#  1\. Introduction

This Data Management Plan presents a summary of the key data that will be used
and generated by the INNOPATHS project, and how this data will be managed to
ensure that it is FAIR – Findable, Accessible, Interoperable and Re-usable.

This is intended to be a ‘living’ document. The information presented below
will evolve and become more specific (or change) over time, as the INNOPATHS
project progresses and as details, practicalities and feedback from project
partners and key stakeholders emerges.

#  2\. Data Summary

The INNOPATHS project involves both primary and secondary data collection, and
the generation of new data.

Primary data collection is planned by activities under Tasks 1.3, 1.4, 1.5,
2.1, 2.2, 2.3, 2.4, 2.5, 3.1, 3.6 and 4.4. Such data collection will largely
take the form of semistructured interviews with officials, analysts, technical
experts, academics and members of the INNOPATHS ‘Co-Design Group’ (CDG). The
collection, handling and storage of personal data will comply with the
procedures outlined in Deliverables 8.1 and 8.2.

Secondary data will be collected under a wide range of activities, tasks and
subtasks throughout the project. Such data will be largely sourced from the
scientific, government and grey literature and associated databases, along
with proprietary datasets. Specific examples of activities and secondary data
sources employed include:

  * Key characteristics (e.g. cost, performance, spillover rates and associated uncertainty ranges) related to key technologies (both historic and characteristics projected for the future according to existing EU scenario, roadmap and transition studies), across the power, ICT, industry, buildings, transport and agriculture sectors, for the EU and Member States (T1.1 – T1.3, & T1.6) 

  

  * Energy-related investments by households, using data from the German Mobility 

  

Panel (MOP), possibly in conjunction with the German Socio-Economic Panel
(SOEP) and the survey Mobility in Germany 2008. Analysis may also be extended
to Denmark or Norway, using similar datasets (T1.4).

  * Effect of environmental legislation on sectoral environmental and economic performance, skill composition of the workforce, and wage premia to different occupational groups, with data required to conduct such analysis sourced from varied public databases, including WIOD, EU-KLEMS and ONET (T1.4). 

  

  * Current and historic flows of finance to both high- and low-carbon technologies, and financial instruments employed. Data will be sourced from both publically available and proprietary databases (e.g. IEA/OECD, BNEF, Thompson Reuters) (T1.5). These datasets are already available to project partners, and will not incur additional cost. 

  

  * Identify significant technological advancements and associated spillover effects for key energy-related technologies using patent analysis. Patent data will be purchased to allow this analysis, with a budget of €10,000 allocated for this purpose (T2.2). 

  

  * Industrial process technologies and their characteristics will be updated in the PRIMES industrial sector model, using the European Commission’s Best Available Technique database (T3.6) 

  

  * Effect on the labour market and industrial competitiveness from changes in energy prices (a proxy of climate policies) using French firm-level data. In particular, three data sources available from the French statistical office will be used: EACAI (on energy expenditures), DADS (on employment and skills) and FARE/FICUS (on productivity and balance sheets). Access to this data is given after presenting a project and paying an annual subscription fee (paid by project partner SPO, outside of the INNOPATHS project budget). These data are protected by the statistical confidentiality directly at the source, and access to is granted only remotely using fingerprint identification (T4.1). 

  

  * The effect of income (in)equality on the ability to transition to a low-carbon economy, using cross-country emissions data linked with the various freely available datasets on inequality (i.e. Milanovic all gini, the world wealth and income database (http://wid.world/) (T4.5). 

  

  * The impact of new low-carbon transition pathways on air pollution, security of supply resources, materials agriculture and land, drawing on publically-available databases including GAINS and EXIOPOL (T4.6). 

  

Other primary and secondary data may be collected throughout the project, as
the need or opportunity arises. The purpose for such primary and secondary
data collection is multifaceted. Such data is required to (a) understand how
existing studies have treated different aspects of technology, the
environment, economy and society, to draw lessons for the analysis to be
conducted in INNOPATHS, (b) allow analysis to address specific questions posed
by the INNOPATHS project, using the most relevant and best data available, (c)
improve the quality of data inputs to, and the characterisation and detail of,
different models to be used to produce new low-carbon transition pathways, and
(d) to analyse the environmental and socio-economic impacts of such pathways,
beyond those assessed by the models that created them.

The data generated by the project in the tasks outlined above (along with
those from other activities and tasks) will be made available principally
through three publically accessible ‘online tools’:

  * **Technology Matrix –** This will consist of graphical representations of underlying data on different parameters regarding different energy-related technologies. The user would be able to select different cost and performance (including environmental performance) variables for the x/y axes and to show the results in a wide range of units. There would also be the functionality for cross-country and cross-technology comparisons (when data at that level is available), a search function (by keywords), and a menu structure (or equivalent). It will also be possible to select future-looking cost and performance estimates for the period 2030-2050 (with uncertainty ranges). A perspective on ‘Technology Readiness Level’ (TRL) progression would also be provided. 

  

  * **Policy Assessment Framework -** This tool will be designed to exploit to the fullest the research carried out under WP2, which is dedicated to the creation of a framework, which will build on official EU criteria, to set out what we know about the outcomes of a range of energy policy instruments. The tool will allow the user to select a policy or a group of policies, and then visualize what the state of the art knowledge is on the different types of impact that policy has had. This knowledge will come from a wide range of literatures and countries and from the project itself. The indication of impacts would include the source of the impact, as well as the level of confidence in the results. 

  

  * **Low Carbon Pathways Platform -** This Platform will allow stakeholders to assess the socio-economic implications of medium- to long-term decarbonisation pathways, including their associated costs, benefit and risks, view and interact with the energy-economy pathways for the 21st century modeled in WP3, and extract the information relevant for their decision-making. They will be able to access the important variables (energy, emissions, technology deployment, prices) for the different models, sectors, scenarios, and countries (and combinations thereof). The user-friendly interface will provide quick introductions and how-to-recipes to facilitate information access by first-time users. 

  

These tools, and the information and data contained and presented therein,
will be useful for a wide range of stakeholders, including academics and
researchers (not least those involved with INNOPATHS, in order to address the
key research questions posed by the project), national and local policy
makers, industry representatives, and the wider public.

A forth online tool will also be developed and employed by the project:

\- **Interactive Decarbonisation Simulator** – This tool has the goal of
giving policy makers, the general public and industry associates a more
intuitive understanding of different decarbonisation strategies, and what
different choices and targets in the various sectors and MS entails for the
other sectors and MS. It is a tool that is fully interactive; policymakers can
increase the mitigation effort in one area and decrease it in another, and the
simulator will give them a rough idea of the expected effect. The tool invites
users to interact with it - by designing a few different decarbonisation
strategies, one can quickly get an intuitive understanding of which measures
have a large effect and which don't, and where potential bottlenecks might
lie.

However, the Interactive Decarbonisation Simulator will draw on scenarios and
data generated by existing studies by project partner E3M, rather than those
generated by the INNOPATHS project. In addition, although it will be
accessible to the public through the INNOPATHS website alongside the three
online tools described above, it will be produced and hosted by E3M (with
project partner N&S applying INNOPATHS style and branding). As such, the
sections below refer only to the first thee online tools described above
(except for Section 2.1, which is applicable to all four tools).

#  3\. FAIR Data

##  1.1 Making data findable & Metadata

###  Discoverability and Metadata

For each online tool webpage/portal, we will adhere to search engine
optimisation (SEO) best practices. This means they will be easily discoverable
by search engines, using HTML metatags to describe the content of the tools in
clear and easily understandable manner. The presence and location of the
online tools will be heavily advertised by INNOPATHS Deliverables,
publications and various dissemination channels (including the project flyer,
social media and events).

Once a user has navigated to the online tool, specific data may be found
through a verity of means, depending on the tool in question and data of
interest. For example, the Policy Assessment Framework (PAF) tool will allow
users to access underlying information (e.g. effectiveness, cost-efficiency)
about different policy instruments and mixes at different levels of
granularity (at least two), including outcomes, level of confidence, and
source material. Different categories of data will be presented in different
ways. For example, the context for a particular policy may be displayed in the
form of a comment, the level of confidence on a particular outcome may be
shown as a number with a clear description (translation) of what that number
represents, and in some cases the ‘impact’ may be measured with a number or a
range.

It is likely that each online tool will have a keyword search, dropdown
filtering functionality and/or structured menus to help narrow down the user’s
selection and more easily navigate the tools to identify the data of interest.

Specific keyword and metadata terms and conventions will be defined as the
data is produced and online tools are created. However, for the Low Carbon
Pathways Platform (LCCP) the metadata will follow the Integrated Assessment
Modelling Consortium (IAMC) convention  1  of scenario and variable metadata,
thus containing information on the scenario definitions, the models used,
their version number, regional resolution.

