Institutional Repository Single Sources of Truth
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The document discusses the challenges and strategies related to the ingestion of electronic theses and dissertations (ETDs) into institutional repositories (IRs) at the University of Zambia. It highlights issues such as delayed ingestion and metadata quality, while proposing a national ETD portal and the use of machine learning to improve ingestion workflows. The aim is to enhance the visibility of scholarly research outputs and potentially improve the university's global ranking.
![[1] Phiri, L. (2018). Research Visibility in the Global South: Towards
Increased Online Visibility of Scholarly Research Output in
Zambia. IEEE International Conference in Information and
Communication Technologies.
[2] Phiri, L. (2020). A Multi-Faceted Multi-Stakeholder Approach for
Increased Visibility of ETDs in Zambia. Cadernos BAD, (1).
https://doi.org/10.1017/S0269888910000032
[3] Arms, W. Y. (1995). Key concepts in the architecture of the digital
library. D-lib Magazine, 1(1).
Bibliography](https://image.slidesharecdn.com/talks-unza20-csc5741-singlesourceoftruth-200610101801/85/Institutional-Repository-Single-Sources-of-Truth-51-320.jpg)
Institutional Repository Single Sources of Truth
- 1. Institutional Repository Single Sources of Truth Lighton Phiri <lighton.phiri@unza.zm> DataLab Research Group Department of Library & Information Science University of Zambia http://lis.unza.zm/~lightonphiri Mining Descriptive Metadata from Electronic Theses and Dissertations Digital Object Bitstreams
- 2. 2June 9, 2020 About The DataLab Research Group at The University of Zambia ● The DataLab research group at The University of Zambia is composed of faculty staff and students—undergraduate and postgraduate—working in three main areas ○ Data Mining ○ Digital Libraries ○ Technology-Enhanced Learning http://datalab.unza.zm
- 3. 3June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 4. 4June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 5. 5June 9, 2020 Institutional Repositories are a Specialised Type of Digital Library Management Systems
- 6. 6June 9, 2020 Digital Objects are Composed of an Identifier, Bitstream and Metadata ● Identifier provides local and global uniqueness to objects ● Metadata provides auxiliary information about objects ● Bitstreams makeup the content associated with the objects http://www.dlib.org/dlib/July95/07arms.html
- 7. 7June 9, 2020 Ingestion of Digital Objects into IRs Involves Numerous Moving Parts ● Digital object bitstreams need to be verified ● Digital object metadata needs to be prepared ○ Preparing metadata is time consuming and error-prone since data needs to be encoded using specific metadata schemes: e.g Dublin Core or ETD-ms ● Multi-step IR workflows http://open.uct.ac.za/handle/11427/29435
- 8. 8June 9, 2020 Supervised Machine Learning 101: Labeled Data is Used to Train a Prediction Model Gmail Spam Detection ● Model implemented by training estimators using using labelled data ● f(x)—Spam/Not Spam classification ○ x—Email address, subject, email content ○ Labels—Mailbox user tagging; Gmail automatic detection
- 9. 9June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 10. 10June 9, 2020 The Online Visibility of Research Output Influences Global Institution Rankings (1/2) http://www.webometrics.info
- 11. 11June 9, 2020 The Online Visibility of Research Output Influences Global Institution Rankings (1/2) http://www.webometrics.info
- 12. 12June 9, 2020 The Online Visibility of Research Output Influences Global Institution Rankings (2/2) http://www.webometrics.info
- 13. 13June 9, 2020 The Online Visibility of Research Output Influences Global Institution Rankings (2/2) http://www.webometrics.info
- 14. 14June 9, 2020 The Online Visibility of Research Output Influences Global Institution Rankings (2/2) http://www.webometrics.info
- 15. 15June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Distribution
- 16. 16June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Distribution
- 17. 17June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Distribution ● 523 publications against ~854 faculty staff ● ONLY 476 (55.7%) faculty staff with online publications
