| dc.contributor.other | Mckenna, Lucy Mary | en |
| dc.date.accessioned | 2021-05-10T08:22:26Z | |
| dc.date.available | 2021-05-10T08:22:26Z | |
| dc.date.issued | 2019 | en |
| dc.date.submitted | 2019 | en |
| dc.identifier.citation | McKenna, L. Debruyne, C. & O'Sullivan, D., A Modified AIM Quality Questionnaire, 2019 | en |
| dc.identifier.other | N | en |
| dc.description | PUBLISHED | en |
| dc.description | This is a modified version of the AIM Quality (AIMQ) questionnaire (Lee, Strong, Kahn & Wang, 2002). The AIMQ questionnaire consists of 65 statements regarding DQ about which the user rates their level of agreement on a scale of 0 (disagree) to 10 (agree). The AIMQ measures DQ according to 14 quality dimensions: Appropriate Amount, Believability, Completeness, Concise Representation, Consistent Representation, Ease of Operation, Free of Error, Interpretability, Objectivity, Relevancy, Reputation, Security, Timeliness, and Understandability. In terms of scoring, higher ratings indicate a more positive perception of the statements (note that scores for negative statements are reversed). This modified version includes a subset of 25 statements and was used in the PhD thesis - NAISC-L: A Linked Data Interlinking Framework for Libraries, Archives and Museums.
References:
Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information & Management, 40(2), 133-146.
McKenna Lucy Mary, NAISC-L: A Linked Data Interlinking Framework for Libraries, Archives and Museums, Trinity College Dublin.School of Computer Science & Statistics, 2020 (http://hdl.handle.net/2262/94131). | en |
| dc.language.iso | en | en |
| dc.rights | N | en |
| dc.title | A Modified AIM Quality Questionnaire | en |
| dc.type | Test or assessment | en |
| dc.type.supercollection | scholarly_publications | en |
| dc.identifier.peoplefinderurl | http://people.tcd.ie/mckennl3 | en |
| dc.identifier.rssinternalid | 228975 | en |
| dc.rights.ecaccessrights | openAccess | |
| dc.relation.source | MCKENNA, LUCY MARY, NAISC-L: A Linked Data Interlinking Framework for Libraries, Archives and Museums, Trinity College Dublin.School of Computer Science & Statistics, 2020 | en |
| dc.relation.source | Lee, Y. W., Strong, D. M., Kahn, B. K., & Wang, R. Y. (2002). AIMQ: a methodology for information quality assessment. Information & Management, 40(2), 133-146. | en |
| dc.subject.TCDTag | DATA ANALYSIS | en |
| dc.subject.TCDTag | DATA QUALITY | en |
| dc.relation.sourceuri | http://hdl.handle.net/2262/94131 | en |
| dc.status.accessible | N | en |
| dc.identifier.uri | http://hdl.handle.net/2262/96220 | |
