the canonical version of the data: anyone can now take this form and understand its properties, regardless of the key names used in the original model. Moreover, as leaf @value nodes are only allowed to define the most basic types (e.g. string, boolean, integer, etc.), this expanded form also enables a parser to easily traverse the document and validate each occurrence of @value.

As the rest of this document relies heavily on JSON-LD, we encourage you to learn more by reviewing the Sources below.

Sources:

Schema.org

  • TODOs in this section:
    • Just describing schema.org is too narrow here. This section should be about linked data on the world wide web in general. schema.org is just a regular player when it comes to linked data and RDF. There are even search engines that users can lookup schemas (http://wiki.dbpedia.org/). Obviously mention schema.org as a preferred source though.

Schema.org is a collaborative initiative with the mission to create, maintain and promote schemata for structured data on the internet. Its schemata are defined through ontologies, with concepts connected to each other through links. A number of encoding formats are supported, including RDFa, Microdata, and JSON-LD.

Available Schemata

Schema.org includes the following core schemata that are closely related to LCC RRM's entity types:

The full list of all core schemata is available at schema.org/docs/full.html.

In summary:

Extensibility of schema.org

Despite an exhaustive list of schemata provided by schema.org, we still have a few use cases that have not been covered: the missing Right and RightsConflict entity types, as well as any additional RRM properties that have not been defined in the existing schemata. Thankfully, schema.org was designed with extensibility in mind–we can modify existing, and even create new, schemata to fit our needs. Schema.org even encourages others to subclass the core schemata into "hosted" and "external" extensions, making available three types of schemata:

  • Core: A set of basic vocabulary for describing the kind of entities needed by most web applications;
  • Hosted: Application-agnostic schemata deriving from core which have their own namespace on schema.org (e.g. http://health-lifesci.schema.org/) and are reviewed by the schema.org community; and
  • External: Schemata from core or hosted which have an application-specific namespace (e.g. http://schema.coala.global) and may be application-specific

In the context of COALA IP, any application-agnostic schemata, including all schemata derived from the LCC RRM, would become a hosted extension. Fortunately, leveraging schema.org in this way maintains compliance with rules five and six of the LCC's "Ten Targets":

  • Rule 5: Links between identifiers are platform agnostic and non-proprietary.
  • Rule 6: Metadata is platform agnostic or interoperable; mappings should be available to translate between schemata authorized by multiple parties.

Sources:

Interplanetary Linked Data

This section describes the functionality of Interplanetary Linked Data (IPLD) and its use when working with immutable data stores and Linked Data. IPLD is an attempt to put Linked Data on distributed ledgers by using hashes as content-addressed links, a technique referred to as "Merkle Links." Merkle links provide a number of interesting properties, foremost of which is the ability to cryptographically check the data referred to by a link.

Motivation for IPLD

If we go back to our Andy Warhol example:

{
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06"
}

Let's add a set of data describing one of his works:

{
    "name":"32 Campbell's Soup Cans",
    "dateCreated": "01-01-1962",
    "exampleOfWork": "https://en.wikipedia.org/wiki/Campbell%27s_Soup_Cans#/media/File:Campbells_Soup_Cans_MOMA.jpg"
}

Note that neither object contains a link to the other. There is no way for someone to tell that Andy Warhol is the creator of "32 Campbell's Soup Cans" from just the data alone. We could solve this by using JSON-LD: we could make both of the objects resolvable on the internet, add @ids to the objects' bodies, and add an author property to the creation object that points to the person object's location.

However, this result runs into the problem of implicitly trusting the hosts that make these objects resolvable. Hosts might return the correct objects at first, but that could change. Even worse, resolving actors have no way of checking the integrity of an object they're requesting; a host could return arbitrary, or even wrong, data that will stay undetected by the resolver. IPLD solves these problems by using a hash-based, content-addressed linking format.

IPLD by Example

For these examples, we use py-ipld, an existing Python implementation of IPLD, to handle IPLD specifics and data transformations. Other implementations, such as js-ipld also exist.

Creation of Linked Objects

We can use IPLD to link the person and creation objects discussed earlier with the following steps:

  1. Serialize the person object to its canonical Concise Binary Object Representation (CBOR) form:

    In [1]: import ipld
    
    In [2]: person = {
    ...:     "givenName": "Andy",
    ...:     "familyName": "Warhol",
    ...:     "birthDate": "1928-08-06"
    ...: }
    
    In [3]: serialized_person = ipld.marshal(person)
    Out[3]: b'\xa3ibirthDatej1928-08-06jfamilyNamefWarholigivenNamedAndy'

    ipld.marshal serializes the person object to a CBOR byte array, using the CBOR reference implementation.

  2. Hash the serialized byte array using multihash, encoding the hash to base58:

    In [4]: ipld.multihash(serialized_person)
    Out[4]: 'QmRinxtytQFizqBbcRfJ3i1ts617W8AA8xt53DsPGTfisC'
  3. Now that we've derived an IPLD hash from the person object, we can use it to define an author for the creation:

    In [5]: creation = {
        "name":"32 Campbell's Soup Cans",
        "dateCreated": "01-01-1962",
        "exampleOfWork": "https://en.wikipedia.org/wiki/Campbell%27s_Soup_Cans#/media/File:Campbells_Soup_Cans_MOMA.jpg",
        "author": { "/": "QmRinxtytQFizqBbcRfJ3i1ts617W8AA8xt53DsPGTfisC" }
    }

    We've now connected the creation to its author by using a person's hash value for the author property, creating our first "Merkle Link." Generally, merkle links can be schematized as:

