Methodological Assessment of Data Suitability for Defect Prediction Article Swipe
Peter Schlegel
,
Daniel Buschmann
,
Max Ellerich
,
Robert Schmitt
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.12776/qip.v24i2.1443
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.12776/qip.v24i2.1443
Purpose: This paper provides a domain specific concept to assess data suitability of various data sources along the production chain for defect prediction.Methodology/Approach: A seven-phase methodology is developed in which the data suitability for defect prediction in interlinked production steps is assessed. For this purpose, the manufacturing process is mapped and potential influencing variables on the origin of defects are identified. The available data is evaluated and quantified with regard to the criteria relevancy, completeness, appropriate amount of data, accessibility and interpretability. The individual assessments are then visualized in an overview, gaps in data acquisition are identified and needs for action are derived.Findings: The research shows a seven-phase methodology to systematically assess data suitability for defect prediction and identify data gaps in interlinked production steps.Research Limitation/implication: This research is limited to the analysis of contextual data quality for the use case of defect prediction. Other data analytics applications or processes outside of manufacturing are not included.Originality/Value of paper: The paper provides a new approach to identify gaps in data acquisition by systematically assessing data suitability for defect prediction and deducting needs for action. The accuracy of predictive defect models is then to be improved by the subsequent optimization of the data basis.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.12776/qip.v24i2.1443
- https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217
- OA Status
- diamond
- Cited By
- 4
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3046403849
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3046403849Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.12776/qip.v24i2.1443Digital Object Identifier
- Title
-
Methodological Assessment of Data Suitability for Defect PredictionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-07-31Full publication date if available
- Authors
-
Peter Schlegel, Daniel Buschmann, Max Ellerich, Robert SchmittList of authors in order
- Landing page
-
https://doi.org/10.12776/qip.v24i2.1443Publisher landing page
- PDF URL
-
https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217Direct OA link when available
- Concepts
-
Interpretability, Production (economics), Computer science, Data mining, Artificial intelligence, Economics, MacroeconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 2, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
- References (count)
-
32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3046403849 |
|---|---|
| doi | https://doi.org/10.12776/qip.v24i2.1443 |
| ids.doi | https://doi.org/10.12776/qip.v24i2.1443 |
| ids.mag | 3046403849 |
| ids.openalex | https://openalex.org/W3046403849 |
| fwci | 0.74285303 |
| type | article |
| title | Methodological Assessment of Data Suitability for Defect Prediction |
| biblio.issue | 2 |
| biblio.volume | 24 |
| biblio.last_page | 185 |
| biblio.first_page | 170 |
| topics[0].id | https://openalex.org/T11719 |
| topics[0].field.id | https://openalex.org/fields/18 |
| topics[0].field.display_name | Decision Sciences |
| topics[0].score | 0.9988999962806702 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1803 |
| topics[0].subfield.display_name | Management Science and Operations Research |
| topics[0].display_name | Data Quality and Management |
| topics[1].id | https://openalex.org/T11891 |
| topics[1].field.id | https://openalex.org/fields/14 |
| topics[1].field.display_name | Business, Management and Accounting |
| topics[1].score | 0.9954000115394592 |
| topics[1].domain.id | https://openalex.org/domains/2 |
| topics[1].domain.display_name | Social Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1404 |
| topics[1].subfield.display_name | Management Information Systems |
| topics[1].display_name | Big Data and Business Intelligence |
| topics[2].id | https://openalex.org/T13690 |
| topics[2].field.id | https://openalex.org/fields/36 |
| topics[2].field.display_name | Health Professions |
| topics[2].score | 0.9017000198364258 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3607 |
| topics[2].subfield.display_name | Medical Laboratory Technology |
| topics[2].display_name | Quality and Safety in Healthcare |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2781067378 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5696004033088684 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q17027399 |
| concepts[0].display_name | Interpretability |
| concepts[1].id | https://openalex.org/C2778348673 |
| concepts[1].level | 2 |
| concepts[1].score | 0.49597272276878357 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q739302 |
| concepts[1].display_name | Production (economics) |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.4481125771999359 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C124101348 |
| concepts[3].level | 1 |
| concepts[3].score | 0.41481828689575195 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[3].display_name | Data mining |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.269844651222229 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C162324750 |
| concepts[5].level | 0 |
| concepts[5].score | 0.0 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[5].display_name | Economics |
| concepts[6].id | https://openalex.org/C139719470 |
| concepts[6].level | 1 |
| concepts[6].score | 0.0 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q39680 |
| concepts[6].display_name | Macroeconomics |
| keywords[0].id | https://openalex.org/keywords/interpretability |
| keywords[0].score | 0.5696004033088684 |
| keywords[0].display_name | Interpretability |
| keywords[1].id | https://openalex.org/keywords/production |
| keywords[1].score | 0.49597272276878357 |
| keywords[1].display_name | Production (economics) |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.4481125771999359 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/data-mining |
| keywords[3].score | 0.41481828689575195 |
| keywords[3].display_name | Data mining |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.269844651222229 |
| keywords[4].display_name | Artificial intelligence |
| language | en |
| locations[0].id | doi:10.12776/qip.v24i2.1443 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2764416040 |
| locations[0].source.issn | 1335-1745, 1338-984X |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1335-1745 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Quality Innovation Prosperity |
| locations[0].source.host_organization | https://openalex.org/P4310314440 |
| locations[0].source.host_organization_name | Technical University of Košice |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310314440 |
| locations[0].source.host_organization_lineage_names | Technical University of Košice |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Quality Innovation Prosperity |
| locations[0].landing_page_url | https://doi.org/10.12776/qip.v24i2.1443 |
| locations[1].id | pmh:oai:doaj.org/article:4a57263da3ff4e00a9e7a20a5dd87e2b |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Kvalita Inovácia Prosperita, Vol 24, Iss 2 (2020) |
| locations[1].landing_page_url | https://doaj.org/article/4a57263da3ff4e00a9e7a20a5dd87e2b |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5069438955 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-0906-4644 |
| authorships[0].author.display_name | Peter Schlegel |
| authorships[0].countries | DE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[0].affiliations[0].raw_affiliation_string | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[0].institutions[0].id | https://openalex.org/I887968799 |
| authorships[0].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[0].institutions[0].country_code | DE |
| authorships[0].institutions[0].display_name | RWTH Aachen University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Peter Schlegel |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[1].author.id | https://openalex.org/A5018196105 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-8363-1331 |
| authorships[1].author.display_name | Daniel Buschmann |
| authorships[1].countries | DE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[1].affiliations[0].raw_affiliation_string | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[1].institutions[0].id | https://openalex.org/I887968799 |
| authorships[1].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[1].institutions[0].country_code | DE |
| authorships[1].institutions[0].display_name | RWTH Aachen University |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Daniel Buschmann |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[2].author.id | https://openalex.org/A5044717416 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-9113-0203 |
| authorships[2].author.display_name | Max Ellerich |
| authorships[2].countries | DE |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[2].affiliations[0].raw_affiliation_string | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[2].institutions[0].id | https://openalex.org/I887968799 |
| authorships[2].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[2].institutions[0].country_code | DE |
| authorships[2].institutions[0].display_name | RWTH Aachen University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Max Ellerich |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[3].author.id | https://openalex.org/A5045094368 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-0011-5962 |
| authorships[3].author.display_name | Robert Schmitt |
| authorships[3].countries | DE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I887968799 |
| authorships[3].affiliations[0].raw_affiliation_string | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| authorships[3].institutions[0].id | https://openalex.org/I887968799 |
| authorships[3].institutions[0].ror | https://ror.org/04xfq0f34 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I887968799 |
| authorships[3].institutions[0].country_code | DE |
| authorships[3].institutions[0].display_name | RWTH Aachen University |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Robert H. Schmitt |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen Aachen, Germany |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Methodological Assessment of Data Suitability for Defect Prediction |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11719 |
| primary_topic.field.id | https://openalex.org/fields/18 |
| primary_topic.field.display_name | Decision Sciences |
| primary_topic.score | 0.9988999962806702 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1803 |
| primary_topic.subfield.display_name | Management Science and Operations Research |
| primary_topic.display_name | Data Quality and Management |
| related_works | https://openalex.org/W4289856193, https://openalex.org/W2295414992, https://openalex.org/W2792591449, https://openalex.org/W2348097614, https://openalex.org/W4240328967, https://openalex.org/W2169048944, https://openalex.org/W3116911201, https://openalex.org/W2347219288, https://openalex.org/W3121299932, https://openalex.org/W2294501020 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2023 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2021 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2020 |
| counts_by_year[2].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | doi:10.12776/qip.v24i2.1443 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2764416040 |
| best_oa_location.source.issn | 1335-1745, 1338-984X |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1335-1745 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Quality Innovation Prosperity |
| best_oa_location.source.host_organization | https://openalex.org/P4310314440 |
| best_oa_location.source.host_organization_name | Technical University of Košice |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310314440 |
| best_oa_location.source.host_organization_lineage_names | Technical University of Košice |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Quality Innovation Prosperity |
| best_oa_location.landing_page_url | https://doi.org/10.12776/qip.v24i2.1443 |
| primary_location.id | doi:10.12776/qip.v24i2.1443 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2764416040 |
| primary_location.source.issn | 1335-1745, 1338-984X |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1335-1745 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Quality Innovation Prosperity |
| primary_location.source.host_organization | https://openalex.org/P4310314440 |
| primary_location.source.host_organization_name | Technical University of Košice |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310314440 |
| primary_location.source.host_organization_lineage_names | Technical University of Košice |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.qip-journal.eu/index.php/QIP/article/download/1443/1217 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Quality Innovation Prosperity |
| primary_location.landing_page_url | https://doi.org/10.12776/qip.v24i2.1443 |
| publication_date | 2020-07-31 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W2884090605, https://openalex.org/W2156495583, https://openalex.org/W4242328596, https://openalex.org/W2981480776, https://openalex.org/W2004291985, https://openalex.org/W6888896187, https://openalex.org/W935072310, https://openalex.org/W2800250618, https://openalex.org/W2293914298, https://openalex.org/W2899109902, https://openalex.org/W4232684334, https://openalex.org/W4205699531, https://openalex.org/W2758197747, https://openalex.org/W2015550419, https://openalex.org/W1378570, https://openalex.org/W2966267176, https://openalex.org/W4381304672, https://openalex.org/W4241065697, https://openalex.org/W2909763883, https://openalex.org/W6888419517, https://openalex.org/W3008273671, https://openalex.org/W2064540392, https://openalex.org/W2722925682, https://openalex.org/W1981000344, https://openalex.org/W1567491469, https://openalex.org/W4205962651, https://openalex.org/W1870959433, https://openalex.org/W2480664052, https://openalex.org/W2128128127, https://openalex.org/W3143468379, https://openalex.org/W3014053438, https://openalex.org/W2201244945 |
| referenced_works_count | 32 |
| abstract_inverted_index.A | 23 |
| abstract_inverted_index.a | 4, 106, 161 |
| abstract_inverted_index.an | 89 |
| abstract_inverted_index.be | 192 |
| abstract_inverted_index.by | 170, 194 |
| abstract_inverted_index.in | 28, 36, 88, 92, 121, 167 |
