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Paper Citation Record · LEDGER

Towards Next Generation Data Engineering Pipelines

As of 10 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 0 inbound Pith citation observations for arXiv:2507.13892.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.13892 v2

Coverage vector

measured 82 of 82 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:18:56.509967Z

measured 82 of 82 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

82 of 82 outbound references displayed

  • verified exact24
  • verified fuzzy13
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch7

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 40c34b85-378e-48a1-8bad-d04fcb325c01 · outbound

This paper cites Four Generations in Data Engineering for Data Science.

Towards Next Generation Data Engineering Pipelines Four Generations in Data Engineering for Data Science

Reference 1

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Observation 94a77ea5-d14d-4680-824a-b6af53a10d4c · outbound

This paper cites The Challenges of Data Quality and Data Quality Assessment in the Big Data Era.

Towards Next Generation Data Engineering Pipelines The Challenges of Data Quality and Data Quality Assessment in the Big Data Era

Reference 2

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Observation 0756e37d-8d62-40a0-8369-dee0f354f00b · outbound

This paper cites GouDa - generation of universal data sets: improving analysis and evaluation of data preparation pipelines.

Towards Next Generation Data Engineering Pipelines GouDa - generation of universal data sets: improving analysis and evaluation of data preparation pipelines

Reference 3

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Observation be4d4c17-5977-4445-915e-d37714b117ea · outbound

This paper cites Ilyas and Xu Chu.

Towards Next Generation Data Engineering Pipelines Ilyas and Xu Chu

Reference 4

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Observation 3864a190-32f4-4cae-a87a-5f0e1ae565d3 · outbound

This paper cites DERM: A reference model for data engineering.

Towards Next Generation Data Engineering Pipelines DERM: A reference model for data engineering

Reference 5

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Observation 5b8ace07-6085-4c52-bf0f-a0d79c3390ca · outbound

This paper cites A Survey of Big Data Pipeline Orchestration Tools from the Perspective of the DataCloud Project.

Towards Next Generation Data Engineering Pipelines A Survey of Big Data Pipeline Orchestration Tools from the Perspective of the DataCloud Project

Reference 6

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Observation cfe8edf3-12ac-4cdd-b125-85df3db5a476 · outbound

This paper cites Self-Awareness as a Prerequisite for Self-Adaptivity in Computing Systems.

Towards Next Generation Data Engineering Pipelines Self-Awareness as a Prerequisite for Self-Adaptivity in Computing Systems

Reference 7

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Observation ed754591-e80a-4aa4-ba26-197b39bc76a2 · outbound

This paper cites Data Processing Pipeline for Eye-Tracking Analysis.

Towards Next Generation Data Engineering Pipelines Data Processing Pipeline for Eye-Tracking Analysis

Reference 8

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source=arxiv_source observed=2026-08-06T16:18:42.645354Z digest=sha256:c35f570ee3926e9659fb2e5a29cb43aee900642b60a2e8881b68c331d967d3c5

Observation 18411631-4674-4216-94fd-20836d84c79a · outbound

This paper cites A unified representation and transformation of multi-model data using category theory.

Towards Next Generation Data Engineering Pipelines A unified representation and transformation of multi-model data using category theory

Reference 9

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Source-reported events for the cited work

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Observation 03427adb-de7d-4690-9928-e8d832e0ab27 · outbound

This paper cites Data Engineering for Data Science: Two Sides of the Same Coin.

Towards Next Generation Data Engineering Pipelines Data Engineering for Data Science: Two Sides of the Same Coin

Reference 10

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Observation 35cbfb20-48f1-4cf2-a1d5-a70eb1286c15 · outbound

This paper cites The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large.

Towards Next Generation Data Engineering Pipelines The Art and Practice of Data Science Pipelines: A Comprehensive Study of Data Science Pipelines In Theory, In-The-Small, and In-The-Large

Reference 11

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Observation 1133a35d-b3c8-4d56-876d-772f4b8247c7 · outbound

This paper cites What About the Data? A Mapping Study on Data Engineering for AI Systems.