    Property = {
        ...
        [<String>]: <MerkleLink>
    }
    
    MerkleLink = {
        "/": <String: multihash value>
    }
  4. Finally, to obtain a resolvable hash for the creation, we repeat the first two steps. First serialize the creation object its canonical CBOR form:

    In [6]: serialized_creation = ipld.marshal(creation)
    Out[6]: b"\xa4fauthor\xd9\x01\x02x.QmRinxtytQFizqBbcRfJ3i1ts617W8AA8xt53DsPGTfisCkdateCreatedj01-01-1962mexampleOfWorkx]https://en.wikipedia.org/wiki/Campbell%27s_Soup_Cans#/media/File:Campbells_Soup_Cans_MOMA.jpgdnamew32 Campbell's Soup Cans"

    And then hash the resulting serialized byte array using multihash and a base58 encoding:

    In [7]: ipld.multihash(serialized_creation)
    Out[7]: 'QmfMLNLyJZgvSPkNMvsJspRby2oqP6hWZ8Nd2PvKLhudmK'

    Note: The creation's CBOR form replaced the original merkle link contained in author with an unassigned CBOR tag (258) to make the link more easily retrievable on deserialization.

Retrieval of Linked Objects

To further explore IPLD, let's assume we've put these objects into a data store and try to retrieve them. We'll use IPFS for the data store as its identifiers are compatible with our previously created hashes.

We can use paths of merkle links ("Merkle Paths") to resolve any object within IPFS from their hash value, as well as further de-reference any nested merkle links in the dereferenced object. Given the example above, the author of the creation could be found through this merkle path:

In [8]: ipld.resolve('/ipfs/QmfMLNLyJZgvSPkNMvsJspRby2oqP6hWZ8Nd2PvKLhudmK/author')
Out [8]:
{"givenName": "Andy",
 "familyName": "Warhol",
 "birthDate": "1928-08-06"}

IPLD resolves any merkle link, in this case the creation's author, to the actual object before any further dereferences are made, allowing the creation and traversal of merkle links to feel similar to Unix paths or accessing properties in nested objects. To link across network addresses, we can use multiaddr to construct resource paths across protocols. Such links would allow an IPLD object to maintain resolvable links even if those links point to separate ledgers (e.g. IPFS, BigchainDB, Ethereum, Bitcoin, etc.).

Evaluation of IPLD

In summary, IPLD looks to be a promising new data format suited for our needs, albeit with a few cavets:

  • Benefits:
    • Provides cryptographic integrity checks of data using upgradable hash functions (multihash);
    • Uses content-addressed storage instead of location addressed storage (merkle links vs. URLs);
    • Enables cross-ledger/database links (multiaddr and merkle paths);
    • Unifies object identifiers through a canonicalized hashing strategy;
    • Imposes immutability through the underlying merkle-dag data structure;
    • Future-proofs underlying concepts (multi-x);
    • Enables wide compatibility, even down to the UNIX file system path; and
    • Deserializes to a multitude of other data serialization formats (YAML, JSON, etc.).
  • Caveats:
    • Non-standardized protocols (multi-x);
      • Overlaps with other protocols that are being standardized
      • Breaks with existing and well-established protocols (e.g. URI vs. multiaddr)
    • Does not comply with most existing Linked Data ontologies due to immutability constraints; and
    • Uses an opinionated CBOR serialization strategy.

Compatibility of IPLD and JSON-LD

Although the naming and concept of IPLD was inspired by JSON-LD, the two have different sets of functionality. In particular, while the two can be used together, IPLD imposes a number of limitations on JSON-LD's feature set.

Self-identifying JSON-LD Objects

With an @id, JSON-LD objects are able to maintain a self-identifying link and directly express their resolvable location to users. However, the same is impossible for IPLD objects: as IPLD objects are designed to be retrieved only by the canonical hash of their data, this hash cannot be included as part of the pre-hashed data (trying to do so would amount to solving a cryptographic puzzle). To avoid this, we use an empty @id on IPLD objects to resolve these objects to their current document bases (i.e. their resolvable, content-addressed location on IPFS, etc.).

Sources:

The Web of Trust

Fingerprinting

Determining the originality and provenance of a creation is challenging. This is true of physical creations, but even more so for digital creations which face the challenges of being perfectly copyable as well as easily modifiable. Although computers are good at determining perfect copies, they struggle if subtle modifications, such as compressing image quality or cropping an image, are made–even if a human would have no difficulties in making a connection.

The LCC takes these problems into account. In their "Ten Targets" document, they propose cross-standard identifiers that can, if needed, be transformed into alternative identifiers. This section discusses a similar idea: the existence of an arbitrarily complex graph that can be used to link all the alternative identifiers of a single work to a single identifier on a global rights registry.

Any function that takes a digital asset as an input and yields a fixed-length value could potentially be used as a fingerprinting function. This could be as simple as a hash function that inspects the arrangement of bytes in a digital asset and returns a integer, but there are more elaborate versions:

  • Image-match: An approximate image match algorithm implemented in Python;
  • pHash: A hashing method using various features of a digital asset;
  • dejavu: An audio fingerprinting and recognition algorithm implemented in Python;
  • And many more

While a manifestation of a digital creation may initially only have a single fingerprint generated by an arbitrary hashing function, more elaborate fingerprinting schemes could later be used to help automatically identify other occurrences of the creation on the internet. Paired with Linked Data, fingerprinting schemes would allow an arbitrarily complex graph to store and track all the information related to the use of a work: copies, remixes, mash-ups, and modified versions could all be identified automatically as paths in the graph. A traversal up a path would reveal the original instance of the work and possibly identify the creator as well as an opportunity for compensation.

