Page History

...

The BTE is a Java framework developed by the Hellenic National Documentation Centre (EKT, www.ekt.gr) and consists of a 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 a data loading step, the a processing step (record filtering and modification) and the an output generation. Data A data loader provides the system with a set of Records, the processing steps step is responsible for filtering or modifying these records and the output generator outputs them in the appropriate format.

Standard The standard BTE version comes with offers several 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 the "-e" must option must be a valid email of a DSpace user and value of option the "-c" must option must be the collection handle the items will be imported totarget collection handle.

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.

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

 
Explanation of beans:

 

beam bean   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 )

...

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 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 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" character. The default value id is "," and that is why the CSV data loader doesn't need to specify this property.

c) quoteChar: this This property specifies the the quote char of the csv and the character used in the CSV file. The default value is the double quote character (").

For the OAIPMHDataLoader, the properties that are supported supported properties are:

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

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

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

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

Case Studies

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

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 to one of the supported formats or you need to create a new data loader. To do this, just create a new Java class that implements the following java Interface Java interface from BTE:
 

      gr.ekt.bte.core.DataLoader

 
of BTE. You will need to implement the following method:
 

      public RecordSet getRecords() throws MalformedSourceException {

in which you have to create records - most propably probably you will need to create your own Record class (by implementing the 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 in order 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 the following BTE abstact class:

    gr.ekt.bte.core.AbstractFilter

You will need to implement the following 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 the following BTE abstact class:

      gr.ekt.bte.core.AbstractModifier

You will need to implement the methodfollowing 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 latterlater, 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 to linearWorkflow, the they will run the one after the other in the specified order.