TITLE: IRIS Software Protocol
AUTHORS: Leonardo Zilli, Erica Andreose, Salvatore Di Marzo

[DESCRIPTION]
This project aims to investigates the discoverability of University of Bologna's scholarly output within OpenCitations Meta, a platform that stores and delivers bibliographic metadata for alle the publications involved in OpenCitations Index which contains recording citations allowing the user to visualize all of the citation links between a document and another. Specifically, this project aims to analyze the coverage of University of Bologna's publications within the OpenCitations Meta, particularly those deposited in the IRIS institutional repository. Various publication types are observed to discern patterns in representation. Utilizing OpenCitations data, the citation impact of these IRIS publications is quantified, encompassing both the citations they receive and those they provide. Additionally, the study delves into the nature of citations, distinguishing between those involving publications within IRIS and those referencing external sources. The study unveils the citation impact of IRIS publications, clarifying their influence within the scholarly community. By dissecting citations, the research also delineates the interplay between internal and external citations, providing a deeper understanding of the institution's scholarly ecosystem. The methodology used will be all compliant to the core values of Open Science, the data and the software used will all be made available to allow the user to replicate, reproduce and validate the conclusions drawn by the end results of the project, that will hold significance for researchers and academic institutions, facilitating informed decision-making and fostering a deeper understanding of scholarly communication dynamics.

[BEFORE_START]
Before starting, we suggest to make sure you have Python3.x installed on your computer, in addition, in order to correctly execute the provided scripts, you must install the required libraries:
requirements.txt

[GUIDELINES]
To let the user with complete reproducibility of the protocol, links to the data used are provided here.
Download link for the UNIBO IRIS bibliographic data dump, dated 14 March 2024: https://amsacta.unibo.it/id/eprint/7608/
OpenCitations Meta can be accessed and queried through a REST API: https://w3id.org/oc/meta/api/v1 

The code used for this research, along with the data produced to answer to the research questions can be found in the github repository.

[STEPS]
SECTION: IRIS Dataset Preparation
1. 
 
After downloading the IRIS dataset, the contents appear divided into 7 different csv files, descriptive as the following:
- "ODS_L1_IR_ITEM_CON_PERSON.csv": information about the people involved in the publications (authors, editors, etc.)
- "ODS_L1_IR_ITEM_DESCRIPTION.csv": the string containing the name of the authors and other related metadata of publications
- "ODS_L1_IR_ITEM_IDENTIFIER.csv": the identifiers (including DOIs) of publications
- "ODS_L1_IR_ITEM_LANGUAGE.csv": the language in which the publication has been written (when applicable)
- "ODS_L1_IR_ITEM_MASTER_ALL.csv": basic metadata information of publications (title and date of publication) 
- "ODS_L1_IR_ITEM_PUBLISHER.csv": the publishers of publications
- "ODS_L1_IR_ITEM_RELATION.csv": additional metadata related to the context of publications (publication venue, editors, etc.)

These files are connected among themselves through a unique item ID tied to each entry, after we gathered the files we converted them into dataframes with the pandas1 library.

1(https://pandas.pydata.org/)
SECTION: OpenCitations Meta Dump preparation
5. OpenCitations Meta has been queried through the use of the OpenCitations Meta april 2024 dump. 
 
After downloading the zip file, the csv files contained in the dataset are turned into parquet file for easier handling:
 

SECTION: Data Visualization
10. The visualizations of the results obtained are computed with the _ _ library.


 


 


 


 



 





SECTION: ID sanification
7. The DOIs and ISBNs from the IRIS dataset are quite dirty and need to be cleaned.
 

 

The two identifiers are then merged into a single list:
 

SECTION: Research Question answering
9.2. What is the coverage of the publications available in IRIS (strictly concerning research conducted within the University of Bologna) in OpenCitations Meta?

 

SECTION: Research Question answering
9.3. Which are the types of publications that are better covered in OpenCitations Meta?


 

SECTION: Research Question answering
9.4. What is the amount of citations (according to OpenCitations Index) coming from the IRIS publications that are involved in OpenCitations Meta (as citing entity and as cited entity)?

 

SECTION: Research Question answering
9.5. How many of these citations come from and go to publications that are not included in IRIS?

 

SECTION: Research Question answering
9.6. How many of these citations involve publications in IRIS as both citing and cited entities?

 

SECTION: OpenCitations Index Dataset Querying
9. 
 
The OpenCitations Index Sparql endpoint allowed us after querying it, to download a csv file of the results of our queries which we then transformed into dataframes.

These are the queries that gave as a result the files:


 

 

 

SECTION: OpenCitations Index Dataset Querying
9.1. We then use these csv files to create the pandas DataFrames that will be used to perform the analyses.

 

SECTION: IRIS Dataset Preparation
2. 2 of the csv files are converted into Dataframes 
 

SECTION: IRIS Dataset Preparation
3. The DataFrames are filtered to remove rows that do not have neither DOI or ISBN ids.

 

 

SECTION: IRIS Dataset Preparation
4. The df_iris_identifier DataFrame is joined with the master dataframe to append the title and the date of publication of the publications to the df_iris_identifier_filtered

 



SECTION: RQ 1. What is the coverage of the publications available in IRIS (strictly concerning research conducted within the University of Bologna) in OpenCitations Meta?
8. 
 

SECTION: OpenCitations Meta Dump preparation
6. The parquet files are then read by using polars' data streaming capabilities: