# USEFLEDS: WP3, D3.1 - 1st Iteration

**Content:**
* [Partners](#Partners)
* [FH Bgld](#FH-Burgenland), [4er](#4ward-Energy), [Advoodle](#Advoodle), [Campus02](#Campus02), [EnergySrv](#Energy-Services), [Kelag](#KELAG), [Nexyo](#Nexyo), [Onlim](#Onlim), [Salzburg AG](#Salzburg-AG), [Salburg Netz](#Salzburg-Netz), [Salzburg Research](#Salzburg-Research), [Scheiber](#Scheiber-Solutions), [SDA](#Sustainable-Data-Agency-Alexander-Steger), [TU Wien](#TU-Wien), [OYD](#OwnYourData)
<!--* [Use Case Proposals](#Use-Cases)
* [Flexible Tarifs](#Flexibe-Tarifs), [Energy Flow Optimization](#Energy-Flow-Optimization), [ESG Reporting](#ESG-Reporting)-->
* [Documents](#Documents)
* [Data Flow Specification](#D31-Data-Flow-Specification)
* [Requirements Document](#D32-Requirements-Dokument)

### 1st round of meetings
- [x] FH Burgenland: Dec 19, 2023 10:00
- [x] 4ward Energy: Dec 20, 2023 14:00
- [x] KELAG: Jan 5, 2024 10:00
- [x] Salzburg AG: Jan 8, 2024 13:00
- [x] Campus02: Jan 9, 2024 09:00
- [x] TU Wien: in-person @TUW Jan 11, 2024 9:00
- [x] Nexyo: Jan 12, 2024 10:00
- [x] Salzburg Netz: Jan 15, 2024 10:00
- [x] Energy Services: Jan 15, 2024 14:00
- [x] Salzburg Research: Jan 19, 2024 10:00
- [x] Advoodle: Jan 22, 2024 14:00
- [x] Alexander Steger, Jan 22, 2024 15:30
- [x] Onlim: Jan 26, 2024 10:00

### Follow-up meetings
- [x] Data Intermediary: Jan 23, 2024 15:30
- [x] Scheiber Solutions: Jan 24, 2024 14:00
- [x] KELAG: Jan 24, 2024 15:30
- [x] TU Wien: Jan 25, 2024 9:00
- [x] Campus02: Jan 29, 2024 11:30

-> Summary available here: https://hackmd.io/dtJS4G0cSC6clQdwR7lCWA?view
-> User Stories here: https://hackmd.io/n_uO5dZqSP-U1pE556Zs9Q

## Partners

### FH Burgenland
Contact: [e-mail]
(organisation: [e-mail])
Role: consortium lead, WP1 lead, WP7 lead, WP8 lead
Type: domain & technical partner
<!--
Use Cases:
* primary: Flexible Tarifs
* Energy Transition (Markus P. & Christian P.)
* Sustainable Innovation & Digitalisierung (Christoph K.)
* Building Technology (optional)
-->
Data for Energy Transition (create opportunities):
* Have
* Need
* network utilization from grid providers
* Process
* Interprete

Stakeholder:
* institutions/organisations (e.g., FH)
* private person
* agriculture
* industry
* energy provider
* grid provider

Data Space Tools
* [Dataspace Management Vision Demonstrator](https://www.figma.com/proto/hVkvoEmzIqo33JE9KEpk4G/Dataspaces?page-id=15%3A167&node-id=15-6403&viewport=3072%2C438%2C0.16&scaling=min-zoom&starting-point-node-id=15%3A6403&show-proto-sidebar=1)
* [Github Link](https://github.com/eclipse-edc/MinimumViableDataspace/blob/main/Vision%20Demonstrator/Vision%20Demonstrator%20Introduction.md)

Dataflow:
* extisting
* not yet
* future
* planned energy monitoring for Landesholding Burgenland
* local communities (Gemeinden): Netzauslastung --> Netzausbau
* PV farms, wind,... decentralised infrastructure of grid
* plan for network expansion
* mobility: students traveling to university
* try in FH (Fachhochschule) & FB (Forschung Burgenland daughter FH)


Meetings:
* 11.Nov23: SSI, partner structure, data spaces
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 19.Dez23: collect DataFlow inputs
* 8.Jan24: Data Intermediaries
* 23.Jan24: Data Intermediaries II

### 4ward Energy
Contact: [e-mail]
(organisation: [e-mail])
Role: WP4 lead
* E-Werk Franz - https://www.ewg.at/ (energy provider + distribution system operator (DSO) in Graz <- collaborate with Energy Services on Use Case
* Energy Services: smart meter management, billing, trading electricity
Type: research partner
<!--primary Use Case: ??? (Salzburg: collaborate on use case development) -->
Data: first 2 iterations for scoping and last 2 iterations focused on selected use cases (more practical)

* Have
* to be provided through Energy Services, might be through E-Werk Franz
* already collected data from previous research projects
* Need
* smartMeter Data - from customers (yearly -> 15min resolution)
* data only available on the next day
* expected problems: internet connections to private customers
* weather data: historic, now, forecasts (global irradiation -> PV), temperature, wind speed, precipitation
* per consumer / better: per device: current consumption / current generation <- should be real time data (15min is too coarse grained)
* including forecasts
* load profile generator: https://www.loadprofilegenerator.de/
* energy tarifs: economic aspects, device data (type, specs)
* current time resolution is not enough right now (example: only yearly billing)
* Process
* access data available in Energy Data Space
* Interprete
* focus is on initial selection of use cases

Stakeholders:
* EDA GmbH
* Energy Services
* providers and users of
* storage (battery)
* power inverter
* photovoltaics
* energy management system (HW+SW -> Loxone: https://www.loxone.com/)
* E-charging stations
* heat pumps
* distribution grid operators (200+ in Austria)
* customers / private households <- are they data provider or do they only consent to providing data?
* GeoSphere Austria / "Energy & Meteo" for MET data

Data Flows:
* existing
* EDA -> check processes: https://www.eda.at/
experts: Energy Services
* GeoSphere Austria: MET
* maybe: Energy & Meteo - https://www.energymeteo.com/
* read device data using MQTT, OPC-UA, REST APIs
* future
* live data metering (electricity, gas, heat)

Meetings:
* 7.Dez23: Salzburg Kick-off (talk after world café)
* 20.Dez23: WP3-WP4 Coordination

### Advoodle
Contact: [e-mail]
(organisation: [e-mail])
Type: domain partner + technical parts (Blockchain, AI)
Role: Legal / Governance Support ("translator" between technology & law incl. visualisations)
primary Use Case: ESG Reporting

**Data**
* European supply chains
* CSRD - [Corporate Sustainability Reporting Directive](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32022L2464)
* includes documentation of strategies/outlook for the future; financial & non-financial impact of individual measures
* double materiality check ("Materialitätsprüfung") with regard to data exchange in the energy industry
* ESRS - European Sustainability Reporting Standards ([overview: figure 3](https://kpmg.com/at/de/home/insights/2022/11/acnews/einigung-zur-csrd.html))
* Reporting: ESEF (European Single Electronic Format) standard for financial reporting (could be extended to non-financial reporting / CSRD reporting)
* general Data Governance
* data ownership
* data protection
* liability
* regulatory governance

**Stakeholder**
* consortium is already well positioned in the area of data
* individual connectors might be necessary

**Data flows**
* link energy data with carbon emissions (more generally: GHG - Green House Gases)
* standardisation of data exchange

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 22.Jan24: 14:00 WP3 first call

### Campus02
Contact: [e-mail]
(organisation: [e-mail])
Role: WP2 lead
Type: domain partner
Meetings:
* 7.Dez23: Salzburg Kick-off (co-host at table)
* 9.Jan24: Co-creation Workshop Prep
* 29.Jan24: Co-creation Workshop Prep II
* 1-2.Feb24: Co-creation Workshop @ FH Bgld

### Energy Services
Contact: [e-mail]
(organisation: [e-mail])
Role: WP7 lead (Aggregation & Evaluation) & collaboration with 4ward Energy
**Type:** domain partner (electricity, covers all market roles: supplier, network operator, system operator, energy service provider - as defined in the law)
* EDM (Energy Data Management) software is made available during the project

