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COALA Intellectual Property Specification

Contributors to this document, in alphabetical order:

We acknowledge the excellent work leading to this document from COALA and the COALA IP working group, including (in alphabetical order): Juan Benet, Constance Choi, Primavera de Filippi, Dor Konforty, Trent McConaghy, Simon de la Rouviere, Diana Stern.

TL;DR! I DON'T HAVE TIME FOR ALL OF THIS!

Want a summary? We've got you covered with presentations:

Don't be shy! Make sure to give us your questions, suggestions or feedback.

Thank you!

READ THIS FIRST

This document is a work in progress. Some sections contain the keyword "TODO" and a description of what is required. Feel free to research an unfinished area and write the section yourself.

If your contribution contains information from external sources, please link to those sources.

If your contribution relies on a field that wasn't previously explained, please provide an overview of the field to give other readers the necessary background.

This document has a soft limit of 100 characters-per-line. Respect the limit! For links, only the descriptor counts. The URI doesn't count.

Make sure to follow the existing styles for formatting as closely as possible.

As an overall guideline for contributions to this document document:

  • Think practical.
  • Think in technologies.
  • Don't reinvent the wheel. Use what's already out there and give proper attribution.
  • Write as if you had to implement next week.

General TODOs:

  • Improve consistency in use of defined terms. Synonyms for technical terms should be replaced with the standard term throughout.
  • Before releasing this document to the public, write an introductory section explaining what COALA is, what its general goals are, why this document matters, what is left to do, and so on...
  • Sometimes this document references internally to other sections ("as seen in the above section", ...). Using relative links, we should point to the sections we're writing about

Table of Contents

  • TODO:
    • link to the individual headlines in a tree structure

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, and lawyers and middlemen extract 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 based on their data profiles. It doesn't have to be this way.

The Coalition Of Automated Legal Applications — Intellectual Property Group (COALA IP) group was formed to address these problems. COALA IP is working to design and implement a free and open specification for representing and licensing intellectual property. COALA IP's goal is to establish open, free, and easy-to-use ways to record attribution information and other metadata about works, assign or license rights, mediate disputes, and authenticate claims by others. We believe there should be a global standard at the data level, without the need for centralized control.

This document details the COALA IP approach to representing intellectual property on distributed ledgers (or blockchains). It's an effort to transform the implementation-agnostic Rights Reference Model (RRM) of the Linked Content Coalition (LCC) into a free and open standard. It outlines technologies that could be leveraged for the implementation and structure of a specification for everyone involved: creators, rightsholders, distributors, consumers, developers, and so on. The protocol will be technology-specific, but ledger-agnostic.

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

  1. Building a community to define a minimally-viable set of data for the description of intellectual property rights and licensing agreements;
  2. Authoring a guide—this document—to provide an overview of the field and the need for a technical specification to represent intellectual property rights on distributed ledgers; and
  3. Defining a free and open messaging and communication protocol for intellectual property rights and licensing transactions.

Introduction

This section provides context for the COALA Intellectual Property (COALA IP) specification. It describes the technological concepts used to model a generic, extensible protocol for managing digital rights. It is meant to give the reader an overview of the concepts; for a more comprehensive understanding, we encourage the reader to explore the reference material throughout the document.

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 are:

The LCC's Ten Targets

The LCC's goal is to enable the widest possible access to accurate rights information and the ability to automate the licensing and assignment of rights, whether for commercial or free use. The LCC released the "LCC Ten Targets for the Rights Data Network," as a general guide toward achieving the following goals:

  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 have a URI to persistently resolve them within the internet;
  5. Links between identifiers are platform agnostic and non-proprietary
  6. Metadata is platform agnostic or interoperable, and schema should have mappings to translate between schema that have been authorized by relevant parties;
  7. The provenance of Rights has to be made explicit;
  8. Any participant has the ability to make standardized, machine-readable statements about rightholdings in Creations;
  9. Conflicts in rights declarations should be automatically identifiable; and
  10. Registered Creations have links to 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 this specification. The Entity Model is a meta-model used by the LCC to model their ontology, the LCC Rights Reference Model.

The LCC Entity Model (LCC EM) is a generic data model the LCC uses to define more specific data models, like the LCC Rights Reference Model (LCC RRM). The 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: Links the Entity to another Entity (e.g. "Andy Warhol" ---isCreator---> "32 Campbell's Soup Cans")

These attributes are each represented as 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 so more complex data models like the LCC RRM can be built on top.

