This article, which is intended for users with the data source manager role, describes Oracle Health Sciences Select supported data sources and describes how to map and import regular data sources. We've included the following sections:
- Understanding composite and regular data sources
- Managing multiple data sources
- Citeline data source
- Mapping and importing regular data sources
- Procedures index
Understanding composite and regular data sources
Select supports two types of data sources: composite and regular.
Composite
Composite data sources contain complex, structured data. With composite data sources, Select handles all five composite data entities that comprise a trial-site (sometimes called a study-site):
- Investigator
- Institution
- Trial
- site
- trial-site
This means that Select's composite data model imports five unique files: investigator, institution, trial, site, and trial-site that Select combines internally to create a single site row.
Benefits of composite data sources:
- Unique institution records combine with investigator records to form sites. Instead of having limited fields to import institution staff records, the investigator file can handle any number of institution staff in a nested structure of: first name, last name, email, phone, and role.
- Instead of being limited to an investigator’s primary and secondary email, the investigator file can import any number of investigator email addresses.
- When creating a master list of sites for evaluation, if the data source contains composite records, users can additionally filter by: therapeutic area, indication, drug class, and/or study phase.
- For studies involving composite data sources, Select calculates an Investigator score, which is the average of all site scores for the site's investigator. This score is listed for each of the investigator’s sites.
Important: Composite data sources are managed only by Oracle administrators. Contact your Oracle Project Manager to manage configuration and import of data into these data sources.
Regular
Regular data sources accept data in a flat, CSV (comma separated value) file format. In this flat data model, each CSV row is a site and that row includes investigator, institution, and site data.
You can configure regular data sources and import data into regular data sources using the Select application. Once you've imported data into a new data source, contact your Oracle Project Manager who can associate the new data source to your studies.
Preferred sites: This type of source allows CRO preferred sites to bypass study parameter filters and move into the Master List. This option requires upload and mapping of a CSV format file with CRO preferred sites. The source file must contain a column labeled "preferred_site" and must specify TRUE or FALSE for each row in the source.
Pre-selected sites: You can also upload study-specific, pre-selected site lists and have only those sites included in the data source displayed on the Master List. To use this functionality, the data source must include a is_pre_selected_site column, which must be set to True for all sites in the data source.
Managing multiple data sources
Select provides the ability to define how data is merged when multiple customer data sources are attached to a study. For standard Select data columns, Oracle defines how each column will handle data merges. For custom data columns, customer data source managers will define the method by which data is merged for a particular column. Available merge methods for custom columns are:
- concatenate data (string array)
- highest priority data source wins (all data types)
- sum data (integer, real)
- average (integer, real)
Example: a custom column “Equipment list” is defined at the site level in two customer data sources as a string array. In data source 1, it includes “fMRI” and “portable X-ray”. In data source 2, it includes only “portable infusion pump” for the same site record. When both data sources are attached to a single study, and the column is defined to concatenate array values, the resulting site record will include “fMRI, portable X-ray, and portable infusion pump” for the data column “Equipment list.”
Please contact your Oracle Project Manager to coordinate custom column merging methods prior to data load.
Citeline data source
Select offers a study data source with the full Citeline subscription. Select customers who have this subscription level can request that an Oracle administrator add this data source to their studies. Please contact your Oracle Project Manager for subscription details.
Mapping and importing regular data sources
If you have the data source manager role in Select, you will have access to the Data source management page.
Creating a new regular data source
Create a new data source for any dataset that you want to import and merge into the Select site profile database. You will determine the unique identifier for the data source and set up definitions for each field in the data source.
Publishing a regular data source
Once data definition is complete, you can publish the data source to your account in Select. The data source will be private to your account.
Importing to regular data source
For any published data source in your account, you can import data in CSV format.
Disambiguating data
The Select data disambiguation match resolution feature surfaces possible matching records, within an account's private data sources, that require human review and intervention to resolve.
While Select automatically identifies and merges strongly matched records, potential matches pending intervention are viewed as individual site records in the Master List. Records identified as matches by a user in your account who has Data Source Management permissions are then merged so the Master List reflects only the single master record. See the Disambiguating data procedure below.
Procedures index
Important: The remainder of this article, including all contents of the Procedures index, refers to managing regular data sources. If your organization will be using composite data sources, please contact your Oracle Project Manager for assistance.
- Create a new regular data source
- Map regular data source fields to standard Select data fields
- Create custom data fields
- Publish a regular data source
- Import data for a published regular data source
- Define data sources for a study
- Disambiguate data
Create a new regular data source
- From the home page under manage click account data sources.
- In the Data source management page, click Create new data source.
- In the Manage data source creation page, in section 1, enter the Data source name and Description.
- Click Import CSV button.
- Select the CSV with all the fields in your data source from your desktop, and click OK.
Map regular data source fields to standard Select data fields
- In section 2, Map your data source fields, in the Your source data fields subsection, the fields from your CSV display. Search for any field using the free text search box or by using the filters.
- Find the unique identifier field and click the radio button to the right of the field.
- (Optional) Hover over the information icon (
)to view a description of the Select field.
- (Optional) You can find matchable fields by viewing the matchlogic icon (
). Select uses matching fields to identify matching sites in other data sources.
- (Optional) Hover over the information icon (
- To map a field to a Select standard field, first find your field in left column ("Your source data fields").
- Next, find the associated Standard field in the middle column ("Select data fields").
- Now, drag the source data field onto the corresponding Select data field.
When you've completed the procedure above, you'll notice that, under the field name, the name of the field it was mapped to displays. You can remove the mapping by clicking on the remove () icon.
Create custom data fields
If you can't find an appropriate Select standard field to map your source data field to, you can create a custom data field.
- To create a custom field, first find your source data field in the left column.
- Click + drag your source data field onto the Create a custom data field section in the middle column.
- In the right column, the name of the newly created custom field displays.
- You can change the column's Display name.
- You can enter a short Description.
- By default, Select will pick a data type based on the sample value included in your CSV. You can change the Data type by picking a different one from the drop-down.
- Next pick the Category that the field belongs to. The categories determine if the field is just for searching or used for both searching and scoring. Click the computer monitor (
) to view a description.
- Pick a sub-category for your field.
- Next, pick a section for your field. If none of the sections in the drop-down apply to your field you can create a new section by typing the section name in the free text field.
- If you want to use your field for filtering, click the check box. This field will become visible in the search criteria.
- If you want to use your field for investigator scoring, click the checkbox, and choose a scoring methodology. This field will affect the search criteria.
All changes are automatically saved. Click the computer monitor () at any time to view a setting's description.
Publish a regular data source
- On the top right of the Manage data source definition page, click the Publish button.
- You will see a pop-up asking you to confirm your action. Click Publish again to publish the data source to your account.
Import data for a published regular data source
- From the home page under manage, click account data sources. On the Data source management page, you will see a list of all the data sources for your account. If you see a green checkmark (
) for a data source under the Published column, you can import data for the data source.
- Under Import column, click upload (
).
- In the Import data source data page, click Import CSV.
- The data fields in your data import CSV must match those of the data fields you mapped while creating the data source.
Once you complete the procedure above, you will see a message that data is being imported and you will see a progress indicator under the Date column. Once the data import is complete, the imported data appears under Date column.
The imported data records are displayed in the Data tab in the Imported data preview table. If there are any errors in the source file, the error messages are displayed in the Error tab.
Define data sources for a study
Note: you must have Data Source Manager permissions to complete this procedure.
- From the home page under manage, click study data sources.
- Choose one or more data source(es) from the Available list on the left and move to the Selected list on the right using the > button. You can choose multiple sources at one time; hold down the Shift key on your keyboard.
- To modify the ranking of data sources, in the Selected list, click one or more sources and use the up/down Ranking arrows to the left of the Selected list to reorder the list.
- Click Done.
Note: Sources that display in light gray are managed by Oracle administrators. If you need to remove an Oracle data source from the Selected list, please contact your Oracle Project Manager.
Disambiguate data
Note: you must have Data Source Manager permissions to complete this procedure.
- From the home page under manage, click source data matches.
- Select displays a list of potential matching records in pairs. Fields in bold font indicate a match. For each pair of potential matching records, review the data.
- If the records match, click Yes to resolve the potential match and display the merged record in the master list.
- If the records do not match, click No to remove the pair from the potential matches list. Two separate records will continue to display in the master list.
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