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  • Writer's pictureResearch Ecosystems

Importance of Metadata Quality for Institutional Academic Archives and Research Information Systems

In information technology usage, the meta prefix denotes data-related items. Metadata is a structured set of information that identifies elements of an information resource, enables it to be used or managed, explains, locates, and facilitates access. Metadata identifies items that contain certain information such as type, length, textual description, and other attributes. In short, metadata refers to any item about the data.

"High-quality data is accurate, usable, complete, compliant, consistent, reliable, actionable, and relevant."

"Quality metadata with fully defined content directly affects their searchability and reuse."

This metadata quality is extremely important in research information systems and academic archives that support international standards. Rich standards of metadata are of vital importance in order to obtain accurate and functional reports, and for systems to work seamlessly with other systems in the world.

Metadata Types:

Descriptive metadata: It enables to discover and identify information sources.

Structured metadata: Defines data models and reference data.

Administrative metadata: Provides information to help manage the resource.

What are the metadata quality elements?

Factors to consider when creating a quality metadata are:

Accuracy: Does the data accurately represent the real-world entity or event?

Consistency: Does the data contain no contradictions?

Availability: Is data accessible now and over time?

Completeness: Does the data contain all the data items that represent the entity?

Compliance: Does the data follow accepted standards?

Reliability: Is the data based on reliable sources?

Workability: Is the data machine readable?

Relevance: Does the data contain the appropriate amount of data?

Timeliness: Is data representative of the real situation and is it published?

What Is The Benefit Of Creating Quality Metadata?

Providing reliable and organized information ensures that the research ecosystem functions properly.

Quality metadata acts as a source or key to the data.

It makes people and institutions accessible and visible.

It provides a general view of the accumulation of knowledge.

It mediates the contribution of the source or data it represents to the society at the highest level.

It provides an accurate and quality reporting opportunity.

It provides interoperability with other systems.

How to Create Quality Metadata?

The metadata record summarizes key information about the data, making it easy to find and work with specific data examples.

Researchers in the academic community, librarians, university administrators, publishers, funders and other stakeholders have important duties in creating quality metadata for the research ecosystem.

Authors seek credit for their work for tenure and promotion. Librarians want an accurate understanding of their faculty and department's research interests and collection needs. They look for faculty publications that can be stored in institutional archives. Universities monitor and report research produced by faculty and doctoral students to demonstrate that they are meeting their obligations as public and private institutions.

When creating metadata for the research ecosystem:

All metadata information of the source must be collected completely.

Metadata fields are repeated in publications broadcasting in a foreign language.

Metadata is entered into databases by using a metadata tool in accordance with the determined/used standards.

Control of metadata entries is provided.

A final check is made before publishing.

When writing metadata for the research ecosystem:

The title is the most important criterion in helping to find the publication or work in the research ecosystem. A good title should answer questions such as what, where, when, who.

Keywords should be determined correctly. Three to five well-written, correct keywords are essential in data discovery.

For keywords, authority indexes (Thesaurus) should be used.

Since the metadata will be read by a computer, symbols that will cause misunderstanding should not be used.

Tabs, indents and carriage returns should not be used.

Spelling language rules must be followed in metadata.

Metadata Fundamentals

The National Information Standards Institute (NISO) has divided metadata into four basic classes. Metadata types and properties are classified as follows:

Quality Metadata Key Areas

For research information systems the EuroCRIS standards are essential, for academic repositories the above fields are Dublin Core (DC) compliant and allow sharing and collation between data archives. However, inclusion of non-DC compatible elements and domain-specific information in the metadata is important to create quality metadata.

Various standards have been developed to collect and present metadata in a certain order. The best-known and most frequently used metadata standards are the Dublin Core Metadata Initiative (DC) and the Data Documentation Intiative (DDI). The list available at can be used to decide on the most appropriate metadata standard for the purpose.

Metadata Standards Supported by OAI

Open Archives Initiatives metadata standards supported by the OAI-PMH protocol (Open Archives Intiative Protocol for Metadata Harvesting).

As Research Ecosytems, the highest quality metadata standards are used in the services we offer to universities. The data of the sources belonging to the institution are singularized and enriched by our expert team. In addition, our product GCRIS, which can be used as a research information system and academic archive, works with metadata in accordance with all standards and is recognized by all international systems. Again, DSpace 7x software, for which we provide installation and service support, is prepared with metadata bearing all these standards and offered to institutions. Today, most of the guides prepared on this subject in our country have been prepared by projects and teams, including our founding partners.

Increasing the interoperability of data across different systems is imperative in research ecosystems. In this respect, topics such as the principles of setting up metadata standards, matching between various metadata standards, search and access protocols should continue to be developed with metadata working groups, editors, librarians and other stakeholders.

Quality metadata guides the research ecosystem cycle by providing regular, accurate and reliable information. It prevents duplication of research and saves time for researchers. It makes people and institutions visible.

An image of the IYTE GCRIS database

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