Sources:

The LCC Rights Reference Model

The LCC Rights Reference Model (LCC RRM) is a formal framework for the representation of intellectual property rights. The LCC RRM specification describes an abstract logical data model built on top of the LCC Entity Model, and is 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 says he has copyright in Untitled Instagram Portrait", or "Sky Ferreira says she has copyright in Untitled Instagram Portrait")
  • RightsConflict: A statement of disagreement over a Right (e.g. "Sky Ferreira and Richard Prince both claim copyright in Untitled Instagram Portrait")

Note: For the sake of simplicity, the Context type was left out of the above list. It is defined only as a parent/categorizing class of Right, RightsAgreement, Assertion, and RightsConflict. It 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 in linked documents. The web is mostly used by humans, publishing and accessing information in human-readable formats, like a webpage. In theory, machines are capable of understanding this kind of information, but in practice machines find this difficult and are inefficient at doing it. For example, a webpage with a table listing the populations of a number of countries is easy for a human to understand, but even if the first column is called "The Name of a Country", it is difficult for a machine to understand and to deduce new information from it. It's even harder for machines to reason from this kind of information if context is not provided.

The semantic web is about publishing information in data schemata that hold semantic meaning for both humans and machines. This allows humans to publish human-readable information in a way that machines can understand too. Doing so would likely prove to be of great value in advancing the web. One of the key building blocks of the semantic web, the Resource Description Framework, is described in the following section.

Sources:

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

The Resource Description Framework (RDF)

Resource Description Framework is a framework for describing entities on the web. It uses the Universal Resource Identifier (URI), a generalization of the Universal Resource Location (URL), to address resources. This makes RDF exceptionally interoperable and extensible.

RDF's core data structure is a graph-based data model that uses sets of triplets to construct subsets of the graph. Each triplet consists of a subject, predicate, and an object. In its smallest form, a set containing a single triplet is already an RDF graph. Visualized, a simple RDF graph could look like this:

Each node of the graph is usually represented as a URI pointing to a resource, providing further details about its 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 RDF 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). ccREL is a schema provided by Creative Commons that allows defining context for machines on how to interpret licensing information for documents on the web. ccREL itself is implemented using RDF Schema, which is a vocabulary for describing properties and classes of RDF resources. By using the Web Ontology Language (OWL), concepts from other RDF schemata can be included in a domain-specific RDF schema, creating a global ontology of semantically structured data.

ccREL is just one example of a context-providing schema built on top of RDF. RDF implementations vary, especially in terms of used data structures. Embedded RDF in HTML pages and RDF/XML syntax are two of the more popular implementations of RDF, albeit with relatively heavy syntax and learning curves. In 2014, with RDF 1.1 coming up, a new RDF-compatible, JSON-based data structure was accepted by the W3C: JSON-LD. It fits the semantic web concept of linked data into Javascript Object Notation (JSON), which makes it much more approachable than comparable implementations. We plan to port the LCC RRM specification to RDF using JSON-LD, so we will explore its main features in the next section.

Sources:

Linked Data

JSON Linked Data

JSON-Linked Data (JSON-LD) is a data structure that merges the concepts of the Resource Description Framework with JSON. Using the concept of a context, it allows users to link a JSON object's property to the corresponding RDF schemata in an ontology.

Assume we have the following set of data:

{
    "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. For a machine that 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 into 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 would result in:

{
    "@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.

Right now, each application or service has its own model for representing users. For example, one site might use birthday as the key for the user's birthday, while others use day_of_birth or birthDay. The sites may even use different formats for the value of the key, with some using YYYY-MM-DD and another using DD-MM-YYYY. Custom logic would have to be written to handle mapping the different keys to each other, but also to convert their values to a standard format even though they all have the same semantic meaning. They all describe when a person was born.

JSON-LD solves these problems by introducing a context to each data model allowing for:

  1. A unified mapping of keys by complying to base schemata
  2. Value-validation on a primitive data types level

Going back to the Andy Warhol example, we need to explain how JSON-LD magically maps our self-defined keys (givenName, familyName and birthDate) to the properties of schema.org's Person. If you look at schema.org's Person definition, you'll see we didn't choose random key names. Names were already part of the definition. In this case, a JSON-LD parser can automatically map and execute validation against these properties by using the schema definition.

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

  1. Notice @context contains http://schema.org/Person
  2. GET http://schema.org/Person
  3. For each of the user-defined keys, check if they map to any keys provided in the schema
    1. If this is the case, traverse the schema until a leaf node (the JSON-LD specification calls this an identifying blank node) is found
    2. "Expand" the data, replacing keys' names with URIs to their more granular schema definitions

Continuing with this example, here is what our previously defined set of data would look like after expansion:

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

We end up with a much more verbose form of our data. In the JSON-LD specification it's called expanded form, as the original object's been expanded with a @context. The original object's form, still with an @context, is defined by the specification as compacted form.

The JSON-LD parser assumes we've defined the correctly named keys for a Person and uses http://schema.org/Person to replace each of our properties with their more detailed schema definition URIs. The result is an automatically mapped set of data that uses an already available schema. Each key of a given value now points to a left node on a schema ontology. Leaf nodes are only allowed to define the most basic types, such as string, boolean, integer, and so on, so the parser can easily traverse the document and validate each occurrence of @value.

Final Thoughts

This example is just the tip of the iceberg. JSON-LD has tremendous power. It can be used for aliasing, self-referencing, built-in types, indexing, and more.

The rest of this document will rely heavily on JSON-LD, so we encourage you to learn more about it by reviewing the Sources section 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 vocabulary is defined as an ontology, connecting different concepts using links. It can be used with different encodings, including RDFa, Microdata, and JSON-LD.

Available Schemas

Schema.org includes the following schemata that are closely related to LCC RRM's Entity types. Potentially, these could be used later to help define the COALA IP specification:

-A full list of all core schema.org schemata can be found here.

In summary:

A full list of all core schema.org schemata can be found here.

Extensibility of schema.org

Although some of the Entity types do not yet exist in schema.org (specifically Rights, RightsAssignment and RightsConflict), the schema.org schemata are easily extensible. We can create our own schemata to fit the needs of LCC. Schema.org even encourages others to subclass their core schemata into what it calls "hosted" and "external" extensions. There are three basic types of schemata on schema.org:

  • Core: A basic vocabulary for describing the kind of entities most common web applications need.
  • Hosted: Subclassed models 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. Hosted schemata should be application-agnostic.
  • External: Subclassed models from Core or Hosted which have an application-specific namespace (e.g. http://schema.coala.global). External schemata may be application-specific.

Applied to the context of the COALA IP specification, application-agnostic schemata (including all of LCC RRM) would ideally become a hosted extension. Application-specific schemata, data models that are specific for a specific application or service, would become external schemata. 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 system agnostic and need to be authorized by participating consortiums.
  • Rule 6: Metadata is system agnostic and its schema has to be authorized by participating parties or consortiums.

Sources:

Interplanetary Linked Data

This section describes the functionality of Interplanetary Linked Data (IPLD) and its use in working with immutable data stores and Linked Data.

Motivation for IPLD

IPLD is an attempt to put Linked Data on distributed ledgers using hashes for linking, a technique referred to as "Merkle links".

Let's go back to our Warhol example:

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

In addition, we have 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 to tell that Andy Warhol is the creator of "32 Campbell's Soup Cans." We could use JSON-LD to create a link between the objects by making both of the objects resolvable on the internet. We could do this by adding @ids to the objects' bodies, and an author property to the creation that points to a resolvable location of the person object.

The problem is we have to trust the hosts that make these objects resolvable. Hosts might return the correct objects at first, but that could change. Since there is no way for resolving actors to check the integrity of the object they're requesting, a host could return arbitrary data and the actor wouldn't know. In addition, internal linking within objects or internal linking from URIs is challenging using linked data protocols like JSON-LD.

The rest of this section explores the features of IPLD that promise to solve these problems.

IPLD by Example

The following sections give a brief overview of IPLD's functionality. More information is available in the IPLD specification draft.

Creation of Linked Objects

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

  1. Serialize the person's object to a canonical form of Concise Binary Object Representation (CBOR):

    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'

    For this demonstration, we use py-ipld, an existing Python library, to handle IPLD specifics and data transformations. In this case, ipld.marshal is used to serialize the person object using a CBOR reference implementation. The result is a byte array.

  2. Hash the serialized byte array using multihash and encode the hash to base58

    In [4]: ipld.multihash(serialized_person)
Out[4]: 'QmRinxtytQFizqBbcRfJ3i1ts617W8AA8xt53DsPGTfisC'

    Multihash is a protocol for differentiating outputs from various well-established cryptographic hash functions. It adds a hexadecimal prefix to each hash generated indicate the hash function used. This lets users identify the hash functions in the future in case of upgrades, and allows for multiple hash functions to coexist within and across applications.

