# NTARC: A Data Model for the Systematic Review of Network Traffic Analysis Research
## 2 Scientific Data Repositories and Data Sharing Initiatives
Here, science objects are linked with tags in a bibliography-like form, making their reference easy. In this respect, Scientific Data, launched by the Nature Publishing Group in 2014, is a peer-reviewed journal that focuses on data descriptors, defined as \"a new type of publication that combines the narrative content characteristic of traditional journal articles with structured, curated metadata that outline experimental workflows and point to publicly archived data records\"[24]. Making research data, results, and materials more profitable is a necessary process that involves manual effort. By analyzing the relationship of institutional repositories with small science, [PERSON] et al. [25] claimed the necessity of redefining and standardizing the understanding of \"data sharing\", as well as promoting the establishment of data curation policies to empower the use of data repositories and protect against data misuse. In a similar line, the USA National Research Council recently published a study about digital curation with the title _Preparing the Workforce for Digital Curation_[26]. In this work, digital curation was deeply analyzed, discussing the current status and practices, society requirements, career paths, professional opportunities, derived benefits, and importance for the scientific advancement. Digital curation is defined as \"the active management and enhancement of digital information assets for current and future use\". In the conclusions, the authors first emphasized the limitations and missed opportunities due to the current immaturity and ad-hoc nature of digital curation. Digital curation is not well understood, but the application of digital curation in organization practices is expected to reduce costs and increase benefits. Some examples of organizations focused on promoting and developing digital curation are: the Digital Curation Center (DCC), the National Digital Stewardship Alliance (NDSA), Research Data Alliance (RDA), and the Committee on Data for Science and Technology (CODATA). Several examples exist that directly show how using data curation and metadata models can benefit science; for instance, the Linking Open Drug Data (LODD) project, which is a task force within the World Wide Web Consortium's (W3C) Health Care and Life Sciences Interest Group (HCLS IG). LODD gathered and connected reliable information about drugs that are publicly available coin the Internet, uncovering relevant questions for the science and the industry, and providing recommendations for best practices [27]. As for the NTA field, the main precedents have been developed by the Center for Applied Internet Data Analysis (CAIDA), i.e., DatCat, an Internet Measurement Data Catalog (IMDC), which is \"a searchable registry of information about network measurement datasets\" [28], and the Internet Traffic Classification [29], which is a collection of 68 curated metadata of NTA papers published between 1994 and 2009. Worth mentioning also is the IMPACTproject [30], but in a wider perspective. The NTARC model goes a step further and proposes a detailed collection of metadata that fits the structure shown in Figure 1. The goal is to improve the reuse of previous research by enabling the use of statistics on data summaries and metadata or meta-analysis (understanding meta-analysisin a broad sense). Meta-analysis consists of bringing together different studies about the same research question and applying statistics and analysis methods to obtain global conclusions and general perspectives. Meta-analysis is a perfect procedure to glue together small science in a global context and transform independent works into more profitable parts of the complete science building. This is specially true when the same research question is repeatedly faced by different teams in different places. Meta-analysis has been actually determinant in fields like medicine, pharmacology, epidemiology, education, psychology, business, or ecology. A well-known introduction to meta-analysis was offered by [PERSON] et al. [31].