Based on this, as rights information becomes more transparent and rights easily licensable by users, participants in the system would be incentivized to create more elaborate fingerprinting systems to further increase transparency.

The Interledger Protocol

  • TODO:
    • This section should briefly explain what Interledger and the Interledger Protocol is about and how COALA IP could potentially use it.

COALA IP: Implementing the LCC RRM with Linked Data

In this section we describe how the LCC Rights Reference Model can be modelled into a Linked Data representation by using schema.org as a building block. We go over each entity described in the RRM and discuss their translations into JSON-LD and IPLD. Linked Data, JSON-LD, and IPLD have been chosen as they offer a number of advantageous properties for modelling global intellectual property claims on distributed ledgers; for more information, see their respective sections above.

Note: The JSON-LD and IPLD models given in this section are not meant to be used directly. They may also grow outdated with time. These models are primarily provided as simple examples for how a given transformation may be implemented; consequently, they may be more incomplete and abstract than a production-ready implementation. For the reference implementation of these models, see the reference JSON-LD / IPLD entity schemata.

What Linked Data Gives Us Out of the Box

As a building block of the RRM, the LCC first defined a generic, linkable Entity Model whose entities could be combined to create an extendable data model for intellectual property. However, by implementing into a Linked Data-based data structure, we can ignore these basic entities as Linked Data already provides us with the linkable base data structure–RDF.

General Approach

Our approach to implementing the RRM is as follows:

  1. Identify existing RDF-compatible schemata that map to RRM entities;
    • If no appropriate schemata exists:
      • Compose new RDF types from existing schemata; or
      • Define entirely new schemata
  2. Define how entities can be identified and resolved;
  3. Resolve any mismatches between the RRM terminology and chosen RDF-compatible schemata; and
  4. Modify the chosen schemata's semantics for use on a distributed ledger, if necessary.

A slight speed bump in the schematization process comes when we try to maintain support for generic links between entities. The RRM defines the existence of links in a generic, one-to-many (i.e. 0 - n) manner. However, RDF and Linked Data require these links to be explicitly named so as to express specific facts within their ontologies. For example, schema.org's schemata often include a finite set of links that can be mapped to the RRM's links, but cannot directly support the possibly infinite number of links allowed by the RRM. To overcome this limitation, users can extend the base schemata we've provided with their own requirements (see User Extensions).

For the purposes of demonstration, we put any new schemata into http://coalaip.schema/ and assume that this document also contains all schema.org definitions (so we don't have to provide http://schema.org/ as an additional context).

The RRM Place Entity

In the LCC RRM, a Place describes a localizable or virtual place. It contains the following property:

  • PlaceType: Defines the type of a Place; one of:
    • lcc:LocalizablePlace: A Place in the physical universe locatable by spatial coordinates; or
    • lcc:VirtualPlace: A non-localizable Place at which a resource may be located

In addition, a Place can have the following outgoing links to other entities:

  • Links to other Places (0 - n; one-to-many): RelatedPlace

Visualized, an RRM Place looks like:

Proposed Transformation

In contrast to schema.org's definition of a Place, an RRM Place is able to describe both physical and virtual places. To avoid confusion in the transformation process of later entities, we explicitly separate the two concepts here. We use an:

  • RRM Place to describe a localizable, or physical, place in the universe that can be described by spatial coordinates; and an
  • Universal Resource Identifier or IPLD merkle link to describe a virtual place where a resource may be found.

With schema.org's Place, the transformation of a localizable Place is straight-forward (example adapted from schema.org):

// In JSON-LD
{
    "@context": "http://schema.org/",
    "@type": "Place",
    "geo": {
        "@type": "GeoCoordinates",
        "latitude": "40.75",
        "longitude": "73.98"
    },
    "name": "Empire State Building"
}

// In IPLD
{
    "@context": { "/": "<hash pointing to schema.org's context>" },
    "@type": "Place",
    "geo": {
        "@type": "GeoCoordinates",
        "latitude": "40.75",
        "longitude": "73.98"
    },
    "name": "Empire State Building"
}

To support links to other Places, one can use either of the two pre-defined properties on schema.org's Place–containsPlace or containedInPlace–or extend the schema with their own properties.

The RRM Party Entity

The LCC recommends a Party to be capable of representing any of the following classes of parties:

  • Rightsholders;
  • Licensors;
  • Administrators;
  • Users; or
  • Any other participants related to rights.

RRM Partys must have the following properties:

  • PartyType: Defines if the Party is an individual (lcc:Individual) or a group of individuals (lcc:Organization);
  • DateOfBirth: Party's date of birth; only if PartyType == 'lcc:Individual'; and
  • DateOfDeath: Party's date of death; only if PartyType == 'lcc:Individual'.

Additionally, a Party can have the following outgoing links to other entities:

  • Links to other Partys (0 - n; one-to-many): RelatedParty
  • Links to Places (0 - n; one-to-many): RelatedPlace

Visualized, an RRM Party looks like:

Proposed Transformation

Note: We describe the transformation of a RRM Party into a JSON-LD/IPLD Person and Organization very literally here, so as to provide reasoning for the steps taken in the transformation. Other entities omit similar descriptions and focus on providing rationale for the transformations that are specific to them.

Schema.org makes both a Person and an Organization available; hence, there is no need to define either concept as a single model differentiated by PartyType. To keep the transformation simple, let us first transform an Party with PartyType == 'lcc:Individual' and then apply the learnings to an Party with PartyType == 'lcc:Organization'.