  3. Now that we have derived an IPLD from the person object, we can link it to the creation as its author:

    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 a person by using the person's hash value, thereby creating a "Merkle link". Generally, Merkle links can be schematized like this:

    Property = {
    ...
    [<String>]: <MerkleLink>
}

MerkleLink = {
    "/": <String: multihash value>
}

  4. Finally, to make this creation object resolvable, we repeat the first two steps. We serialize the creation object to a canonical form of CBOR:

    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"

    Note this is a special case, with the Merkle link contained in creation replaced by an unassigned CBOR tag (258) to make the link more easily retrievable on deserialization.

  5. Hash the resulting serialized byte array using multihash and encode the hash to base58:

    In [7]: ipld.multihash(serialized_creation)
Out[7]: 'QmfMLNLyJZgvSPkNMvsJspRby2oqP6hWZ8Nd2PvKLhudmK'
Retrieval of Linked Objects

To further explore IPLD, let's assume we've put these objects into a data store. We'll use IPFS since its identifiers are compatible with the hashes we created previously.

We can use paths of Merkle links (Merkle paths) to resolve any object within IPFS using its hash value, and also further de-reference any of the object's connecting edges by following its Merkle links. 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, with the actual object, making traversing a Merkle link feel similar to regular property access in objects. To link across network addresses, we can use multiaddr, which allows the construction of resource paths to reach across protocols. Doing so would allow an IPLD object to maintain resolvable links even if its Merkle links point to separate ledgers (e.g. IPFS, BigchainDB, Bitcoin, etc).

Evaluation of IPLD

In summary, IPLD is a promising new technology, 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 (compare to URL).
    • Enables cross-ledger/database resolvability of data (multiaddr and merkle-paths).
    • Unifies object identifiers through a canonicalized hashing strategy.
    • Imposes immutability by using a merkle-dag data structure.
    • Future-proofs underlying concepts (multi-x).
    • Enables wide compatibility, even down to the UNIX file system path.
    • Relies on lightweight protocol drafts and implementations.
    • Deserializes to a multitude of other data serialization formats (YAML, JSON, XML, etc).
  • Caveats:
    • Non-standardized protocols (multi-x).
      • Overlaps with other protocols that are being standardized.
      • Breaks with exisiting and well-established protocols (e.g. URI vs. multiaddr).
    • Does not comply with existing linked data ontologies due to immutability.
    • Opinionated CBOR serialization.

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. This section highlights the limitations imposed on JSON-LD by IPLD.

Self-identifying JSON-LD Objects

JSON-LD objects can maintain a self-identifying link using the @id property. This allows the object to directly express its location. The same is impossible for IPLD objects. Since IPLD objects are supposed to only be retrieved by the corresponding hash of the their data, the hash itself cannot be part of the object as it would be a very difficult to solve cryptographic puzzle. The amount of processing required would be incredible, rendering the identification of objects extremely inefficient. Instead, we prevent JSON-LD objects with IPLD links from self-identifying themselves using an @id property. This is not usually a problem as objects can also identify themselves through content addressing.

Sources:

The Web of Trust

Fingerprinting

Determining the originality and provenance of a physical object is challenging, but there are almost always subtle differences between an original physical object and copies. Digital files can be copied perfectly, down to the bit. Furthermore, it is difficult for a computer to determine that two files actually represent the same photograph or song if the files are different sizes or other subtle modifications have been made, while a human would have no difficulty making the 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 vector 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.
  • TODO: List more libraries
    • Find popular ones that do fingerprinting for all kinds of media types

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 could allow the storage and tracking of all information about the use of a work in an arbitrarily complex graph. Copies, remixes, mash-ups, and modified versions of the work could be identified automatically as paths in the graph. Traversing these paths would reveal the original instance of the work, possibly identifying the creator and providing opportunities for compensation.

As rights information becomes more transparent and users can easily license the rights they want to obtain, 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.
    • Same formalities as in all the sections before apply.

COALA IP: Remodeling the LCC RRM with Linked Data

In this section we describe how the LCC RRM can be modeled using JSON-LD, IPLD, and schema.org. We will go over each model description given in the LCC Rights Reference Model document and discuss how the respective model can be translated into Linked Data.

What Linked Data Gives Us Out of the Box

As a building block of RRM, the LCC first defines a generic, linkable Entity Model whose entities can be combined to create an extendable data model for intellectual property. However, by using an RDF-based data structure, we can skip the transformation of these basic entities as RDF already provides us with a base data structure for linking entities.

