A Data Dictionary DefinitionA Data Dictionary is a collection of names, definitions, and attributes about data elements that are being used or captured in a database, information system, or part of a research project. It describes the meanings and purposes of data elements within the context of a project, and provides guidance on interpretation, accepted meanings and representation. A Data Dictionary also provides metadata about data elements. The metadata included in a Data Dictionary can assist in defining the scope and characteristics of data elements, as well the rules for their usage and application. Show
Why Use a Data Dictionary?Data Dictionaries are useful for a number of reasons. In short, they:
What Are Data Standards and Why Should I Use Them?Data Standards are rules that govern the way data are collected, recorded, and represented. Standards provide a commonly understood reference for the interpretation and use of data sets. By using standards, researchers in the same disciplines will know that the way their data are being collected and described will be the same across different projects. Using Data Standards as part of a well-crafted Data Dictionary can help increase the usability of your research data, and will ensure that data will be recognizable and usable beyond the immediate research team. Resources and ExamplesNorthwest Environmental Data Network, Best Practices for Data Dictionary Definitions and Usage USGS: Data Dictionaries and Metadata If you'd like more information on research data curation and management, please schedule a consultation: What is a data dictionary?A data dictionary is a collection of descriptions of the data objects or items in a data model to which programmers and others can refer. Often, a data dictionary is a centralized metadata repository. Data dictionaries sometimes play a role in data modeling, which creates a tangible diagram of object relationships that lists each object's name, assigned data values and defined relationships. The type of data, such as text, image or binary value, is described; possible predefined default values are listed; and a brief textual description is provided. This collection of information can be referenced through a data dictionary. For example, a bank or group of banks could model the data objects involved in consumer banking. They could then provide a data dictionary for the bank's programmers. The data dictionary would describe each set of data in its data model for consumer banking, such as "account holder" and "available credit." Types of data dictionariesThere are two types of data dictionaries: active and passive. Active data dictionaries are created within the databases they describe and automatically reflect any updates or changes in their host databases. This avoids any discrepancies between the data dictionaries and their database structures. Passive data dictionaries are created separately from the databases they describe to act as a repository for data information. Passive data dictionaries require additional work to stay in sync with the databases they describe. As such, database managers must handle passive directories with care to ensure there are no discrepancies. Data dictionary componentsThe specific components of a data dictionary can vary, but they typically take the form of various types of metadata. Examples of these components include the following:
How to create a data dictionaryWhen planning a data dictionary build, it is important to consider all available data management resources, including associated databases and spreadsheets. Most database management systems, as well as information systems created by computer-aided software engineering tools, contain integrated active data dictionaries. For example, the Performance Analyzer tool for Microsoft Access, which analyzes and documents databases, can create data dictionaries from data either based in or connected to a Microsoft Access implementation. If it's not possible to automatically generate a machine-readable data dictionary, it's recommended to submit a data dictionary from a single source as a spreadsheet file. Spreadsheets can be made into data dictionaries within Microsoft Excel. There are also online templates that can come in handy when creating this type of data dictionary. Pros and cons of data dictionariesData dictionaries can be valuable tools for the organization and management of large data listings. These are some of the biggest benefits of using a data dictionary:
However, data dictionaries can also prove difficult for some to manage. Here are some of the downsides:
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What is in the data dictionary?A Data Dictionary is a collection of names, definitions, and attributes about data elements that are being used or captured in a database, information system, or part of a research project.
What are the benefits of a data dictionary?To summarize, the benefits of a data dictionary include faster detection of data anomalies, improved data quality, availability of trustworthy data, greater transparency within data teams, better regulatory compliance, and faster analytics.
What is a data dictionary used for in SQL?In SQL Server, the data dictionary is a set of database tables used to store information about a database's definition. & The dictionary contains information about database objects such as tables, indexes, columns, datatypes, and views.
What is a data dictionary and how is it used in healthcare?A medical data dictionary is a database that describes the organization and logical structure of the medical data found in a clinical database. It contains “metadata”—or “data about data”—that describes the content, structure, and relationships between clinical data.
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