Towards Next Generation Data Engineering Pipelines What About the Data? A Mapping Study on Data Engineering for AI Systems

Reference 12

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Observation 22544497-827b-4451-973d-86389909c620 · outbound

This paper cites NIST Big Data Interoperability Framework: Volume 1, Definitions.

Towards Next Generation Data Engineering Pipelines NIST Big Data Interoperability Framework: Volume 1, Definitions

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:43.105873Z digest=sha256:8212250748dc6e37a0a359a65fab7953d2254e87722d138e72667a5eec738cf6

Observation 5cb83274-5eb8-4ccb-b7a7-67cb84b7eaf6 · outbound

This paper cites Challenging Big Data Engineering: Positioning of Current and Future Development.

Towards Next Generation Data Engineering Pipelines Challenging Big Data Engineering: Positioning of Current and Future Development

Reference 14

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Observation f8181db7-1c87-4bf4-ade5-b1612e73ccd8 · outbound

This paper cites Atkinson, Michelle Galea, Tan Fong Ang, Paul Martin, and Jano I.

Towards Next Generation Data Engineering Pipelines Atkinson, Michelle Galea, Tan Fong Ang, Paul Martin, and Jano I

Reference 15

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source=arxiv_source observed=2026-08-06T16:18:43.321961Z digest=sha256:454eb1d5936cbe7937a57779f8550a9fdeaba0ea6cd9d734f566f1b8c2128462

Observation 2284ebe6-6d11-42f9-8c80-0430df611a18 · outbound

This paper cites Mahadi Hassan, Micah J.

Towards Next Generation Data Engineering Pipelines Mahadi Hassan, Micah J

Reference 16

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Observation 03340358-19f9-4b9d-aa6c-fbd902eae405 · outbound

This paper cites Parameswaran.

Towards Next Generation Data Engineering Pipelines Parameswaran

Reference 17

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Observation 7eada81a-f551-4013-8b0e-9237d1cbb8d8 · outbound

This paper cites BoostClean: Automated Error Detection and Repair for Machine Learning.

Towards Next Generation Data Engineering Pipelines BoostClean: Automated Error Detection and Repair for Machine Learning

Reference 18

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Observation dc47e29c-8163-4f83-94c6-cdc3ea9b55fd · outbound

This paper cites Ilyas, and Christopher R \' e.

Towards Next Generation Data Engineering Pipelines Ilyas, and Christopher R \' e

Reference 19

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Observation 30579814-a446-4425-8d80-726231629518 · outbound

This paper cites Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning.

Towards Next Generation Data Engineering Pipelines Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning

Reference 20

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Observation dbb3a155-d975-466f-8cdd-ef592cbb0c9b · outbound

This paper cites Ilyas, Mourad Ouzzani, Paolo Papotti, Nan Tang, and Yin Ye.

Towards Next Generation Data Engineering Pipelines Ilyas, Mourad Ouzzani, Paolo Papotti, Nan Tang, and Yin Ye

Reference 21

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Observation e010e491-a227-4679-be6e-4d6fafaed3f3 · outbound

This paper cites Data Preparation: A Survey of Commercial Tools.

Towards Next Generation Data Engineering Pipelines Data Preparation: A Survey of Commercial Tools

Reference 22

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Observation 9c392eb5-99bb-4c59-8074-255c977f6666 · outbound

This paper cites Ilyas, Mourad Ouzzani, Paolo Papotti, Michael Stonebraker, and Nan Tang.

Towards Next Generation Data Engineering Pipelines Ilyas, Mourad Ouzzani, Paolo Papotti, Michael Stonebraker, and Nan Tang

Reference 23

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Observation ab76c142-cba3-4f79-add8-72450a41f533 · outbound

This paper cites SAGA: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications.

Towards Next Generation Data Engineering Pipelines SAGA: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications

Reference 24

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Observation a6f41fb7-33f8-488d-b408-360c9512adf7 · outbound

This paper cites Lindstaedt, Arnab Phani, Benjamin Rath, Berthold Reinwald, Shafaq Siddiqui, and Sebastian Benjamin Wrede.

Towards Next Generation Data Engineering Pipelines Lindstaedt, Arnab Phani, Benjamin Rath, Berthold Reinwald, Shafaq Siddiqui, and Sebastian Benjamin Wrede

Reference 25

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Observation 067fa20d-4423-4ef7-bc5f-f58ef4e9cec0 · outbound

This paper cites From Cleaning before ML to Cleaning for ML.

Towards Next Generation Data Engineering Pipelines From Cleaning before ML to Cleaning for ML

Reference 26

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Observation ce0a72c7-5028-492a-91b2-fb02eedfdb1f · outbound

This paper cites Paritosh, and Lora Aroyo.

Towards Next Generation Data Engineering Pipelines Paritosh, and Lora Aroyo

Reference 27

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Observation af20534e-0d0c-466f-bf0a-71abb1bf04e2 · outbound

This paper cites Wang, Henry B.

Towards Next Generation Data Engineering Pipelines Wang, Henry B

Reference 28

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Observation ee335dc4-6420-4461-b28f-524d6137efeb · outbound

This paper cites Wang, Veda C.

Towards Next Generation Data Engineering Pipelines Wang, Veda C

Reference 29

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Observation 2cf102f1-7455-4173-a785-4a4da8951840 · outbound

This paper cites Blake and Paul Mangiameli.

Towards Next Generation Data Engineering Pipelines Blake and Paul Mangiameli

Reference 30

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source=arxiv_source observed=2026-08-06T16:18:45.202506Z digest=sha256:0242cbd3505197563346879d3bb37b24e49305f10a77aa87f04b9ae26d85d9fd

Observation 8c2b710f-3c43-41bd-b7de-ff9297953421 · outbound

This paper cites Requirements for Data Quality Metrics.

Towards Next Generation Data Engineering Pipelines Requirements for Data Quality Metrics

Reference 31

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Observation 1c881a64-4387-492c-8771-78050bee9a7d · outbound

This paper cites Automating Large-Scale Data Quality Verification.

Towards Next Generation Data Engineering Pipelines Automating Large-Scale Data Quality Verification

Reference 32

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Observation c264d572-5459-4d5d-aebd-bc8ea426cd29 · outbound

This paper cites An Advanced Big Data Quality Framework Based on Weighted Metrics.

Towards Next Generation Data Engineering Pipelines An Advanced Big Data Quality Framework Based on Weighted Metrics

Reference 33

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source=arxiv_source observed=2026-08-06T16:18:45.444627Z digest=sha256:287b5b3906391329f804f96f5c8fbffccfca6a24a9cc3b0fa6c4a817358d4036

Observation 276110cb-0a34-48e8-b365-d94ad012795e · outbound

This paper cites Ilyas, and Theodoros Rekatsinas.

Towards Next Generation Data Engineering Pipelines Ilyas, and Theodoros Rekatsinas

Reference 34

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Observation c1250404-282d-4db8-beaf-d2052589f7c1 · outbound

This paper cites Raha: A Configuration-Free Error Detection System.

Towards Next Generation Data Engineering Pipelines Raha: A Configuration-Free Error Detection System

Reference 35

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source=arxiv_source observed=2026-08-06T16:18:45.733770Z digest=sha256:4411c4bf4084693fec6588e498999de9de32c6c39eb1250ad3b43c7332ba4c71

Observation ed1b85c4-e91a-4df4-ba91-78d2f8c40ed1 · outbound

This paper cites Exploratory Training: When Annonators Learn About Data.

Towards Next Generation Data Engineering Pipelines Exploratory Training: When Annonators Learn About Data

Reference 36

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:45.839458Z digest=sha256:01d726f0a37fc498fb6cbc18cb7fe645ab9adf6e7636f0f6c8a140edaeec2cd6

Observation 68c935bb-21fc-4e92-a166-7089ba633af7 · outbound

This paper cites Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics.

Towards Next Generation Data Engineering Pipelines Visual Interactive Creation, Customization, and Analysis of Data Quality Metrics

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:45.999251Z digest=sha256:d8d32766198b3ac33252579c162e12329cf123712a55cfd5b4d067f15cd08b4b

Observation ebfbc258-4623-433f-b239-b96d8e04db31 · outbound

This paper cites o rl. FAIR is not enough - A Metrics Framework to ensure Data Quality through Data Preparation . In BTW , volume P-331 of LNI , pages 917--929. Gesellschaft f \.

