Purchase Orders Over €20,000 Q4 2016

Spending records

Payment date^*	Supplier	Description	Kind	Amount
31 Dec 2016	ELSEVIER B V	Library Supplies & Services	Purchase Order	€106,495.06
31 Dec 2016	BESTSOFT CONSULTING	Computer equipment and services	Purchase Order	€47,400.00
31 Dec 2016	CAVEO INFORMATION SYSTEMS LTD	Computer equipment and services	Purchase Order	€29,197.00
31 Dec 2016	UNIVERSITY COLLEGE DUBLIN (UCD)	Legal & professional Services	Purchase Order	€23,940.00
31 Dec 2016	ORBIS LABSYSTEMS LTD	Computer equipment and services	Purchase Order	€33,120.00
31 Dec 2016	CLARIVATE ANALYTICS (US) LLC	Library Supplies & Services	Purchase Order	€141,084.53
31 Dec 2016	VODAFONE ECS/INTERFUSION	Telecommunications	Purchase Order	€32,228.56
31 Dec 2016	AIRSPEED TELECOM	Telecommunications	Purchase Order	€26,400.00
31 Dec 2016	DELL COMPUTER (IRL) DEPARTMENT	Computer equipment and services	Purchase Order	€24,360.00
12 Dec 2016	ACORN ADVISORY SERVICES LTD	Research Services	Purchase Order	€36,000.00
12 Dec 2016	QIAGEN LTD	Laboratory Supplies & Services	Purchase Order	€66,000.00
11 Nov 2016	BORD BIA	Research Services	Purchase Order	€30,000.00
10 Nov 2016	SOUTHERN SCIENTIFIC SERVICES LTD.	Research Services	Purchase Order	€20,671.23
11 Oct 2016	UIC GMBH	Laboratory Supplies & Services	Purchase Order	€37,310.00
10 Oct 2016	CAPITA CUSTOMER SOLUTIONS(PREV	Legal & professional Services	Purchase Order	€39,000.00

^* Payment date may be the end of the reporting quarter when the entity does not publish an exact date.

How to read these figures

These are reported values from published purchase order and payment records — not verified cash paid, and not total spending by this organisation. A row may be a purchase order, a payment, or another reported transaction; the source files often do not say which.

Coverage and quality vary. Some fields are blank, supplier names are free text (the same firm can appear under many labels), and descriptions are inconsistent rather than a controlled taxonomy. An amount alone says nothing about value for money and it may or may not include VAT.

Records are retrieved from each organisation’s published files such as spreadsheets, PDFs, and other formats of uneven quality. Extraction techniques (including automated parsing) can introduce gaps, misreads, or incomplete rows when source layout or quality is poor. Treat the data as a starting point for investigation, not a definitive ledger.

Here is a project that encountered similar issues