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Focal Point support to Data Activities Focal Point TEAMS Meeting 06-07 May 2020
Focal Point support to Data Activities
Focal Point TEAMS Meeting
06-07 May 2020
UPDATED PLAN
2
Promoting best practisesTask 5.4. – 22 MSTask 5.5. – 17 MSTask 5.6. – 13 MS
Data collection in the area of animal health & the SIGMA ProjectTask 5.7. – 15 MSTask 5.8. – 13 MS
Training and support activitiesTask 5.9. – 12 MSTask 5.10. – 5 MS
3 areas of activities of the data session:
Promoting best practices
Data collection in the area of animal
health & the SIGMA project
Training and support actions
41st meeting of the FP Network 12-13 November, Parma
After TEAMS meeting of FP network10-11 March 2020
Promoting best practices
3
NEW TASKS – 5.4.
4
“FP supports the implementation of actionsstemming from the Advisory Forum task forceon data collection and data modelling”.
▪ FP acts as an interface betweenthe task force, EFSA and thenational level.
▪ Draft report will be circulatedin May to AF members.
▪ Final AFTF report withrecommendations willbe available in June 2020
ADVISORY FORUM TASK FORCE
5
DIRECTION AND VISION
6
• Effectiveness of the current system?
• Data in a future, the ideal EU food safety system.
• In an era of big data, organizations need to look towards the future.
MAIN OBJECTIVE
7
• Focus on the data collection and reporting processes.
• Data models and IT infrastructure used in the sharing of data between data providers and EFSA from a strategic perspective.
• Formulate recommendations at a strategic level.
MAIN PRIORITIES WITH OUTPUTS
8
1.Data Collection and Reporting1.1 Member State reporting in the Food/Feed domain1.2 Harmonised data capture at the point of sampling1.3 Timeliness of data and real-time reporting1.4 Accessibility and potential uses for new data sources in the Food/Feed domain1.5 Legal framework and legislative updates
2.Data Modelling2.1 Evolution and adoption of the samples data model (SSD)2.2 Revisions of data models and catalogue values2.3 Data models for new data sources2.4 Data governance
3.IT Architecture3.1 Data exchange and access mechanisms3.2 National & EU data systems3.3 Laboratory Information Management System (LIMS) and contract laboratories3.4 Common use of data manipulation, validation and analysis tools
4.Data Analysis4.1 Data driven design of monitoring programmes4.2 Data use in incident tracing, predictive analytics and emerging risks
• Improve interoperability betweendata collection systems.
• Discussion on the usefulness andfeasibility of a standardized,single food safety data model acommon model.
1. DATA COLLECTION AND REPORTING
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• Explore the possibility of using other, modern solutions (data lakes,data ecosystems etc..) taking into account the advantages and thepossible challenges as well.
• Timeliness - to consider what would facilitate more rapid monitoringdata availability at the national level, rapid communication andaccessibility of the data would improve data quality, use and utilityfor example in crisis management.
1. DATA COLLECTION AND REPORTING
10
• Member State reporting in the Food/Feed domain
• Harmonised data capture at the point of sampling
• Timeliness of data and real-time reporting
• Accessibility and potential uses for new data sources in the Food/Feeddomain
1. DATA COLLECTION AND REPORTING
11
Evolution and adoption of the samples datamodel (SSD)- could be further improved forother data domains e.g. food contact materialor feed data.
Revisions of data models and cataloguevalues - the usage of EFSAs catalogues at thenational level.
Data models for new data sources -Alignment with existing data models andmaximize interoperability of datasets.
2. DATA MODELLING
12
• Exploring the possibility ofusing modern solutions, e.g.data ecosystems, data lakes.
• National systems being builttoday should be built withinteroperability in mind.
3. IT ARCHITECTURE
13
• Discussions on designing the ‘futurefood safety data ecosystem ofEurope’. By opening up systems sothey can interact with each other.
• Collaborative joint projects andsharing best architecture practicesshall be encouraged.
3. IT ARCHITECTURE
14
• Collaboration and best practice sharing ofdata analysis methodologies.
• Activities addressing data literacy.
• AI plays a significant role in future of dataanalysis.
• Application of results produced bycomputational science solutions in riskmanagement / policy decision making.
• Good practices of data interpretation.