Towards Next Generation Data Engineering Pipelines o rl. FAIR is not enough - A Metrics Framework to ensure Data Quality through Data Preparation . In BTW , volume P-331 of LNI , pages 917--929. Gesellschaft f \

Reference 38

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source=arxiv_source observed=2026-08-06T16:18:46.128170Z digest=sha256:901d1605ca9fb7deb0baf04bdccd0e4c01c3592b5109870dde8cd4bd06b5d10d

Observation ec7c24bb-e746-472b-9ed1-f1cd15e44842 · outbound

This paper cites a mper, Ralf Diestelk \.

Towards Next Generation Data Engineering Pipelines a mper, Ralf Diestelk \

Reference 39

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source=arxiv_source observed=2026-08-06T16:18:46.253498Z digest=sha256:92d2cfbc31eefe8be5bd607fa55e9b10babb1a57d4a237760c602cddd6838b2d

Observation 428eb458-3442-4c21-8bb9-2c47c38a6302 · outbound

This paper cites noWorkflow: Capturing and Analyzing Provenance of Scripts.

Towards Next Generation Data Engineering Pipelines noWorkflow: Capturing and Analyzing Provenance of Scripts

Reference 40

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:46.368926Z digest=sha256:e29868cc0816bcfa397b72417838e000b327106ade9f466fd513bfe18bab30c5

Observation 36dd8162-afe2-4d83-9672-766d80b8b989 · outbound

This paper cites Capturing and querying fine-grained provenance of preprocessing pipelines in data science.

Towards Next Generation Data Engineering Pipelines Capturing and querying fine-grained provenance of preprocessing pipelines in data science

Reference 41

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metadata mismatch
raw_fallback, observed 2026-08-06T16:19:07.197632Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:46.515199Z digest=sha256:54e05c0f50453edc592fe7c7d25fc4ec692d97be5dcded5bd739428028ba85e0

Observation 368701ce-cc81-4492-a63c-22e5cd2310ca · outbound

This paper cites Data distribution debugging in machine learning pipelines.

Towards Next Generation Data Engineering Pipelines Data distribution debugging in machine learning pipelines

Reference 42

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source=arxiv_source observed=2026-08-06T16:18:46.660215Z digest=sha256:81d5c49c033c4eb1adcda96d16920002091a2d9cd26d997497a7a94279011de6

Observation cdfcaff6-c6d0-4f25-9108-5fda5092d033 · outbound

This paper cites Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline.

Towards Next Generation Data Engineering Pipelines Fair preprocessing: towards understanding compositional fairness of data transformers in machine learning pipeline

Reference 43

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source=arxiv_source observed=2026-08-06T16:18:46.764359Z digest=sha256:c9a417f8d88395171090b6fc7ac617778098e8ccb5651e42998e03a588b59b20

Observation 079e99aa-4eec-4b8f-b5d6-63e9fdd0b989 · outbound

This paper cites Towards Explaining the Effects of Data Preprocessing on Machine Learning.

Towards Next Generation Data Engineering Pipelines Towards Explaining the Effects of Data Preprocessing on Machine Learning

Reference 44

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source=arxiv_source observed=2026-08-06T16:18:46.899502Z digest=sha256:2e4f3d64419b97d0aa67eef688f82237928175f253cfaf50a032374cb6af39ec

Observation 013d21c9-b9f5-41b2-a139-7dadde31483a · outbound

This paper cites Dead or Alive: Continuous Data Profiling for Interactive Data Science.

Towards Next Generation Data Engineering Pipelines Dead or Alive: Continuous Data Profiling for Interactive Data Science

Reference 45

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source=arxiv_source observed=2026-08-06T16:18:47.046949Z digest=sha256:0d2eea8990d5b1672dbbc9fc7bcd0a86797d2aac504e701c3fc59c707892b788

Observation e4df4c95-783c-49fa-a5d6-dfd6913d886a · outbound

This paper cites Data Profiling.