Transformation of RRM Party to an RDF Person

Using the minimum number of properties described in the RRM, an RRM Party with PartyType == 'lcc:Individual' could be modelled with mappings to schema.org/Person like so:

// In JSON-LD
{
    "@context": {
        "DateOfBirth": "http://schema.org/birthDate",
        "DateOfDeath": "http://schema.org/deathDate"
    },
    "@type": "http://schema.org/Person",
    "DateOfBirth": "1928-08-06",
    "DateOfDeath": "1987-02-22"
}

// In IPLD
{
    "@context": {
        "DateOfBirth": { "/": "<hash pointing to RDF-Schema of birthDate>" },
        "DateOfDeath": { "/": "<hash pointing to RDF-Schema of deathDate>" }
    },
    "@type": { "/": "<hash pointing to RDF-Schema of Person>" },
    "DateOfBirth": "1928-08-06",
    "DateOfDeath": "1987-02-22"
}

While there is nothing technically wrong with the above, you may notice that schema.org/Person already contains the birthDate and deathDate properties. Rather than reinventing the wheel and remapping DayOfBirth and DayOfDeath to these properties, we can remove the aliasing and use the properties directly on our model. This gets us:

// In JSON-LD
{
    "@context": "http://schema.org/",
    "@type": "Person",
    "@id": "https://en.wikipedia.org/wiki/Andy_Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

// In IPLD
{
    "@context": { "/": "<hash pointing to schema.org's context>" },
    "@type": "Person",
    "@id": "https://en.wikipedia.org/wiki/Andy_Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

In the example, we've used Andy Warhol's Wikipedia page as his identifier (@id). As an @id value is only required to be a well-formed URI or IPLD merkle-link, a JSON-LD parser would validate this without complaining; however, @id would ideally point to a location that holds the JSON-LD data itself. Unfortunately, this functionality isn't supported by Wikipedia–https://en.wikipedia.org/wiki/Andy_Warhol doesn't return a JSON-LD representation–and we have to look for another solution.

To start, lets look at some limitations and requirements derived from the LCC, JSON-LD, IPLD, and immutable ledgers:

  • LCC's Ten Targets:
    • A Party's identifier should be linked to the International Standard Name Identifier (ISNI) hub.
    • A Party's identifier should have an URI representation, so that it can be resolved predictably and persistently within the Internet.
  • LCC's Principles of Identification:
    • A Party should be associated with at least one persistent unique public identifier that is both human- and machine-readable.
    • If a Party is associated with multiple public identifiers, there should be a way to automatically transform one identifier to another.
    • A Party's identifier can have multiple designations (e.g. ISBN-10, ISBN-13, ISBN-A, etc.).
    • A Party's identifier should have an URI representation.
    • A Party's identifier should not have any intended meaning that could be misinterpreted by humans.
    • A Party's identifier should not include any information about the Party itself or its registration date.
    • TODO: There are even more requirements in this document that should be listed here!
  • JSON-LD:
  • IPLD:
    • Any object must be addressable using its multihashed value.
  • Immutable Ledgers:
    • Elements of the Party's identifier must be capable of representing the public part of an asymmetric cryptographic key-pair.
    • A Party can only be created when at least one valid cryptographic key-pair is provided.

Unfortunately, there are no currently available systems that are able to fulfill all of these requirements and become a registry for RRM Party data. However, let's pretend, for the sake of completeness, that we have access to such an identity service—preferably a decentralized not-for-profit service!–in the following examples. It will let users:

  • Issue an identity that can be resolved using JSON-LD (with Content Negotiation) or IPLD; and
  • Attach the public part of their key-pairs to their identity.

Services that could be extended to support our use case include:

Equipped with this identity service, we can go back to our example's JSON-LD representation and replace its @id value with an URI pointing to the dataset (the dataset itself living on the identity service):

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "Identity",
    "@id": "<URI pointing to this object>",
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

On IPLD, we use an empty @id to identify an object by its own hash. Thus, we get:

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Identity",
    "@id": "",
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

And finally, to complete the transformation, we include support for the possible outgoing links of an RRM Party: links to other Partys (RelatedParty) and links to Places (RelatedPlace). To give some context, a few potential use cases for these links include:

  • Multiple Partys sharing a relationship (e.g. Party A and Party B created Creation C);
  • Partys providing Places as part of their metadata (e.g. home location, contact place, or billing address); or
  • Multiple Partys being bundled together as an Organization.

A few linking possibilities are already covered by schema.org, such as a Person's home address (schema.org/Person's homeLocation; specifying a Place) or parents (schema.org/Person's parent; specifying a Party). If one wanted to use relations that schema.org hadn't already provided, schema.org/Person could be extended with new properties.

Transformation of RRM Party to an RDF Organization

An RRM Party with PartyType == lcc:Organization describes a single entity representing a group of individuals. Using the minimum number of properties listed in the RRM, an lcc:Organization Party could look like this as a schema.org/Organization:

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "Organization",
    "@id": "<URI pointing to this object>",
    "name": "World Wide Web Consortium",
    "founder": {
        "@type": "Identity",
        "@id": "<URI pointing to the founder Party>"
    },
    "member": [
        {
            "@type": "Identity",
            "@id": "<URI pointing to a member Party"
        },
        {
            "@type": "Identity",
            "@id": "<URI pointing to a member Party"
        },
        {
            "@type": "Identity",
            "@id": "<URI pointing to a member Party"
        }
    ]
}

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Organization",
    "@id": "",
    "name": "World Wide Web Consortium",
    "founder": {
        "@type": "Identity",
        "@id": { "/": "<hash pointing to the founder Party" }
    },
    "member": [
        {
            "@type": "Identity",
            "@id": { "/": "<hash pointing to a member Party" }
        },
        {
            "@type": "Identity",
            "@id": { "/": "<hash pointing to a member Party" }
        },
        {
            "@type": "Identity",
            "@id": { "/": "<hash pointing to a member Party" }
        }
    ]
}
  • TODO: This needs a lot of speccing out. How can members of an organization collectively sign something they're submitting? Is there a single public key address assigned to an organization or does the organization just bundle members that act like they were in an organization but act independently?