- 18. 18June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Impact
- 19. 19June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Impact
- 20. 20June 9, 2020 Google Scholar Extraction: The University of Zambia 2018 Scholarly Output Impact 30% of faculty staff research with ZERO impact
- 21. 21June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 22. 22June 9, 2020 Challenges With Ingestions of “ETDs” into The UNZA IR ● Ingestion of ETDs is not timely ● Huge time gaps between submission and eventual ingestion of ETDs ● ETDs have missing and incorrect descriptive metadata Phiri, L. (2018) “Towards Increased Online Visibility of Scholarly Research Output in Zambia”. URL: http://lis.unza.zm/archive/handle/123456789/227
- 23. 23June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 24. 24June 9, 2020 Towards a Zambia National Electronic Theses and Dissertations Portal (1/2) ● Works underway to deploy a national ETD portal ○ IRs implement open standards and protocols that facilitate harvesting of digital objects ● Stakeholders required to harmonise curation http://lis.unza.zm/portal
- 25. 25June 9, 2020 Towards a Zambia National Electronic Theses and Dissertations Portal (2/2) http://www.hea.org.zm ● Ideally the portal is aimed at providing central access to all ETDs produced by HEIs in Zambia ○ Source of knowledge for not-for-profit organisations and policy makers ○ Source of knowledge for taxpayers—entities that fund research
- 26. 26June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 27. 27June 9, 2020 A Multi-Faceted Multi-Stakeholder Approach for Increased Visibility of ETDs (1/2) ● Experimentation with various approaches and techniques ○ System-driven approaches ○ Data-driven approaches ○ People-driven approaches ● Involve key stakeholders in order to mainstream the implementation of IRs in Zambian HEIs ○ Knowledge exchange with HEIs in Zambia
- 28. 28June 9, 2020 A Multi-Faceted Multi-Stakeholder Approach for Increased Visibility of ETDs (2/2)
- 29. 29June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 30. 30June 9, 2020 Subject Specific Institutional Repositories as Potential Solutions for Delayed Ingestions ● Is it feasible to use subject institutional repositories at The UNZA? ○ Subject IR setup in the Department of Library and Information Science ○ Subject IR scored a mean SUS score of 65.5—”Okay-> Good” Mbewe, M., Moonga, H., Mwewa, M., Sikazindu, N., and Mwale, N. (2018) “Investigating the Feasibility of Using Subject IRs: A Case Study at The UNZA”. URL: http://lis.unza.zm/archive/handle/123456789/189 http://lis.unza.zm/archive
- 31. 31June 9, 2020 Identification of Subject Controlled Vocabularies Should Involve Stakeholders ● What is the effect of integrating controlled vocabularies sets in IRs? ○ Sanbox IR integrated with LCSH vocabulary set ○ Mean SUS score computed ○ 68.6—With Vocabularies ○ 65.1—No Vocabularies Chipangila, B., Liswaniso, E., Mawila, A., Mwanza, P., and Nawila, D. (2019) “Effectiveness of Integrating Controlled Subject Vocabulary Sets in the UNZA IR”. URL: http://lis.unza.zm/archive/handle/123456789/2236
- 32. 32June 9, 2020 Effective Workflows for Ingestion of Electronic Theses and Dissertations ● What workflows would be effective at reducing the turnaround time between submission and ingestions of ETDs ○ Stakeholders involved in submission workflow of ETDs Banda, A. (2019--Present) “Investigating the Workflows Involved in the Ingestion of ETD into IRs”. Work-in-Progresss
- 33. 33June 9, 2020 Improved Electronic Theses and Dissertation Metadata Quality ● How can high-quality ETD matadata be ingested into IRs? ● How can submission workflows be modified to facilitate ingestion of ETD-ms encoded metadata? Banda, M., Chinyama, A., Maambo, H., Mulomba, H., and Mwitwa, K. (2020--Present) “Improved Electronic Theses and Dissertation Metadata Quality”. Work-in-Progresss http://www.ndltd.org/standards/metadata