| abstract_inverted_index.is | 26, 40, 48, 64, 128, 189 |
| abstract_inverted_index.of | 12, 57, 77, 133, 141, 151, 156, 185, 198 |
| abstract_inverted_index.on | 54 |
| abstract_inverted_index.or | 148 |
| abstract_inverted_index.to | 8, 70, 109, 130, 164, 191 |
| abstract_inverted_index.For | 42 |
| abstract_inverted_index.The | 61, 82, 103, 158, 183 |
| abstract_inverted_index.and | 50, 66, 80, 97, 117, 178 |
| abstract_inverted_index.are | 59, 85, 95, 101, 153 |
| abstract_inverted_index.for | 20, 33, 99, 114, 137, 175, 181 |
| abstract_inverted_index.new | 162 |
| abstract_inverted_index.not | 154 |
| abstract_inverted_index.the | 17, 30, 45, 55, 71, 131, 138, 195, 199 |
| abstract_inverted_index.use | 139 |
| abstract_inverted_index.This | 1, 126 |
| abstract_inverted_index.case | 140 |
| abstract_inverted_index.data | 10, 14, 31, 63, 93, 112, 119, 135, 145, 168, 173, 200 |
| abstract_inverted_index.gaps | 91, 120, 166 |
| abstract_inverted_index.then | 86, 190 |
| abstract_inverted_index.this | 43 |
| abstract_inverted_index.with | 68 |
| abstract_inverted_index.Other | 144 |
| abstract_inverted_index.along | 16 |
| abstract_inverted_index.chain | 19 |
| abstract_inverted_index.data, | 78 |
| abstract_inverted_index.needs | 98, 180 |
| abstract_inverted_index.paper | 2, 159 |
| abstract_inverted_index.shows | 105 |
| abstract_inverted_index.steps | 39 |
| abstract_inverted_index.which | 29 |
| abstract_inverted_index.action | 100 |
| abstract_inverted_index.amount | 76 |
| abstract_inverted_index.assess | 9, 111 |
| abstract_inverted_index.basis. | 201 |
| abstract_inverted_index.defect | 21, 34, 115, 142, 176, 187 |
| abstract_inverted_index.domain | 5 |
| abstract_inverted_index.mapped | 49 |
| abstract_inverted_index.models | 188 |
| abstract_inverted_index.origin | 56 |
| abstract_inverted_index.paper: | 157 |
| abstract_inverted_index.regard | 69 |
| abstract_inverted_index.action. | 182 |
| abstract_inverted_index.concept | 7 |
| abstract_inverted_index.defects | 58 |
| abstract_inverted_index.limited | 129 |
| abstract_inverted_index.outside | 150 |
| abstract_inverted_index.process | 47 |
| abstract_inverted_index.quality | 136 |
| abstract_inverted_index.sources | 15 |
| abstract_inverted_index.various | 13 |
| abstract_inverted_index.Purpose: | 0 |
| abstract_inverted_index.accuracy | 184 |
| abstract_inverted_index.analysis | 132 |
| abstract_inverted_index.approach | 163 |
| abstract_inverted_index.criteria | 72 |
| abstract_inverted_index.identify | 118, 165 |
| abstract_inverted_index.improved | 193 |
| abstract_inverted_index.provides | 3, 160 |
| abstract_inverted_index.purpose, | 44 |
| abstract_inverted_index.research | 104, 127 |
| abstract_inverted_index.specific | 6 |
| abstract_inverted_index.analytics | 146 |
| abstract_inverted_index.assessed. | 41 |
| abstract_inverted_index.assessing | 172 |
| abstract_inverted_index.available | 62 |
| abstract_inverted_index.deducting | 179 |
| abstract_inverted_index.developed | 27 |
| abstract_inverted_index.evaluated | 65 |
| abstract_inverted_index.overview, | 90 |
| abstract_inverted_index.potential | 51 |
| abstract_inverted_index.processes | 149 |
| abstract_inverted_index.variables | 53 |
| abstract_inverted_index.contextual | 134 |
| abstract_inverted_index.identified | 96 |
| abstract_inverted_index.individual | 83 |
| abstract_inverted_index.prediction | 35, 116, 177 |
| abstract_inverted_index.predictive | 186 |
| abstract_inverted_index.production | 18, 38, 123 |
| abstract_inverted_index.quantified | 67 |
| abstract_inverted_index.relevancy, | 73 |
| abstract_inverted_index.subsequent | 196 |
| abstract_inverted_index.visualized | 87 |
| abstract_inverted_index.acquisition | 94, 169 |
| abstract_inverted_index.appropriate | 75 |
| abstract_inverted_index.assessments | 84 |
| abstract_inverted_index.identified. | 60 |
| abstract_inverted_index.influencing | 52 |
| abstract_inverted_index.interlinked | 37, 122 |
| abstract_inverted_index.methodology | 25, 108 |
| abstract_inverted_index.prediction. | 143 |
| abstract_inverted_index.seven-phase | 24, 107 |
| abstract_inverted_index.suitability | 11, 32, 113, 174 |
| abstract_inverted_index.applications | 147 |
| abstract_inverted_index.optimization | 197 |
| abstract_inverted_index.accessibility | 79 |
| abstract_inverted_index.completeness, | 74 |
| abstract_inverted_index.manufacturing | 46, 152 |
| abstract_inverted_index.steps.Research | 124 |
| abstract_inverted_index.systematically | 110, 171 |
| abstract_inverted_index.derived.Findings: | 102 |
| abstract_inverted_index.interpretability. | 81 |
| abstract_inverted_index.Limitation/implication: | 125 |
| abstract_inverted_index.included.Originality/Value | 155 |
| abstract_inverted_index.prediction.Methodology/Approach: | 22 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5299999713897705 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.75102517 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |