=Paper=
{{Paper
|id=Vol-2548/paper-10
|storemode=property
|title=A Decentralized Provenance Network for Linked Open Data
|pdfUrl=https://ceur-ws.org/Vol-2548/paper-10.pdf
|volume=Vol-2548
|authors=Fabian Kirstein
}}
==A Decentralized Provenance Network for Linked Open Data==
https://ceur-ws.org/Vol-2548/paper-10.pdf
A Decentralized Provenance Network
for Linked Open Data
Fabian Kirstein[0000−0002−9064−2546]
Weizenbaum Institute for the Networked Society, Berlin, Germany
Fraunhofer FOKUS, Berlin, Germany
fabian.kirstein@fokus.fraunhofer.de
Abstract. With the growing availability of Linked Open Data (LOD)
and the consequential generation of derived and aggregated data, the
need for trustworthy, reproducible and accessible provenance informa-
tion has increased. Yet, no consistent mechanism has been established
to manage provenance data of LOD on a global dataset-level. Decen-
tralized networks and peer-to-peer mechanisms have made their revival
in the last years with blockchain and similar distributed ledger tech-
nologies. We propose a novel approach to track and store provenance
information for LOD on a dataset-level by sharing an immutable, com-
mon state between data providers. The basic architecture will not disrupt
existing methodologies and standards for publishing LOD, but will be
transparently integrated into existing ecosystems as an additional layer
to foster broad acceptance. We will investigate the application of emerg-
ing blockchain technologies and established Linked Data specifications
for building this decentralized anchor of truth. We are actively involved
in the design and implementation of LOD and Open Data platforms and
will evaluate our approach in real-world scenarios regarding feasibility,
governance, scalability and usability.
Keywords: Provenance · Distributed Ledger · Blockchain · Open Data.
1 Problem Statement
The Linked Open Data (LOD) movement is a global phenomenon, driven by the
fact that additional value is generated by interlinking structured data. LOD is
Linked Data, which can be distributed by everyone anytime without any restric-
tions. An active community has evolved around the publication and generation
of LOD. A popular publisher is WikiData, which freely offers comprehensive
data, completely serialized in the Resource Description Framework (RDF). [25]
Other issuers release only metadata as LOD, referencing and describing in detail
the actual data inventory, which usually consists of a variety of data formats.
Our work focuses on the latter approach, which is typically applied by Open
Data portals, aggregating public data, published by public administrations or
research organizations. Well-known examples are OpenAIRE [12] for research
data and the European Data Portal (EDP) [6] for data of public authorities in
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
2 Fabian Kirstein
Europe. In fact, many more publishers of LOD exist: The Linked Open Data
Cloud1 lists more than 1300 datasets.
The widespread distribution and availability of Open Data leads to the creation
and publication of derivative or edited datasets. Data from different sources and
origins is copied, aggregated, converted and/or enriched. Furthermore, claims
and conclusions are inferred from (combinations of) these datasets. The trace-
ability and repeatability of such data and its processing is critical for maintaining
trust and accountability. A central foundation for that is the presence of expres-
sive and valid provenance information for each dataset in an LOD processing
chain. No unified mechanism is established to record and track the
provenance of LOD on a dataset-level. The very nature of LOD causes bar-
riers in establishing appropriate measures. The intrinsic reason for this claim is:
LOD ecosystems constitute highly distributed and decentralized systems, where
data is acquired and aggregated across distinct organizational and technical lev-
els. An illustrating example for this is the harvesting process of LOD published
by public services. Typically, harvesting is conducted in a bottom-up form, where
municipal data providers publish data independently. This is followed by an ag-
gregation towards the next higher organizational level and so forth, e.g., towards
data portals of cities, federal states, etc. [9] Users and processors may fetch the
data at any point in the hierarchy. A similar process is applied for scientific
publications, where data is published by individual research organizations and
aggregated in central hubs for scientific publications [12].
