=Paper=
{{Paper
|id=Vol-3759/paper12
|storemode=property
|title=PCFWebUI: Data-driven WebUI for holistic decarbonization based on PCF-Tracking
|pdfUrl=https://ceur-ws.org/Vol-3759/paper12.pdf
|volume=Vol-3759
|authors=Ajay Kumar,Marius Naumann,Kevin Henne,Mohamed Ahmed
Sherif
|dblpUrl=https://dblp.org/rec/conf/i-semantics/KumarNHS24
}}
==PCFWebUI: Data-driven WebUI for holistic decarbonization based on PCF-Tracking==
https://ceur-ws.org/Vol-3759/paper12.pdf
PCFWebUI: Data-driven WebUI for holistic
decarbonization based on PCF-Tracking⋆
Ajay Kumar1 , Marius Naumann2 , Kevin Henne2 and Mohamed Ahmed Sherif1
1
Paderborn University, Data Science Group, Pohlweg 51, D-33098 Paderborn, Germany
2
Paderborn University, Department of Energy System Technologies, Warburger Straße 100, D-33098 Paderborn, Germany
Abstract
The pursuit of corporate greenhoue gas neutrality has become increasingly critical due to heightened sus-
tainability expectations, rising energy and CO2e costs, and stricter regulatory requirements. Key drivers,
such as the mandated reduction of greenhouse gas emissions by 65% by 2030 compared to 1990 levels and
the goal of achieving climate neutrality by 2045, necessitate immediate action toward decarbonization.
In this paper, we introduce PcfWebUI, a data-driven tool developed to support companies in their decar-
bonization journey. PcfWebUI is built on real company data integrated into a knowledge graph, enabling
efficient tracking and management of product carbon footprints (PCF), facilitating strategic planning
and accurate monitoring to help companies meet stringent climate targets and progress toward climate
neutrality. A demo of our system is publicly available at https://climatebowl.demo.dice-research.org/.
Keywords
Knowledge Graphs, PCF Tracking, Energy Efficiency
1. Introduction
Achieving greenhouse gas (GHG) neutrality poses a complex challenge for companies, driven
by political pressures, stakeholder demands, and rising energy costs. Essential drivers such as
the mandatory reduction of GHG emissions by 65% by 2030 relative to 1990 and the attainment
of net zero emissions by 2045 underscore the need for companies to embark on the path to
decarbonization promptly [1]. The allocation of GHG emissions to specific sources and the
identification of suitable measures are complex due to the intricate interactions within the
production systems. Current digital approaches exhibit significant gaps, particularly in the
comprehensive aggregation and assessment of GHG emissions. Furthermore, they fall short
in sufficiently developing reduction measures across the entire value chain. Addressing these
challenges requires a holistic and digital approach. The foundational step towards reducing
GHG emissions is achieving transparency in emissions across both specific sites and the entire
SEMANTICS24: 20th International Conference on Semantic Systems, September 17-19, 2024,Amsterdam
⋆
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*
Corresponding author.
†
These authors contributed equally.
$ ajayk@campus.uni-paderborn.de (A. Kumar); marius.naumann@upb.de (M. Naumann);
khenne2@mscould.uni-paderborn.de (K. Henne); mohamed.sherif@uni-paderborn.de (M. A. Sherif)
https://dice-research.org/AjayKumar (A. Kumar); https://dice-research.org/MohamedAhmedSherif (M. A. Sherif)
0009-0009-2400-1984 (M. Naumann); 0000-0002-9927-2203 (M. A. Sherif)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
value network. This transparency is starting point for the development of decarbonization
measures.
In this paper, we present PcfWebUI1 Based on real companies’ data integrated into knowledge
graph (KG), PcfWebUI enables efficient tracking and management of the Product Carbon
Footprints (PCF), helping companies to identify potentials to reduce GHG emission as well
as derive and assess specific measures. The system’s data-driven approach ensures accurate
monitoring and strategic planning, supporting companies in meeting stringent climate targets
and advancing toward GHG neutrality. PcfWebUI aims to simplify the process of identifying
and implementing energy efficiency (EE) measures. This is the focus of our collaborative project
Climate bOWL2 .
2. PCF-Tracking in context of industrial decarbonization
The holistic decarbonization of corporate activities can be divided into the three phases: target
definition, carbon accounting and action planning [2]. Defining reduction targets and translating
them into a reduction pathway is the foundation of any decarbonisation strategy. It is necessary
to create transparency about the company’s product-specific greenhouse gas emissions through
carbon accounting. The general methodical procedure is defined in the Greenhouse Gas Protocol
(GHGP) or standard DIN EN ISO 14064, the product-specific accounting is specified in standard
DIN EN ISO 14067 [3]. The accounting of all input and output flows for the relevant process
modules of a product is recorded in a life cycle inventory and then subjected to an impact assess-
ment in order to quantify the GHG potential measured in GHG equivalents [4]. By analyzing the
PCF, it becomes clear which process modules in the life cycle inventory have the greatest GHG
potential. The aggregation of process modules according to criteria such as scope categories or
life cycle phases makes it possible to evaluate the influence of individual or aggregated process
modules on the overall PCF. This analysis is important because it defines the starting point for
the development of decarbonization measures by identifying the emission-intensive process
modules. In the third phase of action planning, measures for GHG reduction are derived for the
identified drivers of the PCF. In principle, decarbonization efforts can be strategically imple-
mented following the principles of avoidance, reduction, replacing and offsetting [5]. There is
a need to automate the individual steps of PCF tracking and the development of measures in
order to ensure a holistic approach and accelerate industrial decarbonization [2]. The Climate
bOWL research project is therefore investigating the development of a digital support system
that automates the PCF accounting and analysis as well as the derivation of reduction measures
based on the methodological framework described.
3. Climate bOWL Knowledge Graph
The foundation of PcfWebUI’s robust functionality lies in its use of real companies’ data from
the Climate bOWL project, integrated into knowledge graph (KG). For generating our KG, we
1
Demo: https://climatebowl.demo.dice-research.org. Please be aware that for data protection purposes, our public
demo exclusively utilizes synthetic data. This ensures that no real company data is used or exposed.
2
https://dice-research.org/ClimatebOWL
Company Product Transport :hasEmissionsfactor THGEmissions
:hasProduct
:hasProcess
:hasEmissionsfactor
:hasEmissionsfactor
Material
:hasDocumentation
Process
:hasCategory
:hasCategory
:hasDataQualityAssessment
Documentation
:hasOutput
:hasInput
:hasReferenceFlow
Energy
:hasAnotherTimesampReferenceFlow
:hasAllocation
:hasDatavalidation
Flow :hasCategory
Allocation DataValidation ReferenceFlow DataQualityAssessment
Figure 1: The Climate Bowl Ontology (CLBO)
deployed Python scripts to convert data from Excel files into the KG triples. Our KG conversion
scripts are available from the project Github3 . The resulted triples is then hosted using Apache
Jena4 . To facilitate advanced querying, we also provided a SPARQL endpoint to our KG, allowing
users to perform complex queries and extract more specific information.
The Climate Bowl Ontology (CLBO), see Figure 1, is designed to facilitate the aggregation,
evaluation, and prioritization of GHG emission reduction measures throughout the value chain
in industrial settings. CLBO defines key concepts and their relationships relevant to industrial
GHG emission reduction. Key entities include companies, products, processes, flows, and
documentation standards. Properties describe the relationships between these entities, enabling
a structured approach to tracking and analyzing GHG emissions and identifying potential
reduction measures. For more details see the climatebowl ontology online resource5 .
4. PcfWebUI
We introduce PcfWebUI, a data-driven tool developed to support companies in their decar-
bonization journey. The system emphasizes improving material and energy efficiency as the
first step, followed by substituting energy sources and compensating for residual emissions.
PcfWebUI enables efficient tracking and management of PCF facilitating strategic planning
and accurate monitoring to help companies meet stringent climate targets and progress toward
climate neutrality. The key components of PcfWebUI are:
1. Query Component. The query component is designed to allow users to efficiently search
and retrieve specific information related to their PCF data. This component includes a
3
https://github.com/dice-group/ClimateBowl-KGConverter
4
https://jena.apache.org/
5
http://w3id.org/dice-research/climatebowl/ontology
field for SPARQL queries that utilizes our integrated KG to get detailed data for a product.
We built the query component using React6 for the front-end and Apache-Jena for the
back-end. The query component provides instantaneous feedback, displaying results as
users refine their queries.
2. PCF Tracking Component. The PCF tracking component enables users to monitor and
manage PCF comprehensively. This component presents a table with different parameters
for a single product, where the data for this table comes from the KG using the SPARQL
query in the query component. As shown in Figure 2, the Flow column ("fluss" in
German), there is a drop-down feature that allows users to choose for different materials
or energy sources. The Flow column includes a searchable drop-down that retrieves data
from our KG, allowing users to find materials or energy sources quickly. This component
dynamically reflects changes in emission factors in real-time, indicated by a green arrow
if emissions decrease and a red arrow if emissions increase.
3. Analytics Component. The analytics component of PcfWebUI responsible for analyzing
PCF data and generating insights. This component uses the updated data from the PCF
Tracking table, including all user updates, to display various analytical graphs. One of
the key graphs is the life cycle phases graph, where emission data is divided into different
life-cycle phases of the product and compares old and new emissions (See an example in
the lower part of Figure 2). Another important chart is the scope graph that shows data
grouped by scopes, providing a view of emissions according to different scope categories.
5. Conclusions and Future Work
Corporate climate neutrality is imperative due to strict regulations, rising energy and CO2e costs,
and increased sustainability expectations. PcfWebUI is a pivotal tool, enabling efficient tracking
and management of product carbon footprints with a data-driven approach. By integrating real
company data into a KG, PcfWebUI enhances material and energy efficiency, energy source
substitution, and residual emissions compensation. Despite challenges in data availability, secure
exchange, and PCF tracking complexity, PcfWebUI offers a robust foundation for companies to
meet decarbonization targets and achieve GHG neutrality.
In future work, we will enhance PcfWebUI by developing advanced features for EE bench-
marking, measure derivation, and prioritization to guide companies in decarbonization. We
will also integrate a recommendation system for energy reduction and decarbonization based
on PCF and energy efficiency benchmarking data. Finally, We will integrate our novel SPARQL
query generation approach into PcfWebUI for a more user-friendly experience [6].
Acknowledgments. This work has been supported by the Ministry for Economic Affairs,
Innovation, Digitalisation and Energy of North Rhine-Westphalia (MWIDE NRW) within the
project Climate bOWL under the grant no 005-2111-0020, and by the German Research Foun-
dation (DFG) within the project INGRID under the grant no NG 105/7-3. This work has been
supported within the project "WHALE" (LFN 1-04) funded under the Lamarr Fellow Network
programme by the Ministry of Culture and Science of North Rhine-Westphalia (MKW NRW).
6
https://react.dev/
Figure 2: PCF-tracking UI overview
References
[1] European Commission, European climate law, 2021.
[2] M. Naumann, M. Ostermann, N. Buchenau, J. Oetzel, F. Schlosser, H. Meschede, T. Tröster,
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