- 34. 34June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 35. 35June 9, 2020 Timely and Consistent Ingestion of ETDs Can be Facilitated by Automatic Classification ● Implementation of classification models to automatically classify IR digital objects using the minimum possible input from graduate students: “The ETD Manuscript” ○ The ETD manuscript bitstream is considered the “single source of truth” ○ Metadata prepared by staff that work with IR potentially have inconsistencies Phiri, L. (in press) “Automatic Classification of Digital Objects for Improved Metadata Quality of ETDs”. International Journal of Metadata, Semantics and Ontologies
- 36. 36June 9, 2020 Three Classification Models Implemented for Classifying ETD Type, Subject and Collection ● Text features extracted from a set of core bitstream portions—ETD Title, ETD Abstract, ETD Title Page and ETD pages—to classify ETD manuscripts ETD Type ETD Subjects IR Collection
- 37. 37June 9, 2020 Text Features are Extracted from Single Source of Truth—Bitstream ● Textual content mined from PDF manuscripts ○ Cover/title pages ○ Preliminary pages ● Textual content mined from metadata for training ● PDF document metadata ● Curated datasets from external repositories
- 38. 38June 9, 2020 Text on Title Pages Exhibit Characteristics that Enable ETD Classification ● Textual content mined from PDF manuscripts ○ Cover/title pages ○ Preliminary pages ● Textual content mined from metadata for training ● PDF document metadata ● Curated datasets from external repositories
- 39. 39June 9, 2020 Descriptive Dublin Core Encoded Metadata Used for Training Classifiers ● Textual content mined from PDF manuscripts ○ Cover/title pages ○ Preliminary pages ● Textual content mined from metadata for training ● PDF document metadata ● Curated datasets from external repositories
- 40. 40June 9, 2020 PDF Metadata Provide Auxiliary Metadata Information Such as Total Pages ● Textual content mined from PDF manuscripts ○ Cover/title pages ○ Preliminary pages ● Textual content mined from metadata for training ● PDF document metadata ● Curated datasets from external repositories
- 41. 41June 9, 2020 Metadata was Harvested Using OAI-PMH, Bistreams were Harvested Using OAI-ORE ● OAI-PMH used to harvest all ETD descriptive metadata elements ● OAI-ORE used to harvest all ETD PDF documents
- 42. 42June 9, 2020 The Models are Reasonably Accuracy to be Integrated with IR ● ETD Type—98.1% ● ETD Collection— 81.1% ● ETD Subjects—81.7% ● The models would still need to be incorporated into an application that requires “some” human intervention
- 43. 43June 9, 2020 Models are Deployed as Flask-Based API Endpoints (1/2) https://github.com/lightonphiri/etd_autoclassifier
- 44. 44June 9, 2020 Models are Deployed as Flask-Based API Endpoints (2/2) https://datalab-apis.herokuapp.com/api/collection
- 45. 45June 9, 2020 Outline ● Definitions and Key Concepts ● Contextualisation ● The Problem ● The Bigger Picture ● What We Think Can Work ● Past and Current Projects ● Data-Driven Ingestion of ETDs ● Conclusion and Future Work
- 46. 46June 9, 2020 Formatting Guidelines for ETD Metadata Harvested by National ETD Portal http://lis.unza.zm/portal
- 47. 47June 9, 2020 Automatic ETD-ms Metadata Generation http://www.ndltd.org/standards/metadata
- 48. 48June 9, 2020 Effective Workflows for Ingestion of Electronic Theses and Dissertations ● What is the feasibility of implementing machine learning models for automatically classifying IR objects? ○ This work goes beyond ETDs to include other digital object types ● How can downstream services be integrated with the models? M’sendo, R. (2019--Present) “Mult-Faceted Automatic Classification of Institutional Repository Digital Objects”. Work-in-Progress
- 49. 49June 9, 2020 Online Visibility of Research can Potentially Change the Global Reputation of HEIs http://www.webometrics.info
- 50. 50June 9, 2020 Q & A Session ● Comments, concerns and complaints?
- 51. [1] Phiri, L. (2018). Research Visibility in the Global South: Towards Increased Online Visibility of Scholarly Research Output in Zambia. IEEE International Conference in Information and Communication Technologies. [2] Phiri, L. (2020). A Multi-Faceted Multi-Stakeholder Approach for Increased Visibility of ETDs in Zambia. Cadernos BAD, (1). https://doi.org/10.1017/S0269888910000032 [3] Arms, W. Y. (1995). Key concepts in the architecture of the digital library. D-lib Magazine, 1(1). Bibliography