This methodology and the design of LOD leads to major challenges with respect
to tracking the provenance of a single dataset: Firstly, there is no established ap-
proach for uniquely and persistently identifying a distinct dataset. Although the
Linked Data principles require the use of Uniform Resource Identifiers (URIs) as
unique identifiers, they can be easily reassigned and the DNS itself is transient.
Especially in the domain of research data, the application of Digital Object Iden-
tifiers (DOIs) as a centralized workaround is established. Secondly, provenance
information is often not set, fragmentary or not correctly forwarded in an ac-
quisition and processing chain. Expressive and rich specifications for encoding
provenance are available, foremost the W3C PROV [13]. Still, its successful adop-
tion requires correct handling of it by each participant. Additionally, provenance
information represented as plain metadata allows tampering and manipulation
by malicious partners.
These limitations could be solved by establishing and agreeing on a central man-
agement system for provenance and identifier information. However, the very
character of LOD is decentralization and sovereignty, involving multiple stake-
holders and heterogeneous infrastructures. This environment makes the success-
ful implementation of a centralized system infeasible. This leads to the essential
hypotheses of this dissertation: An additional, immutable and decentral-
ized network can help to overcome current drawbacks in LOD prove-
nance tracking and incentivize its broad application. The recent devel-
opments in blockchain systems and related peer-to-peer (P2P) technologies will
1
https://www.lod-cloud.net
A Decentralized Provenance Network for Linked Open Data 3
be an important foundation for implementing such a network.
This approach can accomplish both: The management of provenance informa-
tion through a homogeneous system and the protection of the independence of
the data providers. This will support the fact that from an organizational point
of view, LOD forms a highly decentralized system, which requires a single point
of truth in order to ensure integrity and trust.
2 Relevancy
Due to the ongoing worldwide digitization, data has become a most valid asset
and the basis of many value-added processes and business models. Although our
work focuses on LOD, this is true for both, public domain data and proprietary
data. The relevance of trustworthy information about the provenance and lin-
eage of data will continue to increase. Simmhan et al. write "With a growing
number of datasets available in the public domain beyond the confines of a single
organization, it has become increasingly important to determine the veracity and
quality of these datasets." [20] As of today, more than 2600 Open Data portals
exist in the world. [16] Although they do not all serve LOD, it shows a clear
tendency of increasing significance in the domain. This data is used, processed,
aggregated and re-published by multiple user groups, e.g., journalists, scientists,
businesses, citizens, etc. These groups will benefit highly from improved prove-
nance information, since it will enable reproducibility and increase trust. This
"proof of origin" will improve the overall quality of the data for the data con-
sumers. This is especially true for the research community, where traceability is
an ethical and legal requirement. With regard to the Open Science movement
and the increasing publication of raw scientific data, provenance information
will become essential. Within the LOD community, efforts for harmonization
are intrinsic and serve the idea of a global interlinked knowledge graph. Well-
known examples are the Linked Open Vocabularies project [24] and the Linked
Data Platform specification [27]. Integrating a trustable, decentralized prove-
nance mechanism can strengthen Linked Data as core layer for the growing data
economy, not limited to LOD, and broaden its adoption. After all, the Seman-
tic Web Stack is missing a trust layer, where provenance will be one essential
building block.
3 Related Work
A lot of research was conducted in the relevant fields of our work. Our approach
crosses established research of provenance for LOD with blockchain and dis-
tributed ledger technologies, which has been already examined to some degree.
In general, data provenance has been widely studied with respect to its use,
subject, representation, storing and dissemination and a variety of software so-
lutions have been developed for managing provenance. These approaches mainly
focus on local data, typically generated by a particular scientific domain, e.g.,
Physics, Earth Sciences, etc. [20] An extensive literature review and overview
4 Fabian Kirstein
of provenance on the Web, including the Semantic Web, was published by Luc
Moreau. [14]
3.1 Provenance for Linked (Open) Data
Early work on provenance for Linked Data focused on modelling RDF vocabu-
laries and ontologies, which can be used to describe the provenance of published
RDF data and query it respectively. [7] Since then, the W3C has developed
PROV, a set of specifications and data models for publishing provenance in-
formation. It is widely established as interchange format for provenance data.
