Abstract
Archives are evolving. Analog archives are becoming increasingly digitized and linked with other cultural heritage institutions and information sources. Diverse forms of born-digital archives are appearing. This diversity asks for systematic ways to characterize existing archives managing physical or digital records. We conducted a systematic review to identify and understand how archives are characterized. From the 885 identified articles, only 15 were focused on archives’ characterization and, therefore, included in the study. We found several characterization features organized in three main groups: archival materials, provided services, and internal processes. © 2021, Springer Nature Switzerland AG.

Abstract
Wikipedia is a free, multilingual, and collaborative online encyclopedia. Nowadays, it is one of the largest sources of online knowledge, often appearing at the top of the results of the major search engines, being one of the most sought-after resources by the public searching for health information. The collaborative nature of Wikipedia raises security concerns since this information is used for decision-making, especially in the health area. Despite being available in hundreds of idioms, there are asymmetries between idioms, namely regarding their quality. In this work, we compare the quality of health information on Wikipedia between idioms with 100 million native speakers or more, and also in Greek, Italian, Korean, Turkish, Persian, Catalan and Hebrew, for historical tradition. Quality metrics are applied to health and medical articles in English, maintained by WikiProject Medicine, and their versions in the above idioms. With this, we contribute to a clarification of the role of Wikipedia in the access to health information. We demonstrate differences in both the quantity and quality of information available between idioms. English is the idiom with the highest quality in general. Urdu, Greek, Indonesian, and Hindi achieved lower values of quality.

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Abstract
Research data management (RDM) practices are critical for ensuring research success. Data can assume diverse formats and data in image format have been understudied in RDM. To understand image management habits in research, we have conducted semi-structured interviews with researchers from four research domains. Most researchers do not formally manage their images, nor do they develop RDM plans. They assume that image management is not a topic discussed at project meetings. In turn, they tend to perform some individual practices, depending on the context and their own opinion, such as creating captions to describe the images and organizing and storing the images in specific locations. However, they see these habits as necessary and admit that they will start to do so in a formal and collaborative way with the working group. These results provide valuable information on practical aspects of the use and production of images in research.

Abstract
- A patient's ability to recall and retrieve health information contributes to a better health management. HealthTalks was developed to address these issues by recording a summary of a medical appointment, uttered by the physician, and transcribing it. For each appointment, the user can also take free-text notes. Nowadays, search engines have become a ubiquitous part of everyone's life and are expected on most applications. Here, we describe the development of a search engine for HealthTalks. The app's characteristics demand a lightweight and offline engine, which requires a specific solution rather than an existing library or service. Our approach combines SQLite's Full-Text Search 4 module, which includes ngram indexing, with traditional information retrieval techniques to rank the documents. We created a test collection with summaries of clinical appointments (our documents), information needs, search queries, and relevance assessments for an initial search engine evaluation. Using this test collection, we assessed performance using NDCG@10, the first rank position of a totally relevant result, and query latency. Results are promising, with an average NDCG of 0.97. The median rank position of the first relevant result varies between 1.9 and 1.95, depending on the use of 4-gram character tokenization, an aspect that did not significantly affect the results. We expect this work to be useful for future developments of full-text search engines in mobile environments.