4. DATA ANALYSIS
15
SHORT- AND LONG-TERM THINKING
16
• Can we simplify existing and potentially future data streams and lessen the burden of reporting?
• Can we ensure a future-proof access to data necessary to conduct risk assessment and risk management?
• Strategic planning is needed to address both the short-term and long-term challenges.
RECOMMENDATIONS
17
• Results of the discussions and conclusions.
• Three categories: quick wins; short- to medium-term; and long-term.
• Grouping and order of recommendation doesn’t not imply importance and the list of recommendations is not a priority list.
• The more complex recommendations (usually the long-term ones) need strategic breakdown of the objectives and defining actionable projects.
5.4 AF TASK FORCE – QUESTIONS
18
“FP supports the promotion of bestpractices for timely submission of data toEFSA”
NEW TASK - 5.5.
19
TIMELINESS
20
Each MS has a different national arrangement.
Important to know processes of data transmission to EFSA.
Identify bottle necks at the national level preventing timely submission of data.
21
Partnership with Network Representatives
BUILD A PARTNERSHIP
22
TIMELINESS TEMPLATE
23
TIMELINESS TEMPLATE
• Identification of bottlenecks
24
TIMELINESS TEMPLATE
• Actions plan for improvements
• Try to focus also on long term goals
25
TIMELINESS TEMPLATE
“FP supports the promotion of best practicesfor improving data quality”.
NEW TASKS – 5.6.
26
▪ Data domains in a countrycooperating in a coordinatedway with common goals.
▪ Define and improve yourdata quality
DATA QUALITY
27
28
DATA QUALITY TEMPLATE
DATA QUALITY TEMPLATE
29• Find initiatives or action to improve the quality of data
DATA QUALITY TEMPLATE
30
DATA QUALITY TEMPLATE
31
32
5.5 and 5.6. CURRENT STATUS
• Share with us what have youmanaged to do so far?
• Give us please feedback on datatasks.
Training and support actions
33
“FP compiles a list of additional training needsrelated to data collection and datasubmission” .
NEW TASKS – 5.9.
34
• Aim of the training is the transfer of knowledge and skills inthe area of EFSA data collection to data provider level.
• Provide a training also to industry/research organisationand encourage them to transmit the data.
• Establish a relationship with stakeholders (academia,industry etc.) to stimulate data submission to EFSA e.g adhoc calls for specific data.
• The cooperation of the data providers with IT programmerof a national data systems to ensure adaptation for the newvalidation rules, business rules etc.
TRAINING AT NATIONAL LEVEL
35
• It is desirable to ensure the continuity of involvement indata collection and data reporting of the experts(Network member, reporting officer, data providers)trained.
• A national network of experts involved in data collectionand data reporting to ensure the circulation ofinformation provided by EFSA to the Network member andreporting officer.
TRAINING AT NATIONAL LEVEL
36
TRAINING AT NATIONAL LEVEL
37
• Use the platform for communication and exchange of views.
• Discuss with colleagues.
TRAINING AT NATIONAL LEVEL
38
Collect the needs
Group the needs
Structure the collected information according to the area
TRAINING AT NATIONAL LEVEL
39
Coordinate the organization of training
5.9. TRAINING NEEDS - QUESTIONS
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“FP in close cooperation with networkrepresentatives and EFSA to provide datastewardship support to EFSA"
i.e. providing technical support and know-how on data transmission to EFSA usingMicrosoft TEAMS community managed by EFSA, and using the spirit ofcrowdsourcing
NEW TASKS – 5.10.
41
42
• FP supports having a process in place which capturesawareness of upcoming changes in national resources,“on boarding” of new resources and ensure proactivecommunication on upcoming changes to EFSA in advanceof opening data collections.
DATA STEWARDSHIP SUPPORT
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• Supports having a process in place forengagement on questions and issuesrelated to ongoing data collectionswhich are placed inTEAMS/SHAREPOINT.
• Comments on revisions of the Guidance,registration of national data providersand reporting officers.
• Engage with other data providers toanswer your question.
• Provide solution.
MICROSOFT TEAMS
▪Microsoft Teams community
(FP, ChemMon, Zoonosis,..etc.)
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MICROSOFT TEAMS
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MICROSOFT TEAMS
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