PG25331 Certificate in Science in Open Data Practice NFQ Level 9 Assignments Ireland 

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01/02/2024

NFQ Assignment Answers

Level 9

The PG25331 Certificate in Science in Open Data Practice, placed at NFQ Level 9, digs into how Irish and European research bodies keep their data open, safe, and useful. It sits somewhere between policy and hands-on work. People learn to balance transparency with care — a tricky mix when licences, ethics and formats don’t always line up.

The award leans heavily on Research Data Management (RDM), FAIR principles, and those bits of law that quietly shape daily research: the Open Data Directive (EU 2019/1024), GDPR, the Data Protection Act 2018 (Ireland), and the Freedom of Information Act 2014. Students move through real-world tools — Zenodo, Figshare, OSF, even old-school CSV files — to understand what happens when theory meets a half-filled metadata sheet.

It’s a pragmatic course. Less talk, more fixing. One learns how DCAT-AP IE, Dublin Core and DataCite profiles connect; how an ORCID can anchor a dataset; how an audit log stops data from quietly slipping out of trace. The programme, tied to NORF and HEA guidance, keeps a tight ethical footing. All examples that follow are anonymised, fictional, and drawn for instruction only.

Online Help With Your PG25331 Certificate in Science in Open Data Practice Continuous Assessment (20%)

This 20 per cent Continuous Assessment tests the small, fussy habits that make RDM real. It looks dull on paper — metadata fields, file names, consent forms — but that’s where research either holds or leaks.

For the sample task, an anonymised “Urban Air Quality Indicators 2022–2023” dataset was used. At 08:12, one field, “data coverage note,” sat blank. It got fixed later that morning after a quick coffee and a Slack nudge from a teammate. The file existed in both CSV and GeoJSON; the first export carried a stray semicolon as a delimiter. A minor thing, but it broke the import script until I checked through OpenRefine.

Mini Checklist

• FAIR baseline scored with a 10-point grid.

• Metadata validated against Dublin Core essentials.

• Consent confirmed — no personal data inside.

• Licence picked — CC BY 4.0, after testing ODC-BY and ODbL.

• Repository chosen — Zenodo community space.

• Quick note on provenance and data-quality routine added.

A slice from the licensing log looked like this:

That table told its own story — each licence promising openness but with hidden chores.
During the FAIR scoring, completeness sat around 92 %, timeliness 87 %, and accuracy ≈ 93 %. Not perfect, but believable. After a DOI was minted at 16:42 and linked to the creator’s ORCID, the score nudged up a bit.

Here’s another small grid from the audit sheet:

Midway through, a mismatch cropped up between “creator” in Dublin Core and “publisher” in DCAT-AP IE. It took twenty minutes and two messages to resolve, logged as schema revision 1.1.

The FAIR baseline started at 7 out of 10. After cleaning metadata and adding that DOI, it reached 8.2 — respectable, not shiny.

Brief Reflection

To be fair, the exercise showed how messy “open” can be. A missing comma, a lazy field name, or a licence badge half-wrong can waste a full day. In practice, RDM isn’t glamourous work. It’s the quiet repetition that keeps research transparent. The audit made it clear: openness isn’t just sharing, it’s owning the small details that let others trust what’s shared.

Instant Solved Assignments Available For NFQ Level 9 Minor Award

Students at this level often face late nights balancing code, policy, and ethics forms. Seeing a solved sample helps steady the pace. Our exemplars walk through real-feeling outputs — a FAIR-mapped GeoJSON, a DCAT-AP IE snippet, even a corrected CSV header.

They show how to match GDPR lawful bases with consent sheets, when to pick Zenodo over OSF, and how long DOIs keep active before refresh. Each sample carries version notes and reviewer comments so learners can see the reasoning, not just the answer.

All of it stays within Irish and EU frameworks — the Open Data Directive 2019/1024, NORF 2023 Plan, and HEA Guidance on Open Research. It’s practical learning: the kind that sticks after the assignment grade fades.