General Approach

The section describes how to get from a LCC RRM model to a RDF-compatible JSON-LD/IPLD model. As discussed, the "LCC: Entity Model" defines a generic model as a base for the Rights Reference Model. The document describes how to implement a fully extensible data model using a multitude of linked entities. Using an RDF-based data structure means that defining a base data structure for linking entities is not necessary—this is what RDF is all about.

To redefine the LCC's Rights Reference Model, we propose the following:

  • Identify RDF schemata that map to entities defined in the LCC RRM specification.
    • If appropriate RDF schemata are not available:
      • Compose new RDF types from multiple RDF schemata; and
      • Define new RDF schemata.
  • Define how entities are identified and resolved.
  • Resolve mismatches between the LCC RRM terminology and RDF schemata.

A slight speed bump in the transformation process is ensuring support for links between entities. The RRM defines the existance of links in a generic manner, as one-to-many (i.e. 0 - n) links. 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 required by the RRM. However, we can overcome this limitation by extending the base JSON-LD schemata, or its underlying RDF implementation. Extensions could be hosted by schema.org as a hosted extension, or by others as extended extensions.

The LCC 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; is one of:
    • lcc:LocalizablePlace: A Place in the physical universe that can be located by spatial coordinates
    • lcc:VirtualPlace: A non-localizable Place at which a resource may be located at

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

Compared to schema.org's definition of a Place, the LCC RRM Place can describe both a physical and a virtual Place. In this specification, we need to separate the two concepts explicitly to avoid confusion later in the transformation process. Neither a URI nor a IPLD Merkle link is able to represent a physical location, which is why in the context of this specification, these will be links pointing to resources, while the LCC Place model will be used only to refer to a physical place.

For reference:

  • LLC RRM Place or Place will be used to describe a localizable Place, meaning a physical Place in the universe that can be described using spatial coordinates.
  • Universal Resource Identifier or IPLD Merkle link will be used to describe a virtual place where a resource can be found.

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

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

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Place>" },
    "geo": {
        "@type": { "/": "<hash pointing to RDF-Schema of GeoCoordinates>" },
        "latitude": "40.75",
        "longitude": "73.98"
    },
    "name": "Empire State Building"
}

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

The LCC Party Entity

The LCC recommends that a Party should be able to represent any of the following classes of parties:

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

RRM Parties must have the following properties:

  • PartyType: Defines if the Party is an individual or a group of individuals;
  • 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 Parties (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 will describe the transformation of a RRM Party into a JSON-LD/IPLD Person and Organization very literally, so as to provide reasoning for the steps taken in the transformation. This will only be the case for this Entity, as the rationale for transforming later Entity types will be similar.

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

// 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's nothing technically wrong with the above, you may notice on a close inspection of schema.org/Person that the schema 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 defined on schema.org/Person. This gets us:

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

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of 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 Party identifier (@id). As an @id value is only required to be a resolvable URI or IPLD merkle-link, a JSON-LD parser would validate this without complaining; however, @id would ideally point to the location of the data itself to show the JSON-LD parser where it could be resolved within the internet. Unfortunately, Wikipedia doesn't support this, so that https://en.wikipedia.org/wiki/Andy_Warhol doesn't return the required data, which is why we'll have to look for another solution.

To start off with, lets look at some limitations and requirements derived from the RRM and JSON-LD / IPLD:

  • 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 have at least one persistent unique public identifier that is both human- and machine-readable.
    • If a Party has 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 (encoded in base58).
      • Multihash allows different hash functions to interoperate and stay upgradeable.
  • And finally, our own requirements to allow for any linked entity data to be put on public ledgers (e.g. blockchains or registries):
    • Elements of the Party's identifier can represent 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.

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

  • Issue an identity that can be resolved using JSON-LD (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 the 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
{
    "@type": "http://coalaip.schema/Identity",
    "@id": "<URI pointing to this object>",
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

On IPLD, we remove the @id property. Not only are we restricted from using self-referencing links in IPLD, but such links are unnecessary, as any object is able to identify itself by its own hash. Thus, we get:

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Identity>" },
    "givenName": "Andy",
    "familyName": "Warhol",
    "birthDate": "1928-08-06",
    "deathDate": "1987-02-22"
}

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

  • Multiple Parties sharing a relationship (e.g. Party A and Party B created Creation C);
  • Parties providing Places as part of their metadata (e.g. home location, contact place, or billing address); or
  • Multiple Parties 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 we wanted to define relations that schema.org hadn't already provided, we could also extend schema.org/Person with our own RDF schema.

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, the Entity type could look like this as an schema.org Organization.

// In JSON-LD
{
    "@type": "http://schema.org/Organization",
    "@id": "http://identityservice.com/organizations/w3c",
    "name": "World Wide Web Consortium",
    "founder": {
        "@type": "http://linkedcontentcoalition.com/Identity",
        "@id": "https://identityservice.com/identities/12bS2BTF4j8kkmNqoyQRwzKy76EXQWRVWJ",
    },
    "member": [
        {
            "@type": "http://linkedcontentcoalition.com/Identity",
            "@id": "https://identityservice.com/identities/152xhUAJBGEht9Jwerv1omFV82xaRcyzHH",
        },
        {
            "@type": "http://linkedcontentcoalition.com/Identity",
            "@id": "https://identityservice.com/identities/1Je5tHHkHcs1ioLZmiBFSuyiXdwd76xf4D",
        },
        {
            "@type": "http://linkedcontentcoalition.com/Identity",
            "@id": "https://identityservice.com/identities/1QDtDjNgBx6242VakTTkFMn5HmkibzrsR8",
        }
    ]
}
  • TODO: Also define how the object would look like in IPLD.
  • TODO: This needs a lot of specing 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?
Allowing Parties to Sign Metadata

As we envision future identity registries built on top of public ledgers, we need to ensure that users are able to include a cryptographic identity with any registered identities, allowing them to sign any submitted metadata. Luckily, the Friend of a Friend Project has already thought about this and provide the Web of Trust RDF ontology for signing RDF documents with public-key cryptography. Integrating this ontology into our identity model, we could get something like:

  • TODO:
    • Give an code example how WOT could look like in an immutable ledger.
    • Make sure that the immutability is not violated, the WOT ontology as of now only work with mutability.

The LCC Creation Entity

An RRM Creation model describes something directly or indirectly made by human beings. According to the specification, it has a single required property:

  • CreationMode: Describes the mode of 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 Parties (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 RRM 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 to define specifics about a creation (e.g. schema.org/Book). However, one distinction to highlight is how an RRM Creation has two CreationModes: one for perceivable Creations (called Manifestations) and one for abstract Creations (called Works). Note that in the rest of the text, we use Creation to refer to the entity type which 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"
{
    "@graph": [
        {
            "@id": "#creation",
            "@type": "http://coalaip.schema/Work",
            "name": "Lord of the Rings",
            "author": "<URI pointing to the author Person>"
        },
        {
            "@id": "#digitalManifestation",
            "@type": "http://coalaip.schema/Manifestation",
            "name": "The Fellowship of the Ring",
            "manifestationOfWork": "#creation",
            "digitalWork": "<URI pointing to file>",
            "fingerprints": [
                "Qmbs2DxMBraF3U8F7vLAarGmZaSFry3vVY5zytuN3BxwaY",
                "<multihash/fingerprint value>"
            ],
            "locationCreated": "<URI pointing to a Place>"
        },
        {
            "@id": "#physicalManifestation",
            "@type": "http://coalaip.schema/Manifestation",
            "name": "The Fellowship of the Ring",
            "manifestationOfWork": "#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
{
    "@type": { "/": "<hash pointing to RDF-Schema of Work>" },
    "name": "Lord of the Rings",
    "author": { "/": "<hash pointing to the author Person>" }
}

// A digital Manifestation of the Work in IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Manifestation (can be any subtype of CreativeWork)>" },
    "name": "The Fellowship of the Ring",
    "manifestationOfWork": { "/": "<hash pointing to the Work>" },
    "digitalWork": { "/": "<hash pointing to a file on e.g. IPFS>" },
    "fingerprints": [
        "Qmbs2DxMBraF3U8F7vLAarGmZaSFry3vVY5zytuN3BxwaY",
        "<multihash/fingerprint value>"
    ],
    "locationCreated": { "/": "<URI pointing to a Place>" }
}

// A physical Manifestation of the Work in IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Manifestation>" },
    "name": "The Fellowship of the Ring",
    "manifestationOfWork": { "/": "<hash pointing to the Work>" },
    "datePublished": "29-07-1954",
    "locationCreated": { "/": "<URI pointing to a Place>" }
}

Note that a distinction has been made between works (typed as Works) and manifestations (typed as Manifestations). Both physical and digital manifestations can be represented, with digital manifestations including a set of fingerprints as well as a link pointing to an example of the work. In the future, we plan to subtype both a Work and a Manifestation type from schema.org's CreativeWork to allow their properties to be easily customizable.

The Copyright Transfer

  • TODO:
    • When a Creation is being transferred, expresses a Copyright transfer between parties
    • Outline how this is working, what implications it has and so on

The LCC 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, 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 as part of exercising the 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).
  • Territory: Defines the Place where the Right is may be exercised (e.g. North America).

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 Parties (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.

Visualized, an RRM Right looks like:

Additional Types of Rights

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

  • SourceRight: A Right from which another Right is derived
  • SuperSededRight: A Right to invalidate a referenced Right
  • RightSet: A collection of Rights bundled as a single Right

For now, we've decided to leave these special types out of the specificiation:

  • SourceRight and SuperSededRight: Although both can be easily represented with an ontology, they would greatly complicate the ownership logic of an immutable ledger.
  • RightSet: In the context of putting Rights onto a global registry, this is specifically a problem: most decentralized ledgers cannot guarantee, and especially synchronize, the concurrent transfer of multiple assets.
    • TODO: Tim: I talked to Dimi about this, and we were trying to figure this out with cryptoconditions, but it seems that at this stage it is not possible.
The Notion of Ownership

As RRM Rights are specific to the RRM Party they're provided for, any digital creator that wants to distribute a Manifestation's Rights to a multitude of interested Parties must take the following steps:

  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 any number of Rights tailored to interested Parties on a global registry; and
  5. Register RightAssignments to assign these Rights to interested Parties.

This highlights that Rights are not strictly limited to only registrations. Rights contain properties of ownership and can be transferred from one Party to another via RightsAssignments.

Manifestations are not limited to a single Right. Parties are able to attach as many Rights as necessary to a Manifestation. There are a few edge cases to consider when licensing information is stored:

  • 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 Persons or must be disallowed. Finally, Parties 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.

Proposed Transformation

Transforming the RRM Right Entity poses some challenges. According to the RRM specification, an RRM Right can:

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

In order for Rights to be atomically transferrable units, we ignore the latter requirement and focus on modelling Rights to be transferrable containers of specific licensing information. To the best of our knowledge there is not an appropriate RDF schema creates such containers, so we propose the following schema that satisfies the consolidated requirements of:

// In JSON-LD
{
    "@type": "http://coalaip.schema/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": "http://schema.org/Date" },
    "validTo": { "@type": "http://schema.org/Date" },
    "manifestation": "<URI pointing to the Manifestation object>",
    "license": "<URI pointing to a license on an immutable ledger>"
}

RRM Rights are just links between Manifestations and licenses. Licenses are usually intended to be read by humans, so the license should be stored on a technology that prevents changes to the license. This could be an immutable ledger or blockchain, or be linked by Content-Addressing. With this in mind, an implementation in IPLD/IPFS is favored:

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of 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": { "/": "<hash pointing to RDF-Schema of Date" },
    "validTo": { "/": "<hash pointing to RDF-Schema of Date" },
    "manifestation": { "/": "<hash pointing to the a Manifestation>" },
    "license": { "/": "<hash pointing to the license>" }
}

RRM Rights can be linked to Parties through cryptographic ownership. Only the individuals or organizations with access to a private key corresponding to a Right-transaction's public key are able to repurpose the Right by, for example, initiating a RightsAssignment to a third Party. Ownership transactions (i.e. RRM RightsAssignments) of every form (e.g. transfers, loans consignments, etc.) must be stored in an ordered fashion to preserve a valid chain of provenance for each right.

The LCC RightsAssignment Entity

According to the RRM specification, an RRM RightsAssignment describes an event that results in the existence or non-existence of a Right. 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. It can be 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 Parties regarding a Right (e.g. a license, publishing agreement, etc.).
  • RightsAssignmentStatus: Defines the status of the RightsAssignment. It can be 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.

The RRM RightsAssignment has the following outgoing references:

  • Links to RRM Parties (0 - n; one-to-many): RelatedParty; and
  • Links to RRM Rights (0 - n; one-to-many): RelatedRight.

Visualized, an RRM RightsAssignment looks like:

Proposed Transformation

Existing schemata for transferring assets could provide a source for transformations, but because of our unique requirements we do not use those schemata. We expect RightsAssignments to be registered on immutable ledgers that can already handle asset transfers. COALA IP has chosen to use both IPLD and the Interledger protocol in the hopes of establishing a metadata and licensing ontology that can span multiple ledgers and immutable data stores. We assume the following requirements will be met by every COALA IP-compatible ledger:

  • Assets must only be transferrable if cryptographic key-pair signatures are used on the transaction level;
  • Transactions must be able to define a JSON-serializable payload;
  • Assets' provenance chains must be easily comprehensible by any user;
  • The Divisibility of Assets must be defined during registration;
  • Transactions must support IPLD as well as ILP's Crypto-Conditions specification;
  • 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);
    • TODO: Are there more modes?
  • TODO: Are there more requirements COALA IP asks from a ledger?

With this assumption, we can model a minimally transformed RRM RightsAssignment to be part of the payload of a ledger-specific transfer-transaction, and automatically include links to related Parties and information about the RightAssignment's status:

// In JSON-LD
{
    "@type": "http://coalaip.schema/Transfer(Payload?)",
    "contract": "<URI pointing to a contract on a ledger>"
}

and in IPLD:

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Transfer(Payload?)>" },
    "contract": { "/": "<hash pointing to a contract>" }
}

Although not required, we include the contract property in this schema to frame the rights that are available to be transferred. A Party is not able to transfer more Rights than they have themselves, so a transfer of Rights can only contain permissions that are a subset of the Rights contained in the original creation of the Right or previous transfer-transaction.

The LCC Assertion Entity

Assets registered under the COALA IP ontology are registered by independent users, not by a trusted central authority (like a rightsholder) or a decentralized network (like the Bitcoin network) that can guarantee the validity of the data. We must assume that some records based on the COALA IP ontology will contain inaccurate or even fraudulent statements made by users. To counteract this, the LCC RRM recommends the implementation of an RRM Assertion Entity that evaluates claims made about the truth or falsehood of statements from participating Parties within the ontology.

The LCC's minimum set of required properties includes:

  • TruthValue: Indicates the level of trust or "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 Parties (0 - n; one-to-many): Asserter;
  • Links to RightsAssignments (0 - n; one-to-many): SubjectOfAssertion;
  • Links to Assertions (0 - n; one-to-many): SubjectOfAssertion; and
  • Links to RightsConflicts (0 - n; one-to-many): SubjectOfAssertion.

Visualized, an RRM Assertion Entity looks like:

Proposed Transformation

Since the ontology will potentially be exposed to an open internet and its users, an Assertion model in the ontology is necessary. It provides a healing mechanism interpreters of the data can use to retrieve a statistical truth. COALA IP proposes that assertions should not be made on actual models, but rather on a model's attributes and links.

Think about the following scenario:

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

Visually, this is what we'd end up with:

This creates an awkward situation. We've stored our ontology on a blockchain supporting IPLD and content-addressed storage. In contrast to a traditional SQL database, it is impossible to revert the transactions. We can only append to a blockchain. The solution is to append an Assertion validating specific statements that are true.

Instead of falsifying the existence of the Work "The Scream", the solution recommended by the LCC RRM, COALA IP suggests making an Assertion about "The Scream"'s Author property. With IPLD's Merkle-path feature, we are able to achieve exactly that by defining an Assertion object:

// In IPLD
{
    "@type": { "/": "<hash pointing to RDF-Schema of Assertion>" },
    "truth": "false",
    "asserter": { "/": "<hash pointing to a Party>" },
    "subject": {
        "/": "<IPLD hash pointing to Work: The Scream's author property>"
        // e.g. /ipdb/<hash of work>/author
    }
}

// and

{
    "@type": { "/": "<hash pointing to RDF-Schema of Assertion>" },
    "truth": "true",
    "asserter": { "/": "<hash pointing to a Party>" },
    "subject": {
        "/": "<IPLD hash pointing to Work: 32 Campbell's Soup Cans's author property>"
    }
}

We end up with the following:

As changing any of the objects values of key would provoke a change in the object's IPLD hash, and since changing data is not possible, we could also simply point the assertion to the object itself. However, we'd probably lose valuable metadata and it would be difficult to find out why an object was flagged by an asserter.

The LCC RightsConflict Entity

TODO: - See other introductory sections of LCC models. Use same structure to describe the model

Proposed Transformation

TODO: - See other introductory sections of LCC models. Use same structure to do the transformation

Future

This document outlined general guidelines on using the LCC Framework to define an RDF ontology for managing digital rights on top of immutable data stores. As the goal is to implement an open standard for rights management, there are a number of events that are to follow; they are outlined here in sequential order:

  • Define a working RDF schema based on this specification
  • Include or build open source communities around it
  • Using the RDF schema, implement this specification
  • Identify a standards commite to send this to
  • Take the RDF schema, take the proposed transformations here and put them in a format of a standard proposal

Thanks for reading!