Towards Next Generation Data Engineering Pipelines Data Profiling

Reference 46

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source=arxiv_source observed=2026-08-06T16:18:47.151185Z digest=sha256:43762420c687f5043fa9d9e067f2291ecf5ae23406f39e00d29d0345e43fbb9c

Observation 3436a317-46ec-4dcd-9f7e-9b2402f0c8fa · outbound

This paper cites Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines.

Towards Next Generation Data Engineering Pipelines Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines

Reference 48

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source=arxiv_source observed=2026-08-06T16:18:47.424147Z digest=sha256:f8b785ec2276b14d3ec4650e308080d03d9afcbc572a042e417bc24aa4594070

Observation 4e97e5b3-d4f6-401a-8497-85f15606a431 · outbound

This paper cites Parameswaran.

Towards Next Generation Data Engineering Pipelines Parameswaran

Reference 49

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source=arxiv_source observed=2026-08-06T16:18:47.546129Z digest=sha256:fca5856308963a529e8c07c2b951113a1b42fb6a32d015ecd5eae4555a898aba

Observation ce2fca88-5788-4b9c-973b-142dc610ed1d · outbound

This paper cites A DaQL to Monitor Data Quality in Machine Learning Applications.

Towards Next Generation Data Engineering Pipelines A DaQL to Monitor Data Quality in Machine Learning Applications

Reference 50

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source=arxiv_source observed=2026-08-06T16:18:47.659269Z digest=sha256:eb6aeb975388cea5af9ae06c2f6e7dcd94da4d45944d078080171dbd96ce6fbb

Observation d88c3220-2028-491c-8d72-0c332fbad8fd · outbound

This paper cites DaQL 2.0: Measure Data Quality based on Entity Models.

Towards Next Generation Data Engineering Pipelines DaQL 2.0: Measure Data Quality based on Entity Models

Reference 51

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verified exact
doi, observed 2026-08-06T16:18:58.455980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:47.812609Z digest=sha256:46f15fa00980b1192643f6ac95671e90e0ed18fa5ff7b1dea8f57de7f74321da

Observation 2f94c143-25fb-4fba-9b4a-93fb3e676313 · outbound

This paper cites Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality.

Towards Next Generation Data Engineering Pipelines Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-06T16:19:12.618911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:47.931600Z digest=sha256:6c6b2b94c3c30b95734ccd9c9480fae4e4bf1e9b2f6d6ff47948422d065081b4

Observation 07e4821b-96d4-4c39-b7d8-f0d55af075d8 · outbound

This paper cites Schuler, Jitin Singla, Brinda Vallat, Kate L.

Towards Next Generation Data Engineering Pipelines Schuler, Jitin Singla, Brinda Vallat, Kate L

Reference 53

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source=arxiv_source observed=2026-08-06T16:18:48.097225Z digest=sha256:34c041735658892684bc6fb3aecf386f06466b395b64d3d37d638ce857cbe924

Observation c81970a9-042b-4869-933a-df366cb6bf88 · outbound

This paper cites An Empirical Study on the Design and Evolution of NoSQL Database Schemas.

Towards Next Generation Data Engineering Pipelines An Empirical Study on the Design and Evolution of NoSQL Database Schemas

Reference 54

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source=arxiv_source observed=2026-08-06T16:18:48.661781Z digest=sha256:518a82ad8a6a3cba38c03a5a5668c5b4b4a72f016367d8b145f47d671655ab91

Observation a1914ddf-841d-4de2-9108-9bf488ec2918 · outbound

This paper cites Schema Evolution in Wikipedia - Toward a Web Information System Benchmark.

Towards Next Generation Data Engineering Pipelines Schema Evolution in Wikipedia - Toward a Web Information System Benchmark

Reference 55

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raw_fallback, observed 2026-08-06T16:19:12.200356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:50.676754Z digest=sha256:c04fba4898a9d33c4fa24a9a02846c63178f6a62dd7c4c4c426b1d8bdfa1f485

Observation 4d12e214-8898-41c5-baff-4d94962b8bbb · outbound

This paper cites Self-healing and self-repairing technologies.