The RRM Creation Entity

An RRM Creation entity describes creations that are directly or indirectly made by human beings. The specification proposes a single required property:

  • CreationMode: Defines the mode of the Creation; one of:
    • lcc:Manifestation: A perceivable manifestation of a Work; or
    • lcc:Work: A distinct, abstract Creation whose existence is revealed through one or more Manifestations.

Additionally, a Creation can have the following outgoing links to other entities:

  • Links to other Creations (0 - n; one-to-many): RelatedCreation
  • Links to Places (0 - n; one-to-many): RelatedPlace
  • Links to Partys (0 - n; one-to-many): RelatedParty

Visualized, an RRM Creation looks like:

Proposed Transformation

Schema.org's existing schemata already covers a large number of the Creation's use cases. Not only is the vocabulary of schema.org/CreativeWork quite extensive, there are also a number of subtypes that can be used for specific creation mediums or types (e.g. schema.org/Book). However, one distinction to highlight is how an RRM Creation encompasses both the perceivable Manifestations and abstract Works (through CreationMode). Note that in the rest of the text, we use Creation as an entity type that encompasses both Works and Manifestations.

Transforming to JSON-LD, we get:

// A Work and its Manifestations in JSON-LD
// Note: We assume that the data will be put on an immutable ledger and so all links must point
//       "backwards"
{
    "@context": "http://coalaip.schema/",
    "@graph": [
        {
            "@id": "#creation",
            "@type": "Work",
            "name": "Lord of the Rings",
            "author": "<URI pointing to the author Party>"
        },
        {
            "@id": "#digitalManifestation",
            "@type": "Manifestation",
            "name": "The Fellowship of the Ring",
            "manifestationOf": "#creation",
            "digitalWork": "<URI pointing to file>",
            "fingerprints": [
                "Qmbs2DxMBraF3U8F7vLAarGmZaSFry3vVY5zytuN3BxwaY",
                "<multihash/fingerprint value>"
            ],
            "locationCreated": "<URI pointing to a Place>"
        },
        {
            "@id": "#physicalManifestation",
            "@type": "Manifestation",
            "name": "The Fellowship of the Ring",
            "manifestationOf": "#creation",
            "datePublished": "29-07-1954",
            "locationCreated": "<URI pointing to a Place>"
        }
    ]
}

A similar result can be achieved for IPLD, although split into multiple different schemata linked with hashes:

// A Work object in IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Work",
    "name": "Lord of the Rings",
    "author": { "/": "<hash pointing to the author Party>" }
}

// A digital Manifestation of the Work in IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Manifestation",
    "name": "The Fellowship of the Ring",
    "manifestationOf": { "/": "<hash pointing to the Work>" },
    "digitalWork": { "/": "<hash pointing to a file on e.g. IPFS>" },
    "fingerprints": [
        "Qmbs2DxMBraF3U8F7vLAarGmZaSFry3vVY5zytuN3BxwaY",
        "<multihash/fingerprint value>"
    ],
    "locationCreated": { "/": "<hash pointing to a Place>" }
}

// A physical Manifestation of the Work in IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Manifestation",
    "name": "The Fellowship of the Ring",
    "manifestationOf": { "/": "<hash pointing to the Work>" },
    "datePublished": "29-07-1954",
    "locationCreated": { "/": "<hash pointing to a Place>" }
}

Note that a distinction has been made between Works (typed as "coalaip.schema/Works"s) and Manifestations (typed as "coalaip.schema/Manifestation"s). Both physical and digital manifestations can be represented, with digital manifestations containing a link to an example of the work as well as possibly being associated with a set of fingerprints.

The Abstract Notion of Works

One can view a Work as the overarching creative concept that is brought to existence by a number of perceivable Manifestations. It is meant as an abstraction to connect a group of related Manifestations together. As such, we argue that empty Works–those not linked to from any Manifestations–do not make much sense and recommend implementations to register Works only with their initial Manifestations.

The RRM Right Entity

In comparison to all other RRM entity types, the Right is by far the most interconnected. A minimal set of required properties include:

  • RightType: Defines the type of Right (e.g. all uses, license, copy, play, stream, administration, an lcc:RightSet, etc.);
  • ToolType: Defines the type of medium that must be employed when exercising the Right (e.g. only watch on mobile phone or only use a brush to produce manifestations). ToolTypes are not consumed as part of exercising the Right;
  • MaterialType: Defines the type of material that may be employed when exercising the right (e.g. only use watercolour paint to produce manifestations). MaterialTypes are consumed during the exercising of a Right and become part of the result;
  • ValidContextType: Defines the type of context in which the Right may be exercised (e.g. in flight, public, commercial use, academic research, etc.);
  • IsExclusive: Indicates whether the Right is exclusive to the rightsholder (e.g. true or false);
  • PercentageShare: Defines the percentage share of the Right controlled (e.g. 51%, 100%, etc.);
  • NumberOfUses: Defines the number of uses permitted by the Right (e.g. 3, 5, unlimited uses, etc.);
  • ValidPeriod: Defines the period during which the Right is valid. (e.g. 2015-2016); and
  • Territory: Defines the Place where the Right may be exercised (e.g. North America).

Note: For the sake of simplicity, we ignore the HostCreationType and OutputCreationType.