**Use Case:** Energy Flow Optimization
* end user with smartMeter / smart Devices
* network operator and energy supplier ([E-Werk Franz](https://www.ewg.at/)) - also feeds in via PV system
* data in EDM (in-house developed and maintained by Energy Services)

**Daten:**
* clear focus on all data managed by [Energiewirtschaftlicher Datenaustausch](https://www.eda.at/?lang=en) EDA.at
* weather data from MetGIS (established contact with Energy Services)

**Stakeholder:**
* be aware that many organisations / company wear multiple hats (example: private company E-Werk Franz)

**Dataflows / Prozesse** - defined through the following establied services:
* data hub: https://www.eda.at/
* interfaces: https://www.ponton.de/eda-how-does-it-work
* data models: https://www.ebutilities.at/schemas/

new releases twice a year as defined on https://www.ebutilities.at

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 15.Jan24: first WP3 Call

### KELAG
Contact: [e-mail]
* Weisskircher Florian (Vertrieb)
* Zwatz Florian (Handel)

(organisation: [e-mail])
Role: data provider
Type: domain partner
Use Case: Flexible Tarifs
* Requirements for energy communities (with regard to energy transition)
* Example Obertauern (80% hotels)
* Data sharing

**Data** for Energy Transition (leverage opportunities):
* L-Band Satelliten: verfügbare Schnee/Wassermenge (ENEO)
* check: https://www.enveo.at/
* for predictive maintenance
* problem with consumer data from smartMeter (resolution: 15min interval)
reliability: if data is missing, how are replacement values generated?
essential driver for day-to-day business is having all data available: relevant for every tariff that is to be billed using current SmartMeter values (especially on Austrian scale)
(if a single value is missing in an energy community - then the whole system stops)
* electricity generation (including heat & gas) - theoretically available in real time
* Abrechnungsperiode ist 15min
* Gas: Speicherstände
* KELAG produces 100% from renewables; and buys 100% green electricity (i.e. electricity with certificates for green electricity)
* disclaimer: only the sum of supply and the sum of consumers matches - but physically electricity may still be delivered from a caloric power plant

**Stakeholders within KELAG:** Trade, Sales, Production

**Dataflows**
* existing
* there is no existing data exchange through data spaces in KELAG yet (only data exchange with Open Data)
* future
* energy requirements (electricity, gas, heat) can be well estimated per year; not so easy are estimations on a more fine grained level
* relevant to know is the form of heating: for a full service it would be interesting to know e.g. gas consumption
* the more information about the customer is available (age, income situation, single/family, which heating system, e-mobility) the better customers can be serviced, the better tailored products can be developed
* flexibility & storage: if the customer has an electric car to store electricity -> the customer has the opportunity to behave in a "system-serving" way (electricity provider manages car battery)
* the desire is to start a campaign that only targets those with these capabilities addresses
* data to generate personas / develop customer segments precisely
* Weather data: forecasts for smaller regions (relevant for heating in winter, generating PV electricity); if I know how heating is done / what heating requirements are / the situation of the building, it has a specific profile that can be taken into account: link from existing weather data to sales profiles
* with an available weatherforecast the power consumption of a heat pump can be better modeled
* Data exchange for trade department
* Copernicus / ESA data for risk analysis (100-year probabilities for extreme events)
* Intraday trading is part of daily business
* real smartMeter data would enable better planning for day-to-day business -> possible future scenario (better forecasts, less uncertainty)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 5.Jan24: first WP3 Call
* 24.Jan24: 2nd WP3 Call

### Nexyo
Contact: [e-mail] (CC: [e-mail])
(organisation: [e-mail])
Role: data spaces, policies, governance, enable data sharing, hosting of a Data Space (check out: [Building Data Spaces in 4 Steps](https://drive.google.com/file/d/1YbYkcrPeJwd-pFEpa9SEviIvRPzQb_G7/view?usp=drive_link))
Type: technology partner
Use Case: ESG Reporting and support other use cases with data sharing through technology support and consulting (recommend: C4 modelling - https://c4model.com/)

Input for State-of-the-art:
- DTS Endreport (https://project-dts.eu/)
- Champions (https://www.champi40ns.eu/en/)

**Data**
* power consumtion (in various granularities)
* carbon footprint (in regard to ESG Reporting)
* climate & weather
* raw materials: calorific value, impact on (carbon) footprint
* population data (Statistik Austria)
* tourims: occupancy of hotels / overnight stays
* power consumption of industry
* transport routes
* economic data (clusters for ESG reporting - SMEs not affected by ESG); also: forecasts for economic development

**Stakeholders:** (beyond consortium that could be relevant)
* GeoSphere (provider of climate and weather data)
* ASFINAG: traffic information
* mobile operator (proxy for energy consumption)
* international multipliers -> how to bring the results to the European level

**Data Flows**
* existing:
* Standardization of power consumption data
* E-Control: a vailability of e-charging stations (https://www.ladestellen.at/#/electric)
* future:
* Consumption data for ESG reporting (Scope 1&2 data)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 12.Jan24: collect DataFlow inputs

### Onlim
Contact: [e-mail]
(organisation: [e-mail])
Role: Conversational AI, Knowledge Graphs
Type: technology partner (spin-off University of Innsbruck)
Use Case: ESG Reporting <- focus

Data: Onlim is data processor but not a data provider
* open questions how to access relevant data
* focus on real data, for testing & benchmarking also synthetic data could be possible

Stakeholder:
* LLM: use Azure instance from OpenAI -> with the goal to host it locally

Data Flows (available tool: https://app.onlim.com/, commercial product)
* modelling & describing data, mapping data from multiple data sources
* data enrichment and interlinking
* integrate with other data (apps & actions) to build data flows / data pipelines
* flow editor to visually connect components
* LLM for data extraction and extending knowledge graphs
* enventually making the data accessible in conversational AI

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 26.Jan24: WP3 Dataflows

### Salzburg AG
Contact: [e-mail]
(organisation: [e-mail])
Role: data provider, evaluate use case & selection of services (to be developed during project)
Type: domain partner (market participant in energy market)
Use Case:
* economic considerations: parallel existence of Salzburg AG & Salzburg Netz
* linking energy provider and networks
* predictive maintenance

**Data:**
* external data to enrich own data
* energy & heat production -> general and per plant and per hour incl. sensor data
* market prices (note: sales department of Salzburg AG is not part of the project but enough know-how available through Stefanie Kritzer)
* network load / grid voltage
* aggregated data for each tarif group -> to answer the question "at what point do I need how much electricity?"
* consumption profile data from industry customers
* synthetic data from small consumers might be outdated
* changes because auf PV systems
* e-mobility
* more / better weather data allow for better prediction on consumption
* labeling of electricity
* Salzburg produces about 50% -> green electricity
* and buyes the rest -> grey electricity
* the resulting trade with carbon certificates is static / defined legal situation
* gas is still very much relevant for heat production

**Stakeholder:**
* energy providers
* sales
* sales
* distribution system operators (grid providers)
* major network operator in Austria: APG (Austria Power Grid)
* small / medium / big consumer
* synthetic profiles
* ski areas - check [end report from CleanEnergy4Tourism](https://drive.google.com/file/d/1ijWEcn2vFHOBlflzId9Ha57P9n1YqkmL/view?usp=drive_link)
* cell phone data (A1, ...)
* electricity sales data
* energy storage technology

**Existing Dataflows:**
* E-Control
* Electricity Market
* EEX (European Energy Exchange): for long-term trades
* EPEX (European Power Exchange): spot markets (focused on day-ahead and intrday trade)
* https://www.eex-transparency.com/de/power/at/produktion/verfuegbarkeit
* energy provider need to report availability of power plants and levels of water storage power plants (also to avoid insider trade)
* report of all commercial transactions
* timetables for power plants
* weather forecasts

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 8.Jan24: WP3 Dataflows

### Salzburg Netz
Contact: [e-mail]
(organisation: [e-mail])
Role: data provider, evaluate use case
Type: domain partner
primary Use Case: Energy Flow Optimization (example: Gasteiner Tal - Anger-Tal Umspannwerk)
- [ ] Dorina: end report from recent research project

