Importing Items via basic bibliographic formats (Endnote, BibTex, RIS, TSV, CSV)

This functionality is an extension of that provided by Importing and Exporting Items via Simple Archive Format  so please read that section before continuing. It is underpinned by the Biblio Transformation Engine (https://github.com/EKT/Biblio-Transformation-Engine )

About the Biblio-Transformation-Engine (BTE)

The BTE is a Java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr ) and consists of programmatic APIs for filtering and modifying records that are retrieved from various types of data sources (eg. databases, files, legacy data sources) as well as for outputing them in appropriate standards formats (eg. database files, txt, xml, Excel). The framework includes independent abstract modules that are executed seperately, offering in many cases alternative choices to the user depending of the input data set, the transformation workflow that needs to be executed and the output format that needs to be generated. 

The basic idea behind the BTE is a standard workflow that consists of three steps, the data loading step, the processing step (record filtering and modification) and the output generation. Data loader provides the system with a set of Records, the processing steps is responsible for filtering or modifying these records and the output generator outputs them in the appropriate format.

Standard BTE version comes with predefined Data Loaders as well as Output Generators for basic bibliographic formats. However, Spring Dependency Injection can be utilized in order to load custom data loaders, filters, modifiers and output generators.  

BTE in DSpace

The functionality of batch importing items in DSpace using the BTE has been incorporated in the "import" script already used in DSpace for years.

In the import script, there is a new option (option "-b") to import using the BTE and an option -i to declare the type of the input format. All the other options are the same apart from option "-s" that in this case points to a file (and not a directory as it used to) that is the file of the input data. However, in the case of batch BTE import, the option "-s" is not obligatory since you can configure the input from the Spring XML configuration file discussed later on. Keep in mind, that if option "-s" is defined, import will take that option into consideration instead of the one defined in the Spring XML configuration.
 
Thus, to import metadata from the various input formats use the following commands:

Keep in mind that the value of option "-e" must be a valid email of a DSpace user and value of option "-c" must be the collection handle the items will be imported to.

BTE Configuration

The basic idea behind BTE is that the system holds the metadata in an internal format using a specific key for each metadata field. DataLoaders load the record using the aforementioned keys, while the output generator needs to map these keys to DSpace metadata fields.

BTE configuration file is located in path: [dspace]/config/spring/api/bte.xml and it's a Spring XML configuration file that consists of beans. (If these terms are unknown to you, please refer to Spring Dependency Injection web site for more information)  

Explanation of beans:

 

beam   id= "gr.ekt.bte.core.TransformationEngine"

This bean is instantiated when the import takes place. It deploys a new  BTE transformation engine that will do the transformation from one format to the other. It needs one input argument, the workflow (the processing step mentioned before) that will run when transformation takes place. Normally, you don't need to modify this bean.

 

bean   id= "org.dspace.app.itemimport.DataLoaderService"

Within this bean we declare all the possible data loaders that we need to support. Keep in mind that for each data loader we specify a key that can be used as the value of option "-i" in the import script that we mentioned earlier. Here is the point where you would add a new custom DataLoader in case the default ones doesn't match your needs.

 Moreover, this bean holds the "outputMap" which is a Map between the internal keys that BTE uses to hold metadata and the DSpace metadata fields. (See later on, how data loaders specify the keys that BTE uses to hold the metadata)

 

bean   id= "linearWorkflow"

This bean describes the processing steps. Currently there are no processing steps meaning that all records loaded by the data loader will pass to the output generator, unfiltered and unmodified. ( See next section "Case studies" for info about how to add a filter or a modifier )

bean   id= "gr.ekt.bteio.loaders.BibTeXDataLoader"

bean   id= "gr.ekt.bteio.loaders.CSVDataLoader"

bean   id= "gr.ekt.bteio.loaders.TSVDataLoader"

bean   id= "gr.ekt.bteio.loaders.RISDataLoader"

bean   id= "gr.ekt.bteio.loaders.EndnoteDataLoader"

bean   id= "gr.ekt.bteio.loaders.OAIPMHDataLoader"