PG25331 Certificate in Science in Open Data Practice Skills Demonstration Assessment (80%)

The Skills Demonstration carries the heavier weight — 80 %. It asks for proof that open-data principles can live in daily work, not just sit in reports. The process followed a plan → do → check → act rhythm, typical of RDM cycles.

A small open dataset was prepared from fictionalised transport metrics collected across three Irish regions. Nothing personal, no identifiers. Files were stored in Parquet for analysis and CSV for publication. An internal DataCite record and a DCAT-AP IE profile were created, both checked through data.gov.ie’s validation tool. The DOI minted cleanly, though the ROR code for one research group had to be fixed twice before validation held.

After week three, a simple run chart of downloads bent upwards — roughly +22 % over baseline — once the schema errors were patched. Not perfect, but enough to show reuse was happening.
All along, every action was logged in a provenance tracker using a Markdown sheet rather than formal software. Hand-typed, timestamped. It kept the rhythm human.

Assignment Activity 1: Perform research and analysis activities in the field of Open Data Practice related to Research Data Management

This stage focused on comparing metadata standards — Dublin Core, DataCite, and DCAT-AP IE — and deciding when each suits a given context.

In practice, most Irish institutional repositories (e.g., TU Dublin ARROW or UL LRA) rely on Dublin Core, while Zenodo and OSF lean on DataCite. The public catalogue data.gov.ie demands DCAT-AP IE.
So it turned out that a small crosswalk file was needed — ten lines of XML mapping — to keep fields consistent.

A quick methods note was written: literature from HEA, EOSC and NORF portals between 2020 and 2024 was reviewed; inclusion limited to repositories with at least 50 datasets; exclusion where metadata was proprietary or non-English. The main limitation, honestly, was time — script debugging ate a full evening.

This part confirmed that alignment matters more than fancy software. A 30-minute schema check can save weeks of lost discoverability.

Assignment Activity 2: Critically assess and evaluate sustainability issues and the ethical risks and impacts associated with Open Data solutions, with a focus on Research Data Management considerations

Sustainability in Open Data lives on four legs — financial, technical, organisational, and environmental. Each wobbles differently.

Financially, DOI minting and long-term storage carry hidden fees. The project budget had a €320 cap for repository costs, which almost ran out after the third version deposit. Technically, the CSV format may vanish sooner than we think; Parquet or Arrow look safer. Organisationally, stewardship turns fragile when staff move on. And the environmental piece — yes, servers hum all night, and storage energy adds up.

To steady the ethics discussion, an Ethics Grid was drafted:

During peer review, one field — “region_code” — was flagged for potential re-identification. It was pseudonymised after a brief team debate at 19:10 that evening.

Ethical reflection ran deep. To be fair, it’s easy to speak of openness and forget the humans behind rows of data. The test was to keep transparency without exposure.

Assignment Activity 3: Synthesize and communicate the opportunity of Open Data practices to underpin strategic decisions to key stakeholders

The communication task turned theory outward. Stakeholders came from across the Irish research scene: policy makers, HEIs, SMEs, NGOs, and civic tech groups. Each cared for a different slice — policy wanted compliance, SMEs wanted efficiency, NGOs wanted fairness.

A one-slide summary outline was used during briefing:

• Headline: Open Data can cut duplication and raise research visibility.

• Metric: FAIR score +18 % after standardisation.

• Benefit: Saves roughly €1 200 per project through reuse.

• Local Tie-in: Supports NORF Open Research Plan 2023.

• Next Step: Run shared DMP workshops across HEIs.

A short fictionalised Irish case helped make it real. The West Coast Transport Pilot, run by a mid-size county council, released public transport punctuality data. Once opened, a local start-up used it to build a commuter dashboard. Within three months, the council tweaked bus timetables, cutting average waiting times by about 11 %. Not flawless, but solid proof that small datasets can shape public planning.

Each stakeholder got the message differently: policy people got a compliance chart; SME reps saw potential for product design; community groups heard about fairness and reuse. In practice, tailoring tone did more than graphs ever could.

Assignment Activity 4: Select and employ advanced and emerging open knowledge practices and tools to facilitate knowledge generation

The later stage turned a bit technical. The focus shifted from cleaning data to building structure and interoperability.
Several tools were tested: CKAN for cataloguing, OpenRefine for metadata repair, and a SPARQL endpoint spun up to query across two linked datasets. One dataset carried air-quality metrics; the other, population density from an open CSO source.

The first query failed — a namespace clash in prefixes. Fixed after a long tea break and one missed semicolon. The combined output later fed into a Parquet file, used to test Frictionless Data validation.

To be fair, none of these worked perfectly. But together, they taught the meaning of interoperability — getting bits of data to actually talk.
A small internal training note was drafted too: one hour on metadata quality for research assistants, half hour on CC licensing, and a 15-minute slot on PID minting. A few sticky notes were left on screens with reminders like “Always test schema before upload”.

Assignment Activity 5: Formulate, design, assess, and implement Open Data management plans based on Open Science and FAIR (Findable, Accessible, Interoperable, Reusable) principles

The Data Management Plan (DMP) was built like a living map — one that could flex as datasets evolved. It followed the structure used in EOSC templates and NORF guidelines.

Data Summary: Fictionalised Irish air-quality readings and transport punctuality logs (no personal data).
Standards: DCAT-AP IE + DataCite schema; UTF-8 encoding; GeoJSON for spatial layers.
Documentation/Metadata: Plain-language README and machine-readable JSON-LD.
Storage/Backup: Institutional drive mirrored nightly to Zenodo.
Legal/Ethics: GDPR-compliant, CC BY 4.0 licence, retention capped at 5 years.
Sharing/Access: Open immediately after project close; embargo allowed for QA.
Reuse Licence: CC BY 4.0 displayed as a badge on the landing page.
Responsibilities: The Data steward signs off before any release.
Resources: Repository credits pre-approved; two-hour monthly QA slot.
Review: FAIR re-assessment every six months.

A compact mapping of FAIR actions looked like this:

The FAIR baseline started modestly. After metadata clean-up and one corrected DOI, it improved to roughly 8/10 overall.
In practice, writing the DMP felt like half admin, half ethics — but it anchored the project. So it turned out that documentation is what truly makes data open.

Assignment Activity 6: Demonstrate a critical understanding of the use of Open Data in various research, business, and technological contexts

At this point, the view widened. Open Data wasn’t just a research ideal; it powered business dashboards, policy pilots, and even machine-learning models.

In research, it enabled replication — one PhD student reused the same dataset to test pollutant forecasting under new weather algorithms.
In business, open ESG data allowed local SMEs to benchmark supply-chain sustainability, feeding into procurement decisions.
In technology, the dataset became part of a training corpus for bias testing; the model card recorded precision drift of ±2.8 % after retraining.

Not everything worked smoothly. Licensing ambiguity cropped up when merging data with an ODbL dataset. Sampling bias appeared — Western counties were under-represented.
But, to be fair, the imperfections were the learning. Data quality drifts, schemas shift, and yet the collaborative habit stays firm.

Looking forward, the next step seems to be synthetic data and privacy-preserving sharing. Both could let Irish agencies publish insights without exposing raw subjects. The conversation’s already happening inside NORF meetings. The key, as ever, is trust — built slowly, dataset by dataset.

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If you’re tackling this Level 9 award and feeling lost between FAIR scores, licences, and ethical clauses — you’re not alone. Many postgraduate learners in Ireland reach out for steady guidance that feels human, not automated. Our experts combine policy know-how with field experience, helping you shape data plans, metadata audits, and ethical statements that read right the first time. With discreet support and a strong eye for Irish and EU compliance, we offer complete reliability — from tight deadlines to confidentiality. Whether you need detailed RDM mapping, FAIR self-assessment, or data-ethics commentary, our online assignment help in Ireland connects you with real academic professionals. Every draft follows authentic frameworks and honest Irish standards under our professional university assignment help services. For more complex sections, you’ll have direct input from our top PhD dissertation writers, ensuring scholarly accuracy without losing your own tone. The result is work that feels genuinely yours, meets NFQ expectations, and passes scrutiny every time.