**Data**
Comment: Salzburg Netz reserved some budget to buy external data (to show added value from linking external data and have creative/new ideas on using data in new ways)
* Cellular data for better planning/predictions
* Network load planning (short-term and long-term)
depends on a fine-granular level on use of e-mobility, heat pumps, photovoltaic, etc.
* Types/divisions in Salzburg Netz
* electricity
* gas
* district heating
* power consumption per consumer is regulated
* single-family home restricted to 4kW
necessary to increase for photovoltaic installation
* mountain railways / ski lifts: much higher and they pay peak values instead of average consumption
* smartMeter data not yet integrated in Salzburg Netz
roll-out at about 80% now
* load profile counters in use for companies
* Salzburg Netz Subsidiaries that might provide other relevant data
* Salzburg Verkehr (buses)
* Schafsbergbahn
* Wolfgangssee-Schifffahrt
* data exchange between network provider and energy produces might be problematic since this is sensitive data
example: energy provider has 400 customers but network provider has information about 700 endpoints
Salzburg Netz is subject to strict monitoring, but has no competitors; nevertheless, Salzburg AG & Kelag are not allowed to benefit from the Salzburg Netz data! -> one possible solution is to make data public / available to everyone

Relevant / possible stakeholder beyond consortium:
* Asfinag, A1
* Google, Booking.com, Social Media (FB, X, Instagram)
* weather data (also search queries from tourists might be relevant)
* Public transport company (ÖBB); Ski train in Gastein

Dataflows
* electricity grid: network maintenance at different levels - plans for first 5s, 20s and 2minutes
* E-cars as electricity storage
* [ ] Dorina: reference to latest standard
* better predictions through tourism data: ski tickets sales, publlic transport utilization, booking situation at hotels, traffic jams (Asfinag)

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 15.Jan24: WP3 Dataflows

### Salzburg Research
**Contact:** [e-mail]
(organisation: [e-mail])
**Role:** WP6 lead (AI Integration) - use case implementation / development of AI algorithms for use cases
**Type:** research partner (incl. developing prototypes)
focus on Salzbuzrg AG & Salzburg Netz (Salzburg cluster)
**Data:**
* processing, interpretation; demonstration of possibilities with AI
* improve forecasts for power grid, e.g., Gasteinertal/Angertal
* measures in critical siutation
* evaluate if and how much improvement is possible
* planned data processing from Salzburg AG, Salzburg Netz, and beyond
* time series data from electricity consumption
* historical power plant schedules
* weather, tourism, mobile carriers
* demand forecast based on consumption data (snow cannon) for edge cases; identify pivot elements based an availability and price of data
* economic consideration of the whole energy system (previously only economic consideration of the individual stakeholders)

**Stakeholder:**
* energy providers (including private feeders, small power plants, local energy communities)
* grid operators
* large consumers (mountain railways, tourism companies)
* weather data providers, mobile operators
* mobility service providers: ÖBB, shuttle buses, taxis

**Dataflows:**
* existing:
* EDA
* future:
* new forms of data exchange are necessary for our project -> establish of cross-organizational data sharing (sharing public data alone does not forn a data space)
* enabling data exchange beyond established trust boundaries (through incentives, new legal frameworks)

**Meetings:**
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 19.Jan24: 10 Uhr (Peter, Nina)

### Scheiber Solutions
contact: [[e-mail]](mailto:[e-mail])
(organisation: [e-mail])
Role: Umsetzung von Use Cases mit Lösungen von Scheiber Solutions (KI Prognose für die nächsten 7 Tage)
Type: technology partner
Use Cases:
* primary: Energy Flow Optimization (load management in power grids)
* decentral and flexible tarifs
* privacy & GDPR

Data:
* EDA data pool for everyone with smartMeter
* data disaggregation for H0 (consumption profile for households; E0 is profile from PV production) -> Link to Salzburg AG
* already use data models from FIWARE and SmartCity research projects

Stakeholder:
* decentralization / energy communities: focus on regional context & effects on higher levels

Data flows:
* local energy consumption as provided by smartMeters (averages out at a higher level)
* but: in a decentralized market, energy is consumed locally, which is then suddenly no longer available at a higher level
* awareness for producers about how electricity consumption is developing
* automation for operating intelligent charging stations

Meetings:
* 24.Nov23: available products & goals
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 24.Jan24: WP3 Data Flows

### Sustainable Development Agency (Alexander Steger)
Contact: [[e-mail]](mailto:[e-mail])
(organisation: [e-mail])
Role: introduces ESG Reporting use case to consortium
Type: domain partner
Use Case: ESG Reporting (automated data exchange)
* as introduced by European Green Deal
* reduce effort to aggregate data which is relevant for ESG Reports
* re-use data for similar activities (join Klimabündnis, request credit/ÖKB)

**Data** (in regard to ESG Reporting use case)
* currently heterogeneous input data (PDF, Excel, images)
* standardised formats for energy and water consumption, ground sealing
* necessary data depends heavily on customer
* focus on simple scenarios to begin with
* develop personas
* existing ESG Hub from ÖKB

**Stakeholder**
* Tourism
* ÖKB - Österreichische Kontrollbank, https://www.oekb.at/ (ESG Data Hub)
* Consultants
* WKO, DIO - for authentication
* Akaryon - ESG Cockpit

**Dataflows**
* harmonizing input and results to avoid discrepancies (example: high variety in carbon emissions reports)
* retrieve data along suplly chain (highly specified data, like country of origin, packaging, transport of goods)
* expected steps
1. data collection
2. data processing and development of a strategy
3. reporting and certificates
4. implementation and improvements
* overall goal: end-to-end solution of an automated consolidation and distribution tool

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 22.Jan24: WP3 Data Flows

### TU Wien
Contact: [e-mail]
(organisation: [e-mail])
Role: WP5 lead
- ASG working group
- Working on modeling and system architecture
- TU Vienna
- Possibly stakeholders
- Buys electricity on the stock exchange
- obtains heat from Vienna Energy
- has many customers internally that need to be coordinated

Type: technology partner
Stakeholder:
- ASG
- Anyone who has anything to do with the energy grid
- TU Vienna
- Central shopping
- Faculties, institutes and working groups
- Network provider
- Optimization service providers
- Data aggregators
- Data collection service providers

WP3 Collaboration:
* State-of-the-art
* Ontologoy Visualization: https://github.com/VisualDataWeb/WebVOWL

**Data**
* on flexible tariffs: basic power (e.g. 3kW) is guaranteed, more needs to be paid extra
* increased decentralization can lead to 2 developments
* grid operator collects data and controls consumers
* so called "aggregators" collect data (example: neoom.com, efriends.at)
* requires more data
* interesting question how to switch between aggregators
* relevant data: e-car, PV, battery, heat pump, ... on different levels (have/not have -> capacity -> profile & capabilities -> live data)

**Dataflows**
* Data Space sense-making: [Data Space Business Alliance - Technical Convergence](https://drive.google.com/file/d/1y9LPiA-Rfw7IACe5ogNpLs3zCalvP7Vf/view?usp=drive_link)
* resilient architecture for decentralized planning of the schedules of small feeders -> establish energy community in Burgenland:
* protocol: ModBus (https://en.wikipedia.org/wiki/Modbus) and data models from Sunspec (https://sunspec.org/)
* collects data and stores in FIWARE
* investigate social compatibility
* types of energy communities:
* local (level 6 - grid behind trafostation)
* regional (level 5 - grid behind substation "Umspannwerk")
-> focus on economic cooperation and saving network costs
* example: Neoom (https://neoom.com/) with accesses to inverters & storage to make intra-day trades

Meetings:
* 7.Dez23: Salzburg Kick-off (inputs on table)
* 11.Jan24 9:00 @TU Wien
* 25.Jan24 9:00 @TU Wien

### OwnYourData
Contact: [e-mail]
(organisation: [e-mail])
Role: WP3 lead
Type: technology partner

<!--
## Use Cases

### Flexibe Tarifs

### Energy Flow Optimization

### ESG Reporting
-->
## Documents

### D3.1 Data Flow Specification
1. Introduction
2. Stakeholder
3. User Stories
4. Data Sources
5. Functional Components
6. Data Flows
7. Conclusions

### D3.2 Requirements Dokument
1. Introduction
2. Motivation and Planned Functionalities
3. Requirements
* Non-functional Requirements
* Functional Requirements
4. Business Aspects and Governance
5. Use Case Analysis
6. Conclusions