Towards Next Generation Data Engineering Pipelines Self-healing and self-repairing technologies

Reference 56

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verified fuzzy
raw_fallback, observed 2026-08-06T16:19:11.809922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:52.847609Z digest=sha256:d7d9c8e171ecf40469385314503aceb0d13ac74e4fe6f574c5695e954b785718

Observation da0be5f1-c65e-4229-ab64-18ebc8b7b24b · outbound

This paper cites DeBinelle: Semantic Patches for Coupled Database-Application Evolution.

Towards Next Generation Data Engineering Pipelines DeBinelle: Semantic Patches for Coupled Database-Application Evolution

Reference 57

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no resolver link, observed 2026-08-06T16:18:53.008184Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T16:18:53.008184Z digest=sha256:f51ea533cd946aaff33f679abde244e6248d679dcfd801132a7ca689a13f027b

Observation 428fe486-fac4-4bf2-9961-0b99e8951fac · outbound

This paper cites Schuler and Carl Kesselman.

Towards Next Generation Data Engineering Pipelines Schuler and Carl Kesselman

Reference 58

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no resolver link, observed 2026-08-06T16:18:53.188784Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:53.188784Z digest=sha256:35e9e20d848c96ad4ccca13e2d28178e9a3ae75e2b52d5b7217c3f9e5169ed45

Observation f9a8542b-6230-4250-8118-0efbd9f7f5e6 · outbound

This paper cites Understanding Uncertainty in Self-adaptive Systems.

Towards Next Generation Data Engineering Pipelines Understanding Uncertainty in Self-adaptive Systems

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:53.307232Z digest=sha256:45d7334bdb22e8ec9bc0999e15cc7e052d48d48c30fe1bff315d7feea93c5380

Observation 19f505fc-5681-42f2-a252-0a0fe1540be6 · outbound

This paper cites Uncertainty in Self-Adaptive Systems: A Research Community Perspective.

Towards Next Generation Data Engineering Pipelines Uncertainty in Self-Adaptive Systems: A Research Community Perspective

Reference 60

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local_arxiv, observed 2026-08-06T16:19:05.817326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:53.394976Z digest=sha256:2c588ed2737c7e4b784a775eeac6eee2d7044206244a983b18567bdf5911ef8b

Observation d501fa8c-e994-4810-bb39-d0822030c526 · outbound

This paper cites o rl, Daniel M \.

Towards Next Generation Data Engineering Pipelines o rl, Daniel M \

Reference 61

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metadata mismatch
raw_fallback, observed 2026-08-06T16:19:05.372021Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:53.515461Z digest=sha256:d93ba1c91e385bfc692ef90fca8d2294efa020e683186719da71f8bc52d5dfa5

Observation bd54e1f3-ac28-414f-bec4-0f4089822d44 · outbound

This paper cites Reducing Ambiguity in Json Schema Discovery.

Towards Next Generation Data Engineering Pipelines Reducing Ambiguity in Json Schema Discovery

Reference 62

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no resolver link, observed 2026-08-06T16:18:53.618032Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:53.618032Z digest=sha256:dd713f7509b84ba90decb53b036bf3459a76276a0c6649c3ffe3ed47687c1ffb

Observation cc023766-9ba6-4736-9a96-97523abe85c6 · outbound

This paper cites Compound Schema Registry.

Towards Next Generation Data Engineering Pipelines Compound Schema Registry

Reference 63

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verified exact
local_arxiv, observed 2026-08-06T16:18:58.158162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:53.728233Z digest=sha256:7e2403b397935c35bf458dd1c94d04d0ae9f99560a7045b1292a34cb92e6a8ea

Observation 5f1b989c-ee61-48d2-8700-aad06d443bbc · outbound

This paper cites Control-Theoretical Software Adaptation: A Systematic Literature Review.

Towards Next Generation Data Engineering Pipelines Control-Theoretical Software Adaptation: A Systematic Literature Review

Reference 64

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metadata mismatch
raw_fallback, observed 2026-08-06T16:19:04.830517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:53.848631Z digest=sha256:77365836f70452fa1f591f2358c46f77fabaa83a4868fb183009f232028aa1f4

Observation 3c3c7c93-03a1-4970-aec4-37e1c74d5afc · outbound

This paper cites Agent-Driven Automatic Software Improvement.