In addition, a Right can have the following outgoing links to other entities:

  • Links to other Rights (0 - n; one-to-many): RelatedRight
  • Links to Partys (0 - n; one-to-many): RelatedParty
  • Links to Creations (0 - n; one-to-many): RelatedCreations
  • Links to Places (0 - n; one-to-many): RelatedPlace
  • Links to RightAssignments (0 - n; one-to-many): RelatedContext
  • Links to Assertions (0 - n; one-to-many): RelatedContext
  • Links to RightsConflicts (0 - n; one-to-many): RelatedContext

Note: The Context entity has been expanded to its non-Right subclasses: RightsAssignments, Assertions, and RightsConflicts.

Visualized, an RRM Right looks like:

Additional Types of Rights

The RRM specifies three special types of Rights intended for specific use cases:

  • lcc:SourceRight: A Right from which another Right is allowed by or created from;
  • lcc:SupersededRight: A Right to invalidate a referenced Right; and
  • lcc:RightSet: A collection of Rights bundled as a single Right.

We utilize lcc:SourceRights in our notion of Copyrights as well as our Right transformation, but, for now, we leave the other types out of the specification:

  • lcc:SupersededRight: Although representable, reversible rights complicate the ownership logic of an immutable ledger; and
  • lcc:RightSet: In the context of putting Rights onto a global distributed ledger, bundling multiple rights together presents a specific problem: most decentralized ledgers cannot guarantee, and especially synchronize, the concurrent transfer of multiple assets (in the future, this may be possible with cryptoconditions).

Proposed Transformation

Transforming the RRM Right entity poses some challenges. According to the RRM specification, a Right can:

  • Represent both copyright as well as licensing information; and
  • Be a lcc:SourceRight, lcc:SuperSeededRight, or lcc:RightSet.

For the purposes of storing Rights on decentralized ledgers, we ignore the requirements of the lcc:RightSet and model Rights as atomically transferrable containers of licensing information. To make a distinction between derived licensing information and a full copyright, we separately explore the semantics of copyright later. To the best of our knowledge, there are no existing RDF schemata for creating such containers, so we propose the following to satisfy the consolidated requirements of:

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "Right",
    "@id": "<URI pointing to this object>",
    "usages": "all|copy|play|stream|...",
    "territory": "<URI pointing to a Place>",
    "context": "inflight|inpublic|commercialuse...",
    "exclusive": true|false,
    "numberOfUses": "1, 2, 3, ...",
    "share": "1, 2, 3, ..., 100",
    "validFrom": {
        "@type": "Date",
        "@value": "2016-01-01"
    },
    "validTo": {
        "@type": "Date",
        "@value": "2017-01-01"
    },
    "source": "<URI pointing to a Copyright>",
    "license": "<URI pointing to a license on an immutable ledger>"
}

The Right can be seen as the link between a Manifestation and its licenses. To prevent undetected changes to these linked licenses—which are usually intended to be read by humans—the licenses would ideally be stored on an immutable ledger or content-addressed storage layer. With this in mind, the implementation in IPLD (on IPFS) is favoured:

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Right",
    "usages": "all|copy|play|stream|...",
    "territory": { "/": "<hash pointing to a Place>" },
    "context": "inflight|inpublic|commercialuse...",
    "exclusive": true|false,
    "numberOfUses": "1, 2, 3, ...",
    "share": "1, 2, 3, ..., 100",
    "validFrom": {
        "@type": "Date",
        "@value": "2016-01-01"
    },
    "validTo": {
        "@type": "Date",
        "@value": "2017-01-01"
    },
    "source": { "/": "<hash pointing to a Copyright>" },
    "license": { "/": "<hash pointing to a license>" }
}

In our transformation, it is important to highlight that every Right must include a source (or equivalent) property that links it to an enabling Copyright or parent Right. With use on an immutable ledger in mind, the source property implements support for lcc:SourceRights–albeit in a "backwards" relation in comparison to the RRM's definition–a Right containing a source property is the derivation while the pointed-to entity is the lcc:SourceRight.

Copyright Semantics

Although RRM Rights are capable of representing both full copyrights as well as derived licenses to Creations, we split these two concepts into different entities to better represent them within distributed ledgers. We base the structure of the Copyright entity on the Right entity's, but as only a subset of the Right's properties pertain to Copyrights (e.g. "territory", "validFrom", etc.), we do not require implementations to subtype Copyrights from Rights. However, semantically, and for the purposes of discussion, we treat Copyrights as a subtype of Rights. Similarly to Rights, we propose that Copyrights be stored on decentralized ledgers for maintaining ownership and provenance.

We propose:

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "Copyright",
    "rightsOf": "<URI pointing to a Creation (usually a Manifestation)>",
    "territory": "<URI pointing to a Place>",
    "validFrom": {
        "@type": "Date",
        "@value": "2016-01-01"
    },
    "validTo": {
        "@type": "Date",
        "@value": "2017-01-01"
    }
}

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Copyright",
    "rightsOf": { "/": "<hash pointing to a Creation (usually a Manifestation)>" },
    "territory": { "/": "<hash pointing to a Place>" },
    "validFrom": {
        "@type": "Date",
        "@value": "2016-01-01"
    },
    "validTo": {
        "@type": "Date",
        "@value": "2017-01-01"
    }
}

For implementations, we recommend that Copyrights be automatically registered with their Manifestations so as to immediately state the Manifestation's copyright holder and allow other Rights to be derived from the Copyright. Given that multiple Copyrights may be needed, e.g. for multiple regions, there is no limit to the number of Copyrights that can be attached to a given Manifestation (for potential conflicts, see Assertions and RightsConflicts.

The Notion of Ownership

Given that Rights and Copyrights are designed to be stored on decentralized ledgers, we propose to link these entities with their related rightsholding Partys by cryptographic ownership. Assuming the ledger natively supports cryptographic ownership of assets, this results in only the owners of a Right or Copyright on the ledger to be maintained as the rightsholders. Moreover, this means that only these owners are able to repurpose the Right by, for example, initiating a RightsAssignment to a another Party. Ledgers should be chosen so that all forms (e.g. transfers, loans, consignments, etc.) of these transactions (i.e. RRM RightsAssignments) can be stored in an ordered fashion to maintain each right's chain of provenance.

With RRM Rights modelled in such a fashion, any digital creator that wants to register and distribute the Rights of a Manifestation to interested Partys must:

  1. Register their Party identifier on a global registry;
  2. Register their Creation as a Work on a global registry and link it to their Party identifier;
  3. Register Manifestations to the Work on a global registry;
  4. Register a Copyright for the Manifestation on a global registry;
  5. Derive any number of Rights tailored to interested Partys from the Copyright and register them on a global registry; and
  6. Register RightAssignments to assign these Rights to interested Partys.

The above steps highlight how a Right is not only limited to registration; with the use of a ledger, Rights also contain properties of ownership and can be transferred from one Party to another via RightsAssignments. The owner of a Right or Copyright on the ledger is maintained to be the rightsholder.

However, there are a few edge cases to consider when licensing information is stored this way:

  • Specific licenses can imply an agreement between the issuer of the Right and the commons; to handle this intention to grant Rights to literally everyone, a special Party symbolizing the commons could be created to receive and hold such Rights. Following the assignment of this Right, other, arbitrary, transfers of Rights of the license to specific Partys must be disallowed. Finally, Partys must also be disallowed from attaching new Rights with licenses that conflict with the "commons license" to the Manifestation.
  • TODO: Maybe there are more edge cases like this. If so, enumerate and discuss/propose solutions.

It is important to note that with these ownership semantics for copyrights and licenses, the ownership of a Work or Manifestation is essentially meaningless: these entities simply contain information about a creative work and are used as pointers for Copyrights and Rights. As such, storing Works and Manifestations in ledgers is unnecessary and an immutable data store, e.g. IPFS, can be used instead if cross-protocol links are supported (i.e. multiaddr).

The RRM RightsAssignment Entity

According to the RRM, a RightsAssignment describes an event that results in the existence or non-existence of a Right (or Copyright). Depending on the type, a RightsAssignment may be linked from an assigning Party ("Assigner") to a receiving Party ("Assignee"). From the RRM, a RightsAssignment can have the following properties:

  • RightsAssignmentType: Defines the type of RightsAssignment; one of:
    • RightsLaw: Represents the creation of a Right by law (e.g. the US Copyright Act of 1976);
    • RightsPolicy: Represents the assignment of a Right from an authorized Party to another Party without requiring the latter's agreement (e.g. security level for user access of a computer system); or
    • RightsAgreement: Represents an agreement between two Partys regarding a Right (e.g. a license, publishing agreement, etc.).
  • RightsAssignmentStatus: Defines the status of the RightsAssignment; one of:
    • lcc:Offer: An open RightsAssignment proposed by a prospective Assigner;
    • lcc:Request: An open RightsAssignment proposed by a prospective Assignee; or
    • lcc:Executed: An executed assignment of rights.
  • RightsAssignmentTime: Defines the the at which the RightsAssignment was made.

The RRM RightsAssignment can have the following outgoing references:

  • Links to Partys (0 - n; one-to-many): RelatedParty
  • Links to Rights (0 - n; one-to-many): RelatedRight

Visualized, an RRM RightsAssignment looks like:

Proposed Transformation

Based on our expectation that Rights will be registered to immutable ledgers, we expect the following requirements to be met by every ledger capable of transferring Rights:

  • Assets are only transferrable if cryptographic key-pair signatures are used on the transaction level;
  • Asset transactions must be able to contain a JSON-serializable payload;
  • Assets' provenance chains must be easily comprehensible for any user;
  • Asset divisibility must be defined during registration;
  • Transactions must support IPLD as well as Crypto-Conditions;
  • Transfer transactions must support different modes, including:
    • Transfers from a group of individuals to a single individual (and vice-versa);
    • Transfers that are only claimable during a certain time span ("timelock conditions"); and
    • Transfers that are only claimable by an individual or group that knows a certain secret key ("hashlock conditions");

With these assumptions, we can model a minimally transformed RRM RightsAssignment on top of schema.org/TransferAction and include it as the payload of a ledger's transfer-transaction. Piggybacking on a transfer-transaction allows the rights transfer to automatically include information such as the current and new rightsholders, time of execution, and status of execution (valid or rejected by the ledger).

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "RightsAssignment",
    "contract": "<URI pointing to a contract on a ledger>"
}

and in IPLD:

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "RightsAssignment",
    "contract": { "/": "<hash pointing to a contract>" }
}

Although not required, we include the contract property to allow a RightsAssignment to more specifically frame the transferred rights (e.g. with additional clauses). A Party can only transfer the Rights they own, so a transfer of Rights will contain only the permissions that are available in the original Right or previous transfer-transactions.

The RRM Assertion Entity

Entities under the COALA IP ontology are registered by independent users, rather than trusted central authorities (such as rightsholders) or decentralized networks (such as the Bitcoin network) that are able to provide guarantees for the validity of the data. As the ontology may potentially be exposed to an open internet and its users, we must assume that some records will contain inaccurate or even fraudulent claims. To counteract this, the RRM recommends the implementation of an Assertion entity that evaluates the truthiness of claims made by participating Partys. These Assertions provide a healing mechanism that can be used by interpreters of the data to retrieve trustable results.

The RRM's minimum set of required properties include:

  • TruthValue: Indicates the "truthiness" of the claim; and
  • ValidPeriod: Defines the time period during which the claim is maintained (e.g from 01.01.2011 to 01.01.2015).

Additionally, an RRM Assertion can have the following outgoing references:

  • Links to Partys (0 - n; one-to-many): Asserter
  • Links to Creations (0 - n; one-to-many): SubjectOfAssertion
  • Links to Rightss (0 - n; one-to-many): SubjectOfAssertion
  • Links to RightsAssignments (0 - n; one-to-many): SubjectOfAssertion
  • Links to Assertions (0 - n; one-to-many): SubjectOfAssertion
  • Links to RightsConflicts (0 - n; one-to-many): SubjectOfAssertion

Note: Differing slightly from the RRM, we have added Creations as a possible SubjectOfAssertion. The Context entity has also been expanded into its subclasses: Rights, RightsAssignments, Assertions, and RightsConflicts.

Visualized, an RRM Assertion entity looks like:

Proposed Transformation

Our transformation proposes that assertions should be made directly on an entity itself rather than the single properties within an entity.

Think about the following scenario:

Andy Warhol decides to use the COALA IP protocol to register his work on a blockchain. He registers "32 Campbell's Soup Cans," one of his works, as a Work and attaches a poster as a Manifestation. He then assigns a Right to the poster, defining the licensing terms of purchase, by creating and attaching the Right to the Manifestation. Mistakenly, as Andy is not really good with computers—they were never really his type of medium—he also accidentally registers a Work of Edvard Munch's "The Scream" under his name.

Visually, this is what's been registered:

This creates an awkward situation: we've stored our ontology on a blockchain that supports IPLD and content-addressed storage, so, in contrast to a traditional SQL database, we can't correct the mistaken transactions by simply reverting them. The only action we can take is to append more information to the blockchain–we can validate the truthiness of specific statements by appending Assertions.

Assertions are applied towards entire entities and evaluate whether an asserting Party ("Asserter") agrees or disagrees with the claim made by the entity. Schema.org's ReviewAction provides a good base to work off of, albeit with less-than-ideal property names that don't map well to the RRM's definitions. We assume that "coala.schema" will alias some of these properties and get:

// In JSON-LD
{
    "@context": "http://coalaip.schema/",
    "@type": "Assertion",
    "asserter": "<URI pointing to a Party>",
    "assertionTruth": false,
    "assertionSubject": "<URI pointing to Work: The Scream>",
    "error": "author"
}

// and

{
    "@context": "http://coalaip.schema/",
    "@type": "Assertion",
    "asserter": "<URI pointing to a Party>",
    "assertionTruth": true,
    "assertionSubject": "<URI pointing to Work: 32 Campbell's Soup Cans>"
}

// In IPLD
{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Assertion",
    "asserter": { "/": "<hash pointing to a Party" },
    "assertionTruth": false,
    "assertionSubject": { "/": "<hash pointing to Work: The Scream>" },
    "error": "author"
}

// and

{
    "@context": { "/": "<hash pointing to coalaip.schema's context>" },
    "@type": "Assertion",
    "asserter": { "/": "<hash pointing to a Party" },
    "assertionTruth": true,
    "assertionSubject": { "/": "<hash pointing to Work: 32 Campbell's Soup Cans>" }
}

Note: On IPLD, you have the option of applying additional granularity to the Assertion by directly referring to an entity's property as the "assertionSubject". For example, if you wanted to assert that "The Scream"'s "author" property is incorrect, you could do so with

{
    ...
    "assertionTruth": "false",
    "assertionSubject": { "/": "/ipdb/<hash of work>/author" },
    "error": "...",
    ...
}

Although this doesn't directly apply the Assertion against the entire Work entity, we still have a link to the Work in the IPLD hash and can associate this Assertion to it.

We end up with the following:

As a recommendation, we add that using IPLD with Assertions is ideal, as it enforces the immutability of an asserted object (as well as the assertion itself); with IPLD, objects cannot be silently changed after-the-fact as any changes will cause their IPLD hashes to also change.

The RRM RightsConflict Entity

TODO:

  • See other introductory sections of LCC entities. Use same structure to describe the entity

Proposed Transformation

TODO:

  • See other introductory sections of LCC entities. Use same structure to do the transformation

Generating Verifiable Claims

As the COALA IP ontology may be potentially exposed to the public, users must have a mechanism of proving their actions to others. To provide this with cryptographic signatures is a two part challenge: we not only need to ensure that user identities can be associated with cryptographic identities (see requirements of Partys, but also that any submitted claim can be signed by those cryptographic identities. Although no optimal solution currently exists for associating identities, a number of pre-existing schemata are available for signing RDF-compatible data:

Building on top of these two facets is the Verifiable Claims Architecture and its associated data model (currently using the Linked Data Signatures schema) that is being standardized by the Verifiable Claims Task Force. In the future, data from COALA IP could be used to generate, or even be created, in the format proposed.

User Extensions

TODO:

  • Explain how users could extend the given entities with their own properties

Future

This document has outlined general technologies and guidelines on using the LCC Framework as the basis of an RDF ontology for managing digital rights with immutable data stores. As the goal is to implement an open standard for rights management, a number of efforts are to follow:

  • Define a production-ready RDF-compatible schema based on the proposed transformations (see schema/)
  • Complete a reference implementation using the RDF-compatible schema (see implementations)
  • Include or build open source communities around COALA IP
  • Identify a standards committee to work with
  • Reformat the proposed transformations and their resulting schemata to that of a standard proposal

Thank you for reading!

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