Each one of the 5 first data loaders (which are actually "file" data loaders) has the following properties:

a) filename: it is a String that specifies the filepath to the file that the loader will read data from. If you specify this property, you do not need to give the option "-s" to the import script in the command prompt. If you, however, specify this property and you also provide a "-s" option in the command line, the option "-s" will be taken into consideration by the data loader.

b) fieldMap: it is a map that specifies the mapping between the keys that hold the metadata in the input file and the ones that we want to have internal in the BTE. This mapping is very important because the internal keys need to be declared in the "outputMap" of the "DataLoadeService" bean. Be aware that each data loader has each own input file keys. For example, RIS loader uses the keys "T1, AU, SO ... " while the TSV or CSV use the index number of the column that the value resides.

Some loaders do have more properties:

CSV and TSV (which is actually a CSV loader if you look carefully the class value of the bean) loaders have some more properties:

a) skipLines: it is a number that specifies the first line of the file that loader will start reading data. For example, if you have a csv file that the first row contains the column names, and the second row is empty, the the value of this property must be 2 so as the loader starts reading from row 2 (starting from 0 row). The default value for this property is 0.

b) separator: it is a value to specify the separator between the values in the same row in order to make the columns. For example, in a TSV data loader this value is "\u0009" which is the "Tab". The default value id "," and that is why the CSV data loader doesn' t need to specify this property

c) quoteChar: this property specifies the the quote char of the csv and the default value is "

For the OAIPMHDataLoader, the properties that are supported are:

a) fieldMap: the same as above, the mapping between the keys that hold the metadata in the input and the ones that we want to have internal in the BTE.

b) serverAddress: the base address of the OAI server. Base address can be specified also in the "-s" option of the command prompt. If is specified in both places, the one in command prompt is preferred.

c) prefix: the metadata prefix to be used in the OAI requests

So, in case you need to pass through the system more metadata fields than the ones that are specified by default, you need to change the data loaders configuration and the output map

Case Studies

Since, DSpace administrators may have incorporated their own metadata scheme within DSpace (apart from default Dublin Core), someone may need to configure BTE to match their custom schemes.

1) I have my data in a format different from the ones that are supported by this functionality. What can I do?
 
Either you try to easily transform your data in a supported format or you need to create a new data loader. To do this, just create a new Java class that implements the following java Interface 
 

      gr.ekt.bte.core.DataLoader

 
of BTE. You will need to implement the method
 

      public RecordSet getRecords() throws MalformedSourceException {

in which you have to create records - most propably you will need to create your own Record class (by implementing gr.ekt.bte.core.Record class) and fill a RecordSet. 

 
After that, you will need to declare the new DataLoader in the Spring XML configuration file (in the bean with id: " org.dspace.app.itemimport.DataLoaderService ") using your own key. Use this key as a value for option "-i" in the import key so as to specify that your data loader must run.

 
 
2) I need to filter some of the input records or modify some value from records before outputting them
 
In this case you will need to create your own filters and modifiers.
 
To create a new filter, you need to extend BTE abstact class:

    gr.ekt.bte.core.AbstractFilter

You will need to implement the method:

    public   abstract   boolean  isIncluded ( Record  record )

Return false if the specified record needs to be filtered, otherwise return true.
 
To create a new modifier, you need to extend BTE abstact class:

      gr.ekt.bte.core.AbstractModifier

You will need to implement the method

    public   abstract   Record modify ( Record record )

within you can make any changes you like in the record. You can use the Record methods to get the values for a specific key and load new ones (For the latter, you need to make the Record mutable) 

After you create your own filters or modifiers you need to add them in the Spring XML configuration file as in the following example:

 
<bean   id= "customfilter"   class= "org.mypackage.MyFilter" />

<bean   id= "linearWorkflow"  class= "gr.ekt.bte.core.LinearWorkflow" >
  <property   name= "steps" >
  <list>
       <ref bean= "customfilter"/>  
  </list>
  </property>
</bean>

You can add in the linearWorkflow  as many filters and modifiers you like, the will run the one after the other in the specified order.