The standard is not limited to Linked Data, but offers multiple serializations,
including an OWL ontology. [13] Extensive research was conducted for effec-
tively attaching provenance information to RDF. Common approaches include
the concept of annotated RDF [23], where each triple is associated with meta-
data. Wylot et al. introduced a high-performance triplestore, allowing to store
provenance-enriched RDF and executing queries, including close-grained prove-
nance information. [31] Little work exists on making provenance information
centrally and globally available. ProvStore is such a central service, allowing to
store and publish provenance information of data, based on the PROV standard.
[8] No approach exists in managing provenance information in a globally shared
state.
3.2 Linked Data and Distributed Ledgers
First research exists on the connection of distributed ledgers/blockchain tech-
nologies and Linked Data/Semantic Web, spanning multiple aspects. English et
al. endorse the notion of improving the persistent identification of RDF resources
with blockchain. [5] Third et al. investigate several stages of extension of storing
Linked Data in a distributed ledger, from a simple verification layer to a pure
storage layer. [21] The InterPlanetary Linked Data (IPLD) project follows a dis-
ruptive approach, by completely lifting the data management to a decentralized
network. IPLD offers a custom data structure, which is globally addressable and
supports interlinking. [17] Sicilia et al. propose an immutable, decentralized stor-
age for raw LOD based on the P2P System Interplanetary File System (IPFS)
to overcome issues of availability. [19] An opposed approach makes decentral-
ized data on the Ethereum blockchain available via Semantic Web technology,
by mapping the blockchain data structures to Linked Data. [22] Applying a dis-
tributed ledger as an additional layer for provenance tracking in the domain of
LOD was not proposed yet.
3.3 Blockchain and Beyond
Blockchain and related technologies are vivid topics of research, where most
work focuses on privacy and security aspects. [33] The most defining and rele-
vant work is the P2P cash system Bitcoin. [15] However, many different areas
A Decentralized Provenance Network for Linked Open Data 5
of application have evolved. A general indicator for applying a blockchain is the
presence of a decentralized environment, with multiple (untrusted) participants
and the need for transparency. [32] Some is related to our proposed approach,
but set in different domains with other emphasises. Rohrer et al. propose a
blockchain-based system for decentralized and transparent storing of citation
and reference provenance for journalistic articles on the Web. [18] Liang et al.
implemented an additional provenance layer based on a blockchain network for
the open source cloud solution ownCloud, which tracks every file transaction
with only little overhead. [11] Other relevant work includes the vibrant ecosystem
of open source blockchain projects. Ethereum is a multi-purpose, decentralized
and transaction-based state machine. It includes smart contract functionality
and allows to build private or public blockchain systems. [30] Hyperledger Fab-
ric enables the creation of permissioned blockchains based on general-purpose
programming languages and custom consensus mechanisms. [2] Finally, a lot
of up-to-date research is conducted regarding consensus protocols for enduring
Byzantine failures and ensuring a unique and correct state of a network. Cachin
et al. give a comprehensive overview on the recent developments. [3]
4 Research Questions
Based on the problem statement, the related work and the recent impact of
distributed ledger technologies, new approaches for addressing provenance of
LOD will emerge. Our work will focus on an additional, decentralized layer,
accompanying existing solutions for publishing LOD. Therefore, we formulate
the following research questions, where RQ1 represents the overall question.
RQ1: Can we manage the provision, management and traceability of prove-
nance information for LOD datasets by applying an additional, decentralized
layer?
RQ2: How can we persistently identify and represent provenance information
of LOD in a globally unique way?
RQ3: What consensus and governance mechanisms can be applied to ensure
the integrity of such a system?
RQ4: Which paradigms and tools are suitable to implement the proposed
approach, considering expectations in flexibility, scalability and usability?
5 Hypotheses
The following hypotheses relate to the aforesaid research questions. H1 depicts
the overall hypothesis of the proposed thesis.
H1: A decentralized network, which holds a globally shared state for all data
providers will improve the tracking and storing of provenance information of
LOD in comparison to locally published provenance data.
6 Fabian Kirstein
H2: An immutable and transparent global database will improve the persis-
tent and unique identification and management of provenance information over
established transient approaches and enables a long-term preservation.
H3: An authority-based governance model and voting-based consensus mech-
anism will ensure a consistent state of the network and prevent misuse.
H4: Blockchain and related technologies can serve as a technical foundation
for the proposed decentralized network.
6 Preliminary Results
In this section, we present first results and experiences from previous and on-
going work in the LOD and distributed ledger domains.
Our work on the EDP [9] has given us valuable insights into the process of LOD
acquisition, processing and re-publishing. We collect Linked Data from more
than 70 data publishers, in total more than 800.000 datasets. The data pub-
lishers themselves gather the data from lower organizational levels. It has been
proven extremely difficult to uniquely identify a dataset in this ecosystem and to
track its provenance. The required metadata simply does not exist or is incom-
plete. In addition, close communication with the data publisher has shown that
there is an aspiration for autonomy and sovereignty. Rapid changes in existing
methodologies and technologies are not endorsed. We came to the conclusion that
an additional and simple to integrate solution has higher chances for adoption.
In our project Policy Compass2 , we developed a platform for mixing, extending,
interpreting and visualizing Open Data. A use case is the assessment of outcome
and impact of governmental policies through analyzing public available data.
[10] We integrated several data sources, e.g. the EDP, Eurostat3 and DBpedia4 .
The project has shown us a clear need for traceability and reproducibility, es-
pecially in the domain of policy evaluation and derived recommended actions.
We implemented basic traceability support, by linking datasets to its original
source and indicating the local provenance in derived assets. However, due to
the heterogeneity of the data sources, the implementation of a more general and
global provenance mechanism has proven unfeasible.
We have conducted several practical case studies with blockchain and distributed
ledger technologies to classify their opportunities and challenges. Based on the
public Ethereum blockchain we have implemented a decentralized digital iden-
tity management system. It allows human users to acquire a persistent iden-
tifier and link public properties, like date of birth, to it. The work is based
on Ethereum smart contracts and the Decentralized Identifiers (DIDs) speci-
fication. [29] Furthermore, we used the permissioned blockchain infrastructure
Hyperledger Fabric [2] for implementing a track and trace system for physical
assets. It demonstrates how a decentralized network can enable data sharing and
2
https://policycompass.eu
3
https://ec.europa.eu/eurostat
4
https://wiki.dbpedia.org
A Decentralized Provenance Network for Linked Open Data 7
Fig. 1. An exemplary high-level process including the provenance network
cooperation beyond organizational borders. We acquired fundamental knowledge
about governance, scalability and representing custom data in such a decentral-
ized environment.
7 Approach
The overall approach is divided into four steps. Steps 1 and 2 refer to RQ2/H2,
step 3 to RQ3/H3 and step 4 to RQ4/H4. The overall outcome relates to
RQ1/H1.
LOD and the Semantic Web follow a decentralized methodology, still some as-
pects require a central authority to be most effective and accurate. An indicator
for that are various approaches to harmonize LOD by some kind of central
stewardship, e.g., Linked Open Vocabularies (LOV) or GeoNames.org.5 Our ap-
proach is the establishment of a decentralized network, which holds a globally
shared state for all data providers and acts as an anchor of truth about prove-
nance information. It is a single point of access for this global information, which
simplifies management and traceability. Each participant of the ecosystem will
act as distributed database node. The central premise is not to disrupt exist-
ing methodologies and standards, but to transparently integrate into existing
ecosystems. Fig. 1 illustrates an exemplary high-level process for LOD aggre-
gation, processing and use, including the decentralized provenance network. An
LOD provider holds metadata and data and publishes a reference of them to the
network. (here illustrated as hash values and a persistent identifier) An LOD ag-
gregator copies only the metadata and extends the original reference accordingly.
(indicated as sameAs) An LOD processor creates new data based on the original
data and adds a new reference to the network, including a derivedFrom indica-
tion. Finally, a data publisher creates a visualization of the data, linking it to the
reference in the network, allowing a clear tracking of the provenance of the data.
5
https://www.geonames.org
8 Fabian Kirstein
1. Formal definition of a dataset: LOD constitutes a set of triples (aka state-
ments), forming a multigraph. Our work does not base upon this smallest entity
of LOD. Typically, a distinct subset of triples forms a self-contained information
unit, restricted by pre-defined boundaries. Concepts like named graphs reflect
this approach. [4] In the first step we will derive a formal definition of what can
be considered a distinct dataset. This includes a URI schema, graph constraints
and publication guidelines. We contemplate to base it on well-established stan-
dards and best practices. The Data Catalogue Vocabulary (DCAT) [26] will act
as a principle recommendation for describing the metadata. The Linked Data
Platform (LDP) specification [27] offers a reference for publishing the datasets
on the Web. A validation mechanism will be based on the Shapes Constraint
Language (SHACL) [28]. The result of this step will be a practical tool set to
publish valid datasets and the groundwork for the following steps.
2. Definition of the identifier and provenance data models: Published datasets
from a provider can be considered local, since they are initially confined to the
providers network and are addressed via a transient URL. The proposed decen-
tralized network forms a global context, since it is shared by many data providers
and leverages all available datasets. In this step, we will essentially model and
define the mapping from a local to a global context. This includes two aspects:
Firstly, the global representation of a persistent identifier and its linking to the
actual local dataset will be modelled. It is important here to consider changes
and relocations of the local identifier and to provide the means to perform a
mapping of the identifiers multi-directionally. Existing decentralized identifier
concepts will act as guidance here. Secondly, the actual global provenance data
model will be designed. Based on the global identifiers, we will provide a com-
pact and basic model to represent the provenance of a dataset. It will utilize a
subset of the methodology and ontology of W3C PROV and its core concepts
Entity, Agent and Activity. [13] The outcome of this will be a comprehensive
specification of the data models, alongside a proof-of-concept implementation.
3. Design of the decentralized network methodology: In this step, we will de-
sign the fundamental architecture of the decentralized provenance network, es-
sentially regarding agent management, governance model, security aspects and
consensus mechanisms. Essentially, a change in the globally shared state needs
corporative validation and confirmation of the network. Only thereby the cor-
rectness and integrity can be guaranteed. We think that an authority-based gov-
ernance model and voting-based consensus mechanism will ensure a consistent
state of the network. Every LOD data provider will have a verifiable identity, au-
thorizing them as a valid member of the network. This authority will be granted
by a proof of ownership, e.g., of a local LOD endpoint. A state change of the
network can be issued by each participant, but requires approval by the major-
ity of the other authorized participants. Hence, a voting is performed, ensuring
that not a single participant can publish defective or wrong data. Eventually,
the transparency of the decentralized network will offer an additional layer of
A Decentralized Provenance Network for Linked Open Data 9
governance. It enables an open and immediate quality assessment and increases
the barrier for publishing faulty information.
We will evaluate these assumptions against real-world LOD ecosystems and pub-
lication schemes. The outcome will lead to accurate guidelines about who will
be allowed to add what data when in the shared store, formed by the network.
Especially, the on-boarding process in this decentralized environment needs to
be investigated. These assumptions will be evaluated with practical artifacts,
either based on existing technologies or individually implemented.
4. Implementation and evaluation of the provenance network: In the final step,
we will implement the network and apply it in a production environment. With
blockchain and similar distributed ledger technologies, decentralized networks
and peer-to-peer mechanisms have made their revival in the last years. A variety
of tools offer improved possibilities for sharing a common state and reaching
consensus in a decentralized environment. Multiple implementations exist for
building customized decentralized networks with desired characteristics: from
public, permissionless to private, permissioned networks, including custom se-
curity and consensus protocols. These recent developments can operate as a
technical foundation for the proposed decentralized network. Yet, your work will
not be limited to blockchain and distributed ledger technologies, but will also
consider traditional peer-to-peer mechanisms and implementations.
The work here will be mainly conducted on two levels. (1) Providing the means
for actually creating the network. This includes a deployable node and a proper
on-boarding process to become a participant in the network. The setup of a
node is envisioned to be as straight-forward as possible. Container technologies,
like Docker, might be suitable approaches here. [1] We will put an emphasis
on scalability and performance and take into account typical data volumes and
throughputs of LOD systems. (2) Create an approach and implementation for
effectively interacting with the network. A straight-forward and easy integra-
tion into existing LOD publication concepts is desired here. The most native
method here constitutes SPARQL. We think that the least disruptive integra-
tion approach would be a proxy for a standard SPARQL endpoint, allowing
users to annotate publication queries with provenance information. The proxy
will extract these annotations, process them and trigger a change of state in the
network, when necessary. It has to be noted that the operators of (1) and (2)
can be disjoint, so not every data provider has to provide a node and vice versa.
The outcome of this step will be a fully working prototype.
8 Evaluation Plan
We plan to evaluate our hypotheses with the following four approaches.
1. Working prototype: Based on a proof-of-concept system, we will test and eval-
uate the fundamental functionality of our approach. Test data will be generated
in real-world volumes. Synthetic, but representative stakeholders and actors will
10 Fabian Kirstein
use the network. We will use the results and findings for improving our approach
in an iterative manner.
2. Application in a production environment: We are actively involved in the
implementation of LOD portals, like the EDP. Hence, we will apply our solution
in a production environment and monitor its qualities and possible adoption. A
cooperation with external stakeholders, like original data publishers and data
users are requested.
3. Practical usefulness: We will measure and qualify multiple characteristics
of the synthetic and the production system. This includes overall performance,
throughput, maximum load and scalability. Since no system for comparison ex-
its, we will evaluate the findings on established expectations for central solutions,
especially for provenance tracking.
4. User studies: The rate of adoption of such a system, is highly dependent on
user acceptance. We will conduct user studies within two different user groups:
(1) Data providers will be asked to join the network by integrating it into their
systems. (2) Data consumers will use the provided information to express prove-
nance statements about given datasets. It is planned to conduct the user studies
twice, with a working prototype and a production version.
9 Reflections
To the best of our knowledge, the proposed research questions and the proposed
approach is a novelty. There does not exist an established solution for a tamper-
proof and globally accessible ledger for provenance information about LOD. The
recent developments and successful real-world applications of blockchain and
similar networks have demonstrated the success and acceptance of a globally
shared state-machine. However, we think that blockchain still has a long way to
go and are aware of its current limitations. A complete migration from estab-
lished centralized systems and architectures, especially in LOD, is improbable.
An additional, decentralized layer, respecting established mechanisms and stan-
dards will have a much better chance for adoption. We are actively involved in
many production LOD, Open Data and Open Science projects. Among others,
this includes the development of the EDP and the design and installation of a
research data platform for the Weizenbaum Institute for the Networked Society.
This allows us to work closely with many relevant stakeholders and consider their
needs and requirements, e.g., the data providers, users or system administrators.
10 Acknowledgements
This work has been funded by the Federal Ministry of Education and Research
of Germany (BMBF) under grant no. 16DII111 ("Deutsches Internet-Institut")
and is supervised by Prof. Manfred Hauswirth.
A Decentralized Provenance Network for Linked Open Data 11
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