###  Versioning

To make it clear when an update has been made to either the functionality of
the online tools, or the data contained in and presented by the online tools,
a version number will be added to the relevant page, along with the date that
the tool was last updated.

##  1.2 Making data openly accessible

###  Accessibility for Project Partners

During the construction of the online tools and their initial population with
data, all partner institutions will have access to the tools via a web
interface. In addition, for the Low Carbon Pathways Platform (LCPP), for the
purpose of convenient scenario data analysis, consolidated snapshots of
scenario data will be available to partner institutions. Selected stakeholders
(i.e. co-designers who will test and provide feedback to the design of the
tools) will also have access, under strict confidentiality arrangements.

The specific protocol for access and data use during this period will depend
on the specific tool. For example, for the LCPP, when submitting data to the
INNOPATHS scenario database for subsequent display on the LCPP tool, modelling
teams will agree to the internal use of their scenario data by all INNOPATHS
partner institutions. However, the team producing the scenario data, in order
to account for the iterative process of scenario calculation and quality
control, must approve publication of research based on such data by project
partners. Individual modelling teams participating in the INNOPATHS project
shall retain control of their preliminary scenario data. Use of preliminary
scenario data by other partners than the modelling team generating this data
must be through explicit permission from the modelling team concerned.

When the online tools are made available to the general public, differentiated
access permissions will be defined. **Accessibility for the Public**

All online tools will be fully accessible to the public. The datasets
contained within and presented by each of the tools will be viewable directly
within the tools themselves, or extractable to comma separated value (CSV)
file format for further analysis. The CSV format is a widely used format
applicable to most data analysis software.

To preserve transparency, the code for each of the online tools will be made
open source and accessible to the public through GitHub (the Interactive
Decarbonisation Simulator will also be open source).

##  1.3 Making data interoperable

The form in which the data is presented will depend on the specific tool and
specific data of interest (e.g. numerical value, text, hyperlink, etc.). All
efforts will be made to ensure the data presented is easily understood and
easy to use for further analysis. This will include, for example, the use of
the IAMC variable template for the data presented by the LCPP. Efforts will
also be made to link to the common scenario databases and scenario
visualisations of the IAMC Working Group on scenarios and the Horizon 2020
project CD-LINKS.

As discussed above, all data presented by the online tools will be
downloadable into CSV format, for ease of interpretation and analysis.

##  1.4 Increasing data reuse

Any license conditions for the use of data presented by the online tools will
be clearly displayed, both on the online viewing platform and accompanying any
downloaded data.

The data for each online tool will be made available to the public once
related scientific work has been made available for publication. This ensures
that the data is subject to the additional quality control from the review
process. After the re-use embargo is lifted, the data may be freely used by
third parties for non-commercial and educational purposes.

Efforts will be made to preserve the online tools for public use for as long
as possible after the conclusion of INNOPATHS. Specific timeframes will be
clarified as the project progresses. Subject to future funding, updates to
data presented by the tools may be updated.

#  4\. Allocation of Resources

The costs for making the data generated by the project ‘FAIR’ will be minor,
and are included as part of the budget assigned to the project partners
responsible for producing the data for the online tools (AU, UCAM, E3M and
PIK), and the project partner responsible for producing the tools themselves
(N&S).

Responsibilities for data management rest in the first instance with the
project partners responsible for generating and collating them (as above), and
then with UCL, who will host the data and the tools through the UCL Research
Data Service (see below). Preserving long-term access to this data, through
the online tools, will be highly valuable to INNOPATHS stakeholders (e.g.
policy makers, industrial groups, NGOs), and is achievable at minimal, and
perhaps zero cost (specific value to be determined).

#  4\. Data Security

The online tools, and data generated by the project for use by these tools,
will be curated by the UCL Research Data Service  2  . UCL’s Research Data
Services (RDS) has the capability to store and access very large volumes of
electronic research data and data products, to support coordinated end-to-end
research workflows encompassing the use of both data storage and computational
resources (e.g. UCL’s high performance computing services), and to protect and
preserve digital data assets, including for future re-use and exploitation.

The project’s data storage strategy will consist of three components: private
web server storage, a secure short-term backup facility, and a long-term
archive. Consortium partners are able to upload and exchange data using the
private server. Web server storage is flexible, backed up, and can be readily
expanded if necessary. The long-term archive will ensure that data and the
online tools are preserved once the project comes on an end (for a timeframe
yet to be determined).

#  4\. Ethical Aspects

For an assessment and management of the ethical aspects of data collection and
use for the INNOPATHs project, please see Deliverables 8.1 and 8.2.