Towards Next Generation Data Engineering Pipelines Agent-Driven Automatic Software Improvement

Reference 65

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:53.988696Z digest=sha256:83adc3315b493527a6183e9df659a3b765f7b64fea4e279e8f6092b613d1c8dc

Observation e8520fca-c0d0-4a57-a1de-d85f9eb9c93f · outbound

This paper cites Fuzzy Self-Adaptation of Mission-Critical Software Under Uncertainty.

Towards Next Generation Data Engineering Pipelines Fuzzy Self-Adaptation of Mission-Critical Software Under Uncertainty

Reference 66

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doi, observed 2026-08-06T16:18:57.904811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.119601Z digest=sha256:47363987ff3edb6f69e6a3db3ba1eb4694b796ce593416bd7095b0a0b2ada385

Observation c91df8ca-20af-444e-affa-bedb5c32f194 · outbound

This paper cites Towards Evolution Capabilities in Data Pipelines.

Towards Next Generation Data Engineering Pipelines Towards Evolution Capabilities in Data Pipelines

Reference 67

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raw_fallback, observed 2026-08-06T16:19:11.363646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.233017Z digest=sha256:4901bcab4be768d6a25d45c42129606fe82be8c1ee5aeeac25f74386aa5dde0f

Observation b344b8bf-e27e-4ee2-b61f-720684b7cf4a · outbound

This paper cites Franklin, and Eugene Wu.

Towards Next Generation Data Engineering Pipelines Franklin, and Eugene Wu

Reference 68

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metadata mismatch
raw_fallback, observed 2026-08-06T16:19:04.319031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.357710Z digest=sha256:48ace0aaf50162ca418a65b4f436c9aba60d429e9656e862c04676b461f4bf29

Observation 50879f76-1b1d-42c5-a417-e1546ed087d2 · outbound

This paper cites What can Data-Centric AI Learn from Data and ML Engineering?.

Towards Next Generation Data Engineering Pipelines What can Data-Centric AI Learn from Data and ML Engineering?

Reference 69

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no resolver link, observed 2026-08-06T16:18:54.488535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:54.488535Z digest=sha256:c3271f90507319a70537f51ce268b168ef577c5f19afb2df89531f5549e0cb91

Observation a1b91f72-aa9d-432f-87f9-0d660be4d2a9 · outbound

This paper cites Johnson, Gyorgy Simon, and Constantin Aliferis.

Towards Next Generation Data Engineering Pipelines Johnson, Gyorgy Simon, and Constantin Aliferis

Reference 70

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doi, observed 2026-08-06T16:18:57.638807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.611345Z digest=sha256:3603b4005788882f7f9fc1fa3d340905ac609aded9f157291ccc1d029ec621d1

Observation 9cc6aeb6-19c9-4e29-b701-4dad951ee39b · outbound

This paper cites Towards an End-to-End Data Quality Optimizer.

Towards Next Generation Data Engineering Pipelines Towards an End-to-End Data Quality Optimizer

Reference 71

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no resolver link, observed 2026-08-06T16:18:54.737601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:54.737601Z digest=sha256:5e2dd2ff29e7549210e85e01113060a5fbacfa8d9d671798c275d77de9f88531

Observation 2ee479b9-5cd2-476b-ba0d-d295106e6bab · outbound

This paper cites Empirical comparison of supervised learning techniques for missing value imputation.

Towards Next Generation Data Engineering Pipelines Empirical comparison of supervised learning techniques for missing value imputation

Reference 72

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doi, observed 2026-08-06T16:18:57.388212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.844195Z digest=sha256:46f2c1481f7039c356e7efc2850b3e2f82809b561819be1f624557b8e1e1c33d

Observation 731f060b-0590-4b7f-aafc-8e9ec9c40b4f · outbound

This paper cites Kamrul Hasan, Md.

Towards Next Generation Data Engineering Pipelines Kamrul Hasan, Md

Reference 73

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verified fuzzy
raw_fallback, observed 2026-08-06T16:19:11.042201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:54.950468Z digest=sha256:81ef1fdf3a3abf94cfcc440bfe5c932e7fc77054b279e732e30d3720841e4266

Observation b9c52985-0620-405f-ae9e-a10a504d9556 · outbound

This paper cites o rl. ALPINE: Abstract Language for Pipeline Integration and Execution . In BTW Workshops , volume P-363 of LNI , pages 207--217. Gesellschaft f \.

Towards Next Generation Data Engineering Pipelines o rl. ALPINE: Abstract Language for Pipeline Integration and Execution . In BTW Workshops , volume P-363 of LNI , pages 207--217. Gesellschaft f \

Reference 74

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verified exact
doi, observed 2026-08-06T16:18:57.067167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:55.088711Z digest=sha256:d55ce6d79984924e32bbb8cc18de0b14eb4efd06d8d757667a4878b3205dd1ee

Observation 1ae8f269-34d4-4061-b9a5-93adc9d603d5 · outbound

This paper cites Towards machine learning-aware data validation.

Towards Next Generation Data Engineering Pipelines Towards machine learning-aware data validation

Reference 75

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verified fuzzy
raw_fallback, observed 2026-08-06T16:19:10.717533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T16:18:55.236087Z digest=sha256:dc023e6ce3e8564920e0c031ec30ed7a46a324e28b00f52551bc045f3409f931

Observation 9b410dab-750d-48a3-88d6-ff4df8bc98ae · outbound

This paper cites Transparent Data Preprocessing for Machine Learning.

Towards Next Generation Data Engineering Pipelines Transparent Data Preprocessing for Machine Learning

Reference 76

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unresolved
no resolver link, observed 2026-08-06T16:18:55.385634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a1450a14-2a19-4bd4-8b1f-591e679e4fd9 · outbound

This paper cites Breunig, Hans - Peter Kriegel, Raymond T.

Towards Next Generation Data Engineering Pipelines Breunig, Hans - Peter Kriegel, Raymond T

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-06T16:18:55.567021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:18:55.567021Z digest=sha256:9295271e389fb87277f0636dce96176605eeebad3881e02814cf099c34e8f5d1

Observation 27cf353c-c40b-48ac-a0fd-876777397731 · outbound

This paper cites Kramer, Valerie Restat, and Uta St \" o rl.

Towards Next Generation Data Engineering Pipelines Kramer, Valerie Restat, and Uta St \" o rl

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:19:10.323257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d1285b19-8c7e-4616-840f-2648b49ec632 · outbound

This paper cites Birefringent Graphene Oxide Liquid Crystals in Micro-channels for Optical Switch.

Towards Next Generation Data Engineering Pipelines Birefringent Graphene Oxide Liquid Crystals in Micro-channels for Optical Switch

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-06T16:18:55.852431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 32b2fe69-75f1-40ac-be31-ae15b4200396 · outbound

This paper cites A Survey on Application of Knowledge Graph.

Towards Next Generation Data Engineering Pipelines A Survey on Application of Knowledge Graph

Reference 80

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 5f63074e-964a-48ff-83f4-1b6bedd8688f · outbound

This paper cites Large Language Models for JSON Schema Discovery.

Towards Next Generation Data Engineering Pipelines Large Language Models for JSON Schema Discovery

Reference 81

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c03459ec-e8f2-4420-8aa6-d1b8f5322618 · outbound

This paper cites Towards Taming the Adaptivity Problem - Formalizing Poly-/MultiStore Topology Descriptions.

Towards Next Generation Data Engineering Pipelines Towards Taming the Adaptivity Problem - Formalizing Poly-/MultiStore Topology Descriptions

Reference 82

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation d4010b8f-901c-4870-80f6-ed1a887dfc07 · outbound

This paper cites Schema Extraction and Structural Outlier Detection for JSON-based NoSQL Data Stores.

Towards Next Generation Data Engineering Pipelines Schema Extraction and Structural Outlier Detection for JSON-based NoSQL Data Stores

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:19:09.753709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Pith citing papers

No